The DataWeave Blog

Category: E Commerce

  • Online Furniture Pricing Strategies on 2019 Prime Day

    Online Furniture Pricing Strategies on 2019 Prime Day

    Just as with electronics, other retailers actually offered far better discounts than Amazon during Prime Day 2019.

    Online furniture sales have risen significantly since the 2000s, driven largely by a growing array of products, and even more so by the convenience of avoiding travel and crowded stores. According to Statista, online furniture and homeware sales were estimated to reach approximately $190 billion in 2018, with China and the United States accounting for over $60 billion in revenue each.

    Thus, furniture has quickly become a key product category during sale events globally – and Prime Day was no different. At DataWeave, we got down to figuring out exactly how plum those deals were this year.

    Our Methodology

    We tracked the pricing of several leading retailers selling home and furniture products to assess their pricing and product strategies during the sale events. Our analysis was focused on additional discounts offered during the sale to estimate the true value that the sale represented to its customers. We calculated this by comparing product prices on Prime Day versus the same prices prior to the sale. Our sample consisted of the top 1,000 ranked products across 10 popular product types, including beds, dining table sets, sofas, entertainment units, and coffee tables – analyzed for five retailers (Amazon, Home Depot, Target, Walmart, and Wayfair).

    The Verdict

    As we found in the electronics category, there were surprising price spikes in this category too – with Target reporting an average increase as high as 14.7%, and Amazon clocking a still moderately high 9.4%. Target also reported the highest distribution of products with price markups. Home Depot indicated the lowest price increase at 4.6%.

    When it came to additional discounts, Amazon fell short of expectations – at 4.7%, it offered the lowest average among its competitors. Target, on the other hand, was extremely aggressive both in terms of additional discounts and volume of discounted products.

    To conclude, all the retailers observed seemed to be keeping a close watch on their margins by countering price reductions with nearly equivalent surges elsewhere in their assortment.

    While there was no single product type that was found to be popular across all five retailers, it was clear that Target was again the most aggressive at offering discounts. It also had among the largest product ranges on discount.

    Amazon chose to follow a very moderate route both in terms of average discount and discounted product volume.

    Additional discounts across popularity levels

    We determined popularity using a combination of average review rating and number of reviews, and the resulting scores were categorized as low, moderate, and high.

    There doesn’t seem to have been much of a focus on low-popularity products in terms of additional discounts. Most of the attention was focused on products with moderate popularity, since there isn’t much of a need to be aggressive on price for highly popular products, and products with lower popularity aren’t really worth promoting.

    The only retailer that offered a higher discount on its most popular products was Home Depot. Walmart, too, seemed reluctant to let go of the opportunity to capitalize on popularity – it chose to offer the same discount on moderately as well as highly popular products.

    Interestingly, Walmart seems to have a disproportionately large share of products in its low popularity category – something it should possibly evaluate in the future in terms of brand quality, products, and service.

    The percentage distribution of products mostly indicated a linear relationship, with the highest distribution usually being offered for highly popular products. The exception was Wayfair, which offered a much larger array in its moderately popular category.

    Additional discounts across product “premiumness” levels

    Premiumness was calculated as the average selling price before the sale event. This was divided into four percentile blocks, with higher percentile blocks indicating higher selling prices.

    Most of the discounting activity seems to have occurred in the lower end of the premium spectrum, with a view to protect margin – despite a largely healthy distribution of products across percentile ranges. This indicates a clear strategy to protect margins, while also promoting attractive offers to draw traffic.

    However, there are a couple of exceptions – Target was consistent throughout the “premiumness” spectrum, resulting in the highest overall discounting activity. Home Depot too was aggressive, but selectively so – it chose attractive pricing for the lower and higher ends of its assortment.

    As expected, many retailers showed higher discounting activity in the higher ranks of their listing pages. As usual, though, there are a few exceptions here too. Home Depot and Wayfair indicated unusual patterns – perhaps relying on search results as opposed to organic listing page results. On the other hand, Target again indicated a consistent pattern, with mostly similar discounts across visibility levels.

    Overall, across all parameters analyzed, both the Electronics and Furniture categories have been treated quite similarly in terms of pricing activity by most retailers. Is Prime Day really all about its marketing hype, or will it live up to its promise in at least one segment? Stay with us to find out as we follow through with our series of articles analyzing various product categories on this year’s Prime Day.

  • A Study of Deals on Amazon Prime Day 2019 | DataWeave

    A Study of Deals on Amazon Prime Day 2019 | DataWeave

    Our preliminary analysis reveals that Prime Day 2019 had other retailers offering better deals than Amazon in many cases.

    As Prime Day extended into an additional day this year, Amazon seems to be hitting the right note with its customers, going by the revenue it’s raking in. This year, the longest Prime Day event ever witnessed a sales increase of 72% – overtaking Black Friday and Cyber Monday combined.

    At DataWeave, we were curious to find out how prime these deals were, and if in fact other retailers were offering better discounts. We started with the electronics category, which remains among the most popular categories year on year.

    Our Methodology

    We tracked the pricing of several leading retailers selling consumer electronics to assess their pricing and product strategies during the sale event. Our analysis was focused on additional discounts offered during the sale to estimate the true value that the sale represented to its customers. We calculated this by comparing product prices on Prime Day versus the prices prior to the sale. Our sample consisted of up to the top 1,000 ranked products across 10 popular product types in consumer electronics on Amazon, Best Buy, Target, and Walmart.

    The Verdict

     

    What we found most surprising was that across retailers, some portions of the assortment underwent price increases as well. While Amazon indicated the lowest increase at 9.1%, Best Buy indicated an increase as high as 27.1%. However, Amazon reported the highest percentage of products (6.9%) that showed a price increase.

    Equally surprising was that Amazon reported the lowest price reduction at 6.3% – Walmart, Target, and Best Buy in fact reduced their prices by much larger margins than Amazon did. A point to note here, however, is that Amazon did report the highest percentage of additionally discounted products – with Best Buy coming in at a close second.

    This goes to show that Prime Day, for all its hype, does not in truth offer the best deals to Amazon shoppers. This, of course, is expected based on the competitors’ perspective of wanting to avoid losing market share. As a result, shoppers would be well advised to compare prices across websites to find the best deal.

    Top product types by additional discount

     

    USB flash drives were a popular product category across all four retailers analyzed, with Best Buy offering the best average additional discount at 40.7%. Other popular product types ranged from the usual personal devices such as mobile phones, tablets, and smartwatches to home appliances such as refrigerators and TVs.

    Additional discounts across popularity levels

    We determined popularity using a combination of average review rating and number of reviews, and the resulting scores were categorized as low, moderate, and high.

    Interestingly, discounts were not found to be directly proportional to popularity. Except Walmart, all the retailers tended to offer the best discounts on products that enjoyed moderate popularity. This makes sense, since there isn’t a strong need to be aggressive on price for highly popular products in any case. On the other hand, products with lower popularity aren’t really worth promoting. Walmart, which was the exception, reported a higher discount on low- and high-popularity products than it did on moderately popular products.

    The percentage distribution of products did mostly show a directly proportional relationship, with the highest distribution usually being offered for highly popular products. The exception in this case was Best Buy, which evidenced a much higher distribution in its moderately popular goods.

    Additional discounts across product “premiumness” levels

    Premiumness was calculated as the average selling price before the sale event. This was divided into four percentile blocks, with higher percentile blocks indicating higher selling prices.

    In general, all retailers were found to have slightly higher additional discounts in the lower end of the “premiumness” spectrum. This is still a smart move, as it enables sellers to save on margin while still promoting attractive discount percentages. Interestingly, Amazon offered the lowest additional discount – a flat 5% – across all categories, despite offering more or less competitive product distributions compared to other retailers.

    Additional discounts across visibility levels

    Here, too, the lower end of the spectrum mostly witnessed higher additional discounts. This tactic actually offers double benefits – one, the most attractive discounts are offered in the higher realms of visibility, thus effectively enticing consumers to buy these products, and two, it helps build a low price perception (despite this not holding good as one delves deeper into the higher ranks). Again, it’s interesting to note that Amazon didn’t offer the highest discounts here either – in fact, it mostly offered the lowest additional discounts.

    All in all, it seems that Prime Day isn’t all it’s hyped up to be, at least not in the Electronics segment. How about other categories? Watch this space for more insights!

  • The Importance of Pricing Parity for Brands

    The Importance of Pricing Parity for Brands

    With bricks-and-mortar stores steadily increasing their online presence, the balancing act of pricing online and in-store is now more important and complex than ever. Companies spend years building brands and brand equity. Yet, a misplaced or poorly executed pricing strategy to handle both online and offline pricing can erode that equity with consumers very quickly.

    This problem is not new. It first started when Clubs like Costco and Sam’s started popping up in the 80’s. Suddenly, brands had to figure out a way to balance Club and Grocery pricing while taking advantage of a new, fast-growing channel. The biggest difference between now and then is that consumers now can check prices within seconds on their phone.

    So, how do you avoid losing your brand equity while ensuring price parity across online and offline channels?

    The key areas to consider are:

    1. Product Mix

    Do you have a broad enough mix of product sizes and case configurations for each channel? To maximize your sales and minimize your price disruption, reviewing your supply chain and product mix to ensure you are able to deliver value to both online and offline retailers is critical. Each channel is looking for ways to improve and maximize your brand sales. If you do not give them the right size and case configuration to enable them to increase margins, you will end up relying disproportionately on trade spend (dollars a brand spends with a retailer to promote products) to do so, or find your product on page 212 of every search.

    Examples of this strategy can be seen with companies offering only “bundled” items such as 12 cans or a large case on online marketplaces, while other retailers offer individual cans for purchase. This allows your online partners to make up margin by shipping a full case and not going through the process of breaking down a case and shipping single units. Also, this allows bricks-and-mortar retailers to have a sharper price point to lure consumers into the store. This strategy has played out well for many brands as they dealt with the rise of Club stores and can be played successfully in e-commerce as well, benefiting all parties.

    2. Price Lists

    Do you have harmonized price lists that do not favor one channel over another? If you do not, you are likely subsidizing the higher list cost in a channel with trade spend, which is highly inefficient. A single price list that provides an adequate price slope between the various sizes across your product range will maximize your ability to manage both channel pricing and brand equity.

    The single largest mistake brands tend to make is thinking that offering “net price” price lists to online marketplaces will benefit them while they use trade dollars in bricks-and-mortar stores to cater to EDLP (Everyday low price) customers. This approach is quite inefficient in many ways, and consumes valuable time and resources that can otherwise be better utilized. Having a single price list with the same price offered to all retailers allows for a more manageable and equitable pricing environment. It also enables a more profitable distribution of trade spend across the most effective areas to invest in for each retailer.

    I have worked with two brands in the past – one that managed two separate price lists and one that we implemented as a single-standard. While the one with the single price list saw sales grow and trade spend remain constant, the other saw trade spend double in just two years as it got caught in a scenario of always having to placate one side of the equation or the other.

    3. Trade Spend

    Today’s brands need to focus on a balanced trade spend strategy to address each channel’s unique needs. Using trade spend with online retailers can be tricky, as the channel is usually assumed to be the lowest priced anyway. Still, it can be used to drive traffic and offset supply chain costs, in order to ensure sufficient margins for the retailer, which will keep you off the CRAP (Can’t Realize A Profit) lists. Meanwhile, as JC Penny quickly learned when it made the disastrous shift to EDLP, consumers still want in-store discounts and sales.

    The best approach I have worked with is to set a single dead net price inclusive of all trade. For example, if your product’s standard list cost is $6.80 and you have a dead net price for promotions (or EDLP) of $5.40, then all retailers – online and bricks-and-mortar – are on equal footing. The only variance in the price for consumers will be the margin each operator chooses to take. This approach is not without issues, as you have to apply all elements of trade spend (such as ad fees, etc.) to the promotional unit costs to ensure you are truly capturing the dead net cost of the retailer.

    Still, the advantage of utilizing this approach is that when a retailer complains about the price another is offering to consumers, the conversation turns to margins being taken and not the cost of the product. At the very least, this approach provides a common ground on which to have a constructive conversation with all retailers.

    So why does this all matter so much to a brand?

    The road to selling online is littered with disaster and missed expectations for sales. Most manufacturers that jumped to online sales without considering pricing quickly learned that abandoning one channel for another does not lead to increased sales. Conversely, we have seen a few brands go from online only to in-store as well. These brands seem to have learned from the others’ mistakes and rarely will you find price variances between the online and offline channels. Instead, you tend to see these brands growing, as online consumers start experiencing the brand in-store.

    A Business To Community study by Larisa Bedgood in 2019 showed that “lower price” was second to only “convenience” for why consumers shop online, while 51% of consumers said that the biggest drawback to shopping online was not being able to touch and feel the product. Brands that are able to bridge the gap and provide consumers with the convenience of online while also showing up well in-store at the right price point will be able to break out of the stagnate 1-2% (if they are lucky) growth most CPG companies are experiencing. If online selling is growing 40-50% a year, why are these companies only managing brand declines and flat growth? I believe it is mainly due to the lack of a proper pricing parity strategy for the two channels along with a lack of actionable e-commerce data.

    Brands that do not focus on all three areas listed above often find themselves in a constant churn of conversations with retailers on all sides, which will typically lead to either online marketplaces or bricks-and-mortar stores deprioritizing the brand in promotions or search. Finding and setting a level playing field will allow for a balanced trade spend and growth for brands on both platforms, while also enabling a brand to break out of the net 1% growth that is plaguing a lot of CPG brands today.

    Outside of deploying basic pricing principles for your brand, I would also suggest early and strong investments in data, systems and people to monitor your brand’s health and pricing. Many brands jumped online without any way to monitor the consumer conversation around the brand or the pricing of the brand online. Not having the tools and resources in place to do this can lead to a quick and long-lasting erosion of brand equity and sales. Most, if not all, large manufacturers have subscribed to POS data for years and fully understand how to analyze this data. But the world has shifted. If your organization has not invested in digital shelf analytics, you may be driving blind and unaware that your brand is losing equity, which equals losing consumers and sales.

    Using a combination of pricing principles and e-commerce data mining tools will help you maintain price parity and brand relevance, while keeping you from becoming the last brand of choice for consumers, regardless of where they shop.

  • Compete Profitably in Retail: Leveraging AI-Powered Competitive Intelligence at Massive Scale

    Compete Profitably in Retail: Leveraging AI-Powered Competitive Intelligence at Massive Scale

    AI is everywhere. Any retailer worth his salt knows that in today’s hyper-competitive environment, you can’t win just by fighting hard – you have to do it by fighting smart. The solution? Retailers are turning to AI in droves.

    The problem is that many organizations regard AI as a black box of sorts – where you can throw all your data (the digital era’s blessing that feels like a curse) in at one end and have miraculously meaningful output appearing out the other. The reality of how AI works, however, is a lot more complex. It takes a lot of work to make AI work for you – and then to derive value out of it.

    Image Source: https://xkcd.com/1838

    Following the advent of the digital era, businesses across industries, particularly retail, were left grappling with massive amounts of internal data. To make things worse, this data was unstructured and siloed, making it difficult to process effectively. Yet, businesses learned to leverage simple analytics to extract relevant data and insights to affect smarter decisions.

    But just as that happened, the e-commerce revolution stirred things up again. As businesses of all shapes, sizes, and types moved online, they suddenly became a whole lot more vulnerable to other players’ movements than they were just about a decade ago, when buyers rarely visited more than one store before they made a purchase. In other words, retailers are now operating in entire ecosystems – with consumers evaluating a number of retailers before making a purchase, and a disproportionate number of players vying for the same consumer mindshare and share of wallet.

    Thus, external data from the web – the largest source of data known to man at present – is becoming critical to business’ ability to compete profitably in the market.

    Competing profitably in the digital era: Can AI help?

    As organizations across industries and geographies increasingly realized that their business decisions were affected by what’s happening around them (such as competitors’ pricing and merchandize decisions), they started shifting away from their excessive obsession with internal data, and began to look for ways to gather external data, integrate it with their internal data, and process it all in entirety to derive wholesome, meaningful insights.

    Simply put, harnessing external data consistently and on a large scale is the only way for businesses to gain a sustainable competitive advantage in the retail market. And the only way to practically accomplish that is with the help of AI. Many global giants are already doing this – they’re analyzing loads of external data every minute to take smarter decisions.

    That said, though, what you need to know is that all this data, while publicly available and therefore accessible, is massive, unstructured, noisy, scattered, dynamic, and incomplete. There’s no algorithm in the world that can start working on it overnight to churn out valuable insights. AI can only be effective if enormous amounts of training data is constantly fed back into it, coaxing it to get better and more astute each time. However, given the scarcity of readily available training datasets, limited and unreliable access to domain-specific data, and the inconsistent nature of the data itself, a majority of AI initiatives have ended up in a “garbage in, garbage out” loop that they can’t break out of.

    What you need is the perfect storm

    At DataWeave, we understand the challenge of blindly dealing with data at such a daunting scale. We get that what you need is a practical way to apply AI to the abundant web data out there and generate specific, relevant, and actionable insights that enable you to make the right decisions at the right time. That’s why we’ve developed a system that runs on a human-aided-machine-intelligence driven virtuous loop, ensuring better, sharper outcomes each time.

    Our technology platform includes four modules:

    1. Data aggregation: Here, we capture public web data at scale – whatever format, size, or shape it’s in – by deploying a variety of techniques.

    2. AI-driven analytics: Since the gathered data is extremely raw, it’s cleaned, curated, and normalized to remove the noise and prepare it for the AI layer, which then analyzes the data and generates insights.

    3. Human-supervised feedback: Though AI is getting smarter with time, we see that it’s still far from human cognitive capabilities – so we’ve introduced a human in the loop to validate the AI-generated insights, and use this as training data that gets fed back to the AI layer. Essentially, we use human intelligence to make AI smarter.

    4. Data-driven decision-making: Once the data has been analyzed and the insights generated, they can either be used as it to drive decision-making, or then integrated with internal data for decision-making at a higher level.

    With intelligent, data-backed decision-making capabilities, you can outperform your competitors

    Understandably, pricing is one of the most popular applications of data analytics in retail. For instance, a leading, US-based online furniture retailer approached us with the mission-critical challenge of pricing products just right to maximize sell-through rates as well as gross margin in a cost-effective and sustainable manner. We matched about 2.5 million SKUs across 75 competitor websites using AI and captured pricing, discounts, and stock status data every day. As a result, we were able to affect an up to 30% average increase in the sales of the products tracked, and up to a 3x increase in their gross margin.

    DataWeave’s powerful AI-driven platform is essentially an engine that can help you aggregate and process external data at scale and in near-real time to manage unavoidably high competition and margin pressures by enabling much sharper business decisions than before. The potential applications for the resulting insights are diverse – ranging from pricing, merchandize optimization, determination of customer perception, brand governance, and business performance analysis.

    If you’d like to learn more about our unique approach to AI-driven competitive intelligence in retail, reach out to us for a demo today!

  • 6 Smart Pricing Strategies for eCommerce Success

    6 Smart Pricing Strategies for eCommerce Success

    Over the last decade, the proliferation of e-commerce and the consequent surge in competitiveness among retailers has brought focus to one of the most critical drivers of success in online retail: pricing. According to McKinsey, an average 1% increase in price can translate into an 8.7% increase in operating profits (with the assumption that there’s no loss of volume). Yet, the company estimates that up to 30% of pricing decisions fail to provide the best price – every year. That’s a potential impact of millions in lost revenue for most modern-day retailers, a fact only made worse by the irony that in today’s times of automation and big data, there’s no shortage of intelligence to facilitate the best decision-making.

    What you need is the ability to gather and rationalize all the data out there – of competitor prices, price perceptions, market dynamics, buyer behavior, etc. – in good time to price your products just right for maximum margin and revenue. The best part? Effective product pricing contributes significantly toward fostering a great customer experience, too.

    Once you have your intel in place, there are plenty of eCommerce pricing strategies to choose from – it’s only a matter of identifying the metrics that matter the most to your business goals. That said, there are several models that have gained widespread popularity and acceptance over the years, like the following six:

    1) Introductory pricing

    This is a common marketing strategy used in the e-commerce space, where you draw consumer focus to a newly launched product or service, or the fact that you’re a new entrant in a market. There are two ways to do this – one is to start with steep discounts (particularly during sale events, and often in partnership with the consumer brand) with the aim of winning over more market share. At the other end is the strategy of setting relatively high initial prices. This works best for “exclusive offer” or “limited edition” opportunities; for instance, the opportunity to be the first to own the latest iPhone model.

    2) Cost-linked pricing

    In this method, you calculate how much it costs to sell a product and add a pre-determined margin to the final cost. In the world of online retail, product cost amounts to a lot more than the mere sum of manufacturing costs. For instance, it includes the procurement, labor, software, sales and marketing, shipping, and overhead costs that contribute to the total cost of housing it as long as it’s unsold. Therefore, all these costs need to be factored when determining the final product price. While the advantages of this model are its simplicity and the promise of guaranteed returns for each product sold, the flip side is that it doesn’t factor in the competitive landscape. The trick, therefore, lies in finding the balance between higher margin and sell-through rates, particularly given the aggressively competitive nature of online retail.

    3) Competitive pricing

    Today’s digitally savvy customers are forever comparing prices across several websites in the quest for the lowest prices. In fact, price is among the most critical factors that influences purchase decisions across products as well as categories. The competitive eCommerce pricing strategy, therefore, determines product price based on how the same products are priced by various competitors. While this model allows you to modify prices as frequently as necessary to drive efficient pricing and maximize revenue and margin, the complexity lies in ensuring consistent access to competitor prices, particularly in today’s highly dynamic e-commerce environment. DataWeave’s Pricing Intelligence platform helps eCommerce businesses overcome this challenge by helping them identify price improvement opportunities based on timely competitive intelligence at a massive scale.

    4) Dynamic pricing

    This model takes into account competitor prices, demand, and inventory levels, which are set up as triggers for automated pricing rules. While this results in sustained competitiveness, it requires a price optimization model that determines the optimal price in real-time response to fluctuations in demand and competitive prices – all the time ensuring alignment with your business goals. In other words, this model allows you to ensure consistently competitive yet optimized prices, thus acquiring and retaining a competitive edge in the market.

    5) Price perception management

    The company most famous for following this strategy is Amazon. The retail giant frequently identifies its most popular products and offers its largest discounts on them, often undercutting competitors. In other words, in this model, you “invest” in customer acquisition through excessively aggressive discounts on a select group of products – following which, you can cross-sell or up-sell other higher-priced products. Thus, you boost your perceived value to customers. Another way to drive a positive perception is to display discounted products at higher ranks on featured listings. For instance, in a recent study that we conducted, we found that 9 out of 10 leading US retailers’ top 50 ranked products (in each category) were significantly cheaper than the rest of their products.

    6) Bundle pricing

    The principle for this model is simple. You sell a number of the same products (or a range of complementary ones) for a combined, economical price. This is different from customers adding products individually to their cart as it works on the consumer psyche, which is more likely to favor a purchase that offers considerable perceived value. Thus, not only are you offering enhanced value to your customers (and in turn improving overall customer experience), you’re also actually increasing sales. Bundle pricing works best for products that are likely to involve repeat purchases (such as batteries, cereal boxes, or socks), and also for those that may need accessories (for instance, a food processor with various attachments). However, for bundle pricing to be effective, it’s also important to understand how your competitors are bundling their products.

    Granted, it isn’t easy to identify the perfect pricing strategy for you. As customers increasingly engage with you at every stage of their decision-making process and market dynamics become exceedingly complex, pricing as a function has to keep pace. As a retailer, your objective is to unearth the actionable insights hidden in your big data and leverage the resulting opportunities to drive the maximum possible revenue and margin – without getting lost in the flood.

  • Retailers Adopt Aggressive Private Label Pricing Strategies in CPG

    Retailers Adopt Aggressive Private Label Pricing Strategies in CPG

    Nine out of 10 leading retailers price their private label products lower than the average prices of their respective categories, reveals the latest DataWeave study, drafted in collaboration with SunTrust Robinson Humphrey The study reveals that an increasing number of retailers are viewing private label brands as a way to ensure sustained profitability.

    “As the CPG space reels under intense competition, a number of retailers are doubling down on private labels to capture valuable additional margin. For instance, Kroger, Walmart, and Amazon Fresh have a higher degree of private label penetration than the other retailers we analyzed,” said Karthik Bettadapura, Co-founder & CEO at DataWeave. “Our study unveils several such key insights covering product assortment & distribution patterns, price perception, and private label dynamics, revealing a clear snapshot of the disruptive transformations sweeping across the US CPG landscape.”

    Other key findings from the report, which tracked and analyzed 450,000 products across 10 leading retailers and 10 ZIP codes each, include the following:

    • Product assortment is emerging as a driver that’s as critical as pricing when it comes to customer retention. Target, H-E-B, and Kroger have a head start here, offering the largest product assortments among the retailers analyzed.
    • A sharp assortment strategy customized to local tastes and preferences is key to sustaining and enhancing customer satisfaction. Albertsons, Walmart, and Amazon Fresh lead here, revealing a higher focus on localized assortments.
    • “Home” and “Beauty & Personal Care” categories lead the distribution of private label products across retailers. The focus on these categories echoes a similar focus among national brands as well. These categories have the highest overall brand concentration, with around 4,000 brands each.

    To download the entire report, click here.

  • Thanksgiving Weekend Sale: How Top US Consumer Brands Fared

    Thanksgiving Weekend Sale: How Top US Consumer Brands Fared

    Online retailers in the US have enjoyed an impressive turnover during 2018’s Thanksgiving weekend sale. Over the last few weeks, DataWeave has published deep-dive reports on the performance of top US retailers in fashion and consumer electronics during this period, detailing their discounting and product strategies across several product types.

    In continuation of our series of articles on the Thanksgiving weekend sale, this article focuses specifically on the top brands across all retailers analyzed.

    Read Also:

    A Study of Fashion Retail Pricing Across Thanksgiving, Black Friday and Cyber Monday 2018

    How Consumer Electronics Was Priced Across Thanksgiving, Black Friday and Cyber Monday 2018

    While a lot of attention from the media and analysts during these sale events is often focused on the strategies and performance of retailers, the festive sale period is equally vital for consumer brands. Both established brands and new entrants across all categories compete aggressively to gain market share during a period that accounts for a substantial portion of annual sales turnover.

    For brands, the two primary drivers of conversion specific to sale events are competitive pricing and prominent brand visibility. At DataWeave, we went about analyzing which brands came out on top across retailers and categories during the Thanksgiving weekend sale, based on these two factors.

    Our Methodology

    We tracked the pricing of 6 leading fashion retailers and 5 major consumer electronics retailers to study the pricing strategies of brands during the sale events. Our analysis focused on additional discounts offered during the sale period to evaluate the true value of the sale event to customers. To calculate this effect, we compared the pricing of products on Thanksgiving Day, Black Friday and Cyber Monday to the pricing of products prior to the sale commencing. We considered the Top 500 ranked products on 11 product types across Men’s and Women’s Fashion and 11 popular consumer electronics products for this analysis.

    Consumer Electronics Brands

    In digital cameras, Canon’s traditional role as a discount leader was on show, featuring on both Best Buy (14%) and Target (20%), the two most aggressive price discounters in consumer electronics. Nikon took Canon’s place in DSLR cameras, for Best Buy (13%), New Egg (10%) and Walmart (4%), albeit at a comparatively low additional discount point.

    Razor benefited from Amazon’s strategy of promoting its lower-priced products, promoting a modest 9% additional discount but across its entire range of laptop products. The competitiveness of this category between brands is shown by Samsung’s decision to give an additional 53% discount across 36% of its product line at Best Buy.

    The strategic approach brands take with different retailers was illustrated by HP’s 30% additional discount on 31% of its products at Target while over at Walmart, HP had a dire a 4% additional discount on a mere 13% of its products. A similar strategy was employed by LG with its televisions. On Amazon, its TVs had a 10% additional discount applied to 46% of its products, while at New Egg that translated to 25% and 8% respectively.

    Among the fast emerging wearables category, under-pressure Chinese firm Huawei dropped an aggressive 46% additional discount on 100% of its product range at Best Buy. By comparison, the next highest in this category was Marc Jacobs at Target with 33% and 40% respectively.

    Most Visible Brands Across Product Types

    In our analysis, brand visibility is represented in terms of both the number of products for each brand, as well as the average rank of all its products (“lower” the rank value, higher is the visibility).

    The influence an online retailer exerted on a brand’s average ranking is illustrated by Canon’s digital cameras. On Amazon, its 296 products had an average ranking of 272, while on Best Buy it was 30 and 48, 73 and 212 on New Egg and 20 and 69 on Walmart. For all these retailers, Canon was the most visible brand in digital cameras, despite such variation.

    It was a similar story on laptops, with HP’s Amazon ranking of 298 based on 166 products, contrasting with a Target ranking of 14 on 18 products and Walmart ranking of 21 on 20 products.

    These patterns appear to play out in TVs too, with Samsung’s Amazon average ranking of 292 based on 150 products contrasting with Walmart average ranking of 10 across 7 products.

    Unsurprisingly, across our analysis of additional discounts and brand visibility, the top brands are well known and recognizable brands in each product type, with very few new entrants breaking out from the pack. This story, though, takes a turn in the following analysis on visibility growth.

    Brands With Highest Growth in Visibility

    To perform this analysis, we developed an index for the visibility of a brand based on the number of products available per brand as well as the average rank of those products. We then compared this score for each brand between before and during the sale period, and subsequently calculated the percentage growth.

    The list of brands that showed the highest growth in visibility for each product type is an interesting mix of well established and newer brands. The usual suspects included the likes of Philips, Fitbit, Sony, Kodak, Nikon, etc. The presence of brands like Apple, Google, and Bose is surprising as they would be expected to command strong visibility even before the sale. Some of the newer brands include Rha, Westinghouse, Garmin, Lanruo, and more.

    Some brands showed a dramatic increase in visibility. Examples include Bose on Walmart (698%), HTC on New Egg (657%), Galanz on Amazon (657%), and Jlab on Target (608%).

    Kodak’s digital cameras (2% growth) on Best Buy took the honors for the lowest increase in visibility, just ahead of HP laptops (3%) on Walmart, Nostalgia Electrics refrigerators (4%) and Belkin Tablets (7%) both on sale at Target. These numbers indicate a relatively static assortment for the respective retailers and product types.

    Fashion Brands

    Moving over to the Fashion category, we observed significantly more aggressive discounting activity, as expected. Parent’s Choice T-shirts recorded the highest additional discount (80%) applied to the widest product range (Walmart 91%). Similarly, Fruit of the Loom saw Amazon promote a 78% additional discount applied across 20% of its products.

    In shoes, Macy’s promoted a 60% additional discount on 50% of Kenneth Cole’s product range. In watches, Amazon featured a 57% additional discount on 50% of Kate Spade New Year branded products. Meanwhile, in sunglasses, Ray Ban in Bloomingdale’s enjoyed a 20% additional discount spread across a whopping 95% of its products, compared to just a 14% additional discount applied to a mere 10% of Ray Ban products in New Egg.

    In stark contrast to what was observed in Electronics, the Fashion category saw fewer large brands dominate the discounting landscape across categories. This isn’t surprising given how the Fashion category tends to be cluttered with a plethora of brands, while the Electronics category usually consists of a leaner set of popular brands in each product type.

    Most Visible Brands Across Product Types

    In casual shoes, Nike’s ranking of 264 on 93 and Converse’s ranking of 239 on 89 products contrasted with Vision Street Wear’s ranking of 8 on 9 products and Time And Tru’s 15 ranking on 14 products.

    Another point of contrast was Micheal Kors (Handbags) cross-retailer platform performance - its average ranking of 184 on 102 products on Macy’s while its average ranking on New Egg was 20 across 12 products. Still, it appears the brand discounted heavily in New Egg to compensate for its relatively low visibility on the website.

    Ray Ban recorded a category high ranking of 209 based on 321 products on Macy’s. By comparison, Ray Ban had a ranking of 17 on 34 products at New Egg. Over at Amazon, Ray Ban managed a creditable 189 ranking on 124 products and a 163 ranking on 120 products at Bloomingdale’s.

    Brands With Highest Growth in Visibility

    Compared to the Electronics category, Fashion consists of certain brands that skyrocketed in their visibility. Examples include Next Level T-shirts (Amazon 2,000%), Michael Kors Watches (Walmart 1,424%), Dakota Watches (Target 751%) and Adidas sports shoes (Amazon 516%).

    Bloomingdale’s delivered amazing visibility growth for key brands, with Burberry (527%), Reiss (500%), The Kooples (%00%), Tory Burch (500%), J Brand (475%), and Adidas (300%) all enjoying strong visibility growth.

    At the other end of the visibility growth spectrum, the growth rates of Lucky shirts (New Egg, 11%), Micheal Kors (New Egg, 20%) Dickies jeans (Target, 22%), Tasso Elba shirts (Macy’s, 23%), and Puma Casual Shoes (Target, 25%) indicate a relatively more static assortment in their respective product types.

    Depth Of Product Range And Discounting Strategy Matters

    Across the three sales, DataWeave identified several different additional discounting and product assortment strategies by both the retailers and the brands.

    While retailers are increasingly discounting the lower priced products to shape price perceptions among shoppers (take a bow Amazon), what are the implications for brands? Firstly, a thin product range is going to make achieving visibility more challenging. Secondly, brand strategies across online retailing platforms will need to be more clearly defined and executed. Thirdly, those brands that treated Thanksgiving, Black Friday and Cyber Monday as discrete events are going to have to rethink their approach as these lines increasingly blur with time.

    If you’re interested to learn more about how DataWeave aggregates and analyzes data from online sources as massive scale, as well as how we provide competitive intelligence to retailers and consumer brands, visit our website!

  • Consumer Electronics Prices During the Holidays

    Consumer Electronics Prices During the Holidays

    Consumer electronics has always been one of the most popular product categories for consumers during the Thanksgiving weekend sale each year.

    Shoppers often hold off on making expensive purchases in electronics in anticipation of great discounts during these sale events. While Cyber Monday is traditionally the key day for offers in electronics, recent trends, triggered by the growth of eCommerce, lean toward offering attractive prices across the entire sale weekend.

    Studies indicate that in 2018, the average value of an online transaction hit $97. This compares with $91 in 2017 and $87 in 2016, continuing the trend of a steadily increasing transaction value over the past two years. This year, the scene was set for a massive Cyber Monday as Black Friday purchases of electronics reached $6.22 billion, up 23.6 percent from last year according to Adobe Analytics.

    At DataWeave, we recently analyzed and published a blog post on the Thanksgiving weekend sale for the Fashion vertical.

    (Read here: A Study of Fashion Retail Pricing Across Thanksgiving, Black Friday and Cyber Monday 2018)

    As part of the same project, we scrutinized the consumer electronics vertical just as keenly across top electronics retailers in the US by monitoring prices across the weekend.

    Our Methodology

    We tracked the pricing of the 5 leading retailers selling consumer electronics to assess their pricing and product strategies during the sale events. Our analysis focused on additional discounts offered during the sale to evaluate the true value the sale event represented to customers. To calculate this effect, we compared the pricing of products on Thanksgiving Day, Black Friday and Cyber Monday to the pricing of products prior to the sale commencing. We considered the Top 500 ranked products on 11 popular product types in carrying out this analysis.

    Key Findings

    In contrast to the Fashion category, the consistency in the discounting strategy for all retailers across the three sale days in the Consumer Electronics category was striking. The only exception was Walmart, which opted somewhat curiously to roll back its discounts on Cyber Monday. All other retailers held similar additional discounts levels on a fairly similar set of products through the sale weekend.

    Target and Best Buy led the electronics discount charge at 22% and 21% for 18% and 17% of their assortment, respectively.

    While Amazon discounted the highest number of products at 29% of its range, it continued its recent strategy of not discounting steeply. In fact, Amazon was among the lowest in terms of additional discounts. The other end of the spectrum, Walmart provided a 28% additional discount on the first two sale days, offered only on a modest range of products (4% and 1%).

    Headphones and USB Drives proved popular lead product types for discounting by all retailers. Other product types making the cut included Refrigerators (Target), Laptops (Walmart), and Wearable Technology (Newegg).

    Amazon’s discounting strategy appears to be informed significantly by product visibility. The highest ranked products were far more aggressively discounted, and the discounts reduced progressively as we move to less visible products. This supports previous evidence illuminating Amazon’s strategy to develop a low price perception. We saw a similar trend emerging from Best Buy and Newegg as well.

    This discounting approach is in stark contrast to the behavior we witnessed in our earlier analysis of the Fashion category, where we found little correlation between visibility and discounts. However, given the higher price points and greater price elasticity in the Electronics category, we were not surprised to see this level of strategic clarity. Interestingly, our analysis of Target’s discounting behavior showed an opposite trend as Target opted to load up discounts on its less visible products.

    Walmart was excluded from this part of our study due to the very low number of common products before and during the sale that we could analyze.

    Another stable trend which emerged during our analysis of the sale weekend is the consistency with which lower priced products are offered at higher additional discounts relative to the more premium, higher priced products in the retailers’ product type. This trend largely held across retailers. Customer perceptions of low prices can be built by heavily discounting products at the lower end of the premium spectrum, while retailers can harvest their critical margin on their higher value goods.

    Diving Deeper Into Amazon

    Amazon announced a few days ago that it had its biggest shopping day in the company’s history on Cyber Monday. In its announcement, the company also stated the five shopping days starting with Thanksgiving and continuing through to Cyber Monday shattered records as US consumers bought millions of more products over the five-day sales compared with the same sales period last year.

    When the product popularity was evaluated and compared with additional discounts, we see higher discounts for better-reviewed products on Thanksgiving and Black Friday. Cyber Monday was an exception where discounts were distributed more smoothly across the three popularity bands.

    As with what we witnessed in the Fashion category, we detected higher additional discounts in Amazon’s Electronics private label brands (17%) relative to the average discount for other brands (7%).

    Profitability is back in the spotlight

    Electronics continued to be a key focus eCommerce retailers during their pivotal sales events in 2018. We are seeing signs of a shift to eCommerce and an accelerating emergence of a “Black November” and a “Cyber Post-Thanksgiving Weekend” impacting on sales results for the beginning of the holiday season.

    This year, there was a more concerted and strategic approach by retailers to maximize margin in the high-value end of the Electronics Category while still discounting the more popular and lower priced products. As expected, both Target and Best Buy featured prominently with their heavy discounting, while both Amazon and Newegg appeared to be executing a more nuanced discounting strategy. This rather reserved approach to the sale and careful focus on profitability is backed up by recent reports of Amazon’s shift in approach to housing low margin products.

    As was the case with the Fashion category, we saw the importance of Cyber Monday for Electronics sales being eroded and spread across the entire weekend, on the backdrop of a larger trend of attractive offers encompassing much of November and December.

    If you would like to know more about how DataWeave aggregates data from online sources to deliver actionable insights to retailers and consumer brands, check out our website!

  • A Study of Fashion Retail Pricing Across Thanksgiving, Black Friday and Cyber Monday 2018

    A Study of Fashion Retail Pricing Across Thanksgiving, Black Friday and Cyber Monday 2018

    The biggest holiday sale event of the western retail calendar — the Thanksgiving weekend sale, which includes Thanksgiving Day, Black Friday, and Cyber Monday — came and went a few weeks ago and made a huge splash along the way. While the sale event, especially Black Friday, is traditionally an offline sale event, modern online retailers too step up to offer products at attractive prices through this period.

    Online retail sales numbers grew at an impressive clip based on stats reported by Adobe Analytics. Thanksgiving Day sale itself generated $3.7 billion in sales, up 28 percent from a year ago. Black Friday delivered a record $6.22 billion in online sales — a substantial leap of 23.6 percent year on year. Cyber Monday sales online generated a new record of $7.9 billion, up nearly 18 percent from last year.

    Spending on fashion specifically was up 5.4 percent over the 2018 Black Friday weekend, the best growth seen since 2011, according to consulting firm Customer Growth Partners. Apparel retailers now book nearly a quarter of their annual sales during these holiday sales — a measure of just how important these annual sales have become to the online retailer’s commercial performance.

    As a provider of Competitive Intelligence as a Service to retailers and consumer brands, DataWeave consistently monitors and captures pricing and assortment information from leading retailer websites during sale events to study their product and pricing strategies — and we’ve done the same for this year’s Thanksgiving weekend sale as well.

    Our Methodology

    We tracked the pricing of 6 leading fashion retailers to study their pricing and product strategies during the sale events. Our analysis focused on additional discounts offered during the sale to evaluate the true value of the sale event to customers. To calculate this effect, we compared the pricing of products on Thanksgiving Day, Black Friday and Cyber Monday to the pricing of products prior to the sale commencing. We considered the Top 500 ranked products on 15 product types across Men’s and Women’s Fashion for this analysis.

    Key Findings in Men’s Fashion

    Macy’s and Bloomingdale’s featured prominently among the top discounting retailers. This is unsurprising, given their focus on Fashion. Macy’s, in particular, additionally discounted just over half its fashion assortment over the three days. This was an order of magnitude greater than its nearest competitor Amazon at 29 percent.

    Target and Walmart too discounted aggressively on Thanksgiving and Black Friday. Target exceeded Macy’s by 2 percentage points. However, Target and Walmart rolled back their discounts on Cyber Monday effectively halving them.

    Walmart’s discount strategy displayed significant variation across the 3 days of sale. On Black Friday, Walmart led the retailing pack with its 46 percent discount only to roll back to 15% on Cyber Monday. The fluctuations in these discounts reflect significant variation and churn in Walmart’s Top 500 ranked products across the three days of sales.

    As we have seen in previous sales, Amazon was a model of consistency in its discount strategy across the three days, maintaining a healthy 15% — 16% on roughly a third of its assortment. Strikingly, Newegg elected not to compete too aggressively in Fashion this year, adopting high single digit discounts on a similar percentage of its products.

    Across all six retailers, Shirts, Jeans, and T-shirts proved to be the most popular product types in terms of additional discounts although accessories such as sunglasses (Newegg) and watches (Macy’s) broke up apparel’s dominance.

    Did additional discounts vary by price range?

    We also studied the variation of discounts across ranges of product “premiumness”. We generated a percentile scale based on price ranges of products from before the sale, and studied the additional discounts offered for products in these price range buckets during the sale. A percentile score or 1 is the cheapest product and 100 is the most expensive product. All of these metrics were calculated first at a product type level and then aggregated at an overall level for each retailer.

    Amazon and Target display a clear strategy to additionally discount their more affordable range of products – those in the 1–20 cluster.

    Bloomingdale’s showed a less structured strategic approach. Its additional discounts were largely spread evenly across levels. Its product churn among the Top 500 items during the sale focused on its more expensive products as indicated by its score of 0 for the 81–100 percentile bracket.

    Macy’s opted to discount even more evenly across the board than Bloomingdale’s. It’s likely Macy’s relied on a different lever to drive discounts strategically. Walmart’s pricing approach was markedly uneven and all over the board from a strategic perspective.

    Key Findings in Women’s Fashion

    One of the most interesting patterns to emerge from these sale events was the marked difference in discounting strategy adopted for Women’s Fashion compared to Men’s Fashion. Both Amazon and Macy’s discounted their Women’s Fashion line up far less aggressively than their Men’s Fashion products. Their discounts also applied to a smaller set of products.

    Bloomingdale’s Women’s Fashion discounting was similarly marginally less aggressive than its approach to its Men’s Fashion. Only Target’s pricing remained consistent across its Men’s and Women’s Fashion products. However, Newegg’s strategy of not engaging too aggressively in Men’s Fashion this year carried over to its treatment of Women’s Fashion.

    The top product types additionally discounted were also not unexpectedly different between the Men’s and Women’s Fashion products. Skirts, Shoes, and Tops emerged as the favorite product types to discount, although no two retailers had the same discounting emphasis.

    As with Women’s Fashion, Amazon and Target discounted their less expensive products more consistently. However, in Women’s Fashion, they were joined by Walmart and to a lesser degree, Newegg.

    This showed evidence of a strategy to retail the less expensive products at more attractive price points to generate the price perception of being low-priced. Meanwhile, they continued to harvest comparatively more margin through their more expensive products. This was a more nuanced approach to margin management than what we saw in Men’s Fashion.

    Does product visibility correlate with discounts?

    One working hypothesis is that products discounted heavily tend to have higher visibility to drive the perception of lower price. However, the results of our analysis appear counter-intuitive.

    Amazon’s additional discounts in Men’s Fashion appear relatively uniform across all product cohorts. In fact, Amazon’s peaked additional discounts with the 200–400 cohort.

    Similar trends surfaced with other retailers. Newegg additionally discounted its longer tail products, while Walmart additionally discounted its Top 50 products at only 16% compared to an average of around 23% for other cohorts in its Top 500.

    A closer look at Amazon.com

    (Read Also: Amazon’s US Fashion and Apparel Product Assortment Evolves)

    We extracted data on Amazon’s reviews and ratings to investigate its discounting strategy across ranges of product popularity — a measure that’s defined using a combination of average review rating and number of reviews. We compiled a measure of all products that were rated as High, Medium, and Low cohorts and evaluated Amazon’s discounting strategy in each cohort.

    In Men’s Fashion, Amazon aggressively discounted its Medium and Low rated products on Thanksgiving, only to switch its strategy the next day on Black Friday. This tactical switch was presumably intended to showcase Amazon’s well-reviewed products at attractive prices on Black Friday — a larger sale event.

    By Cyber Monday, Amazon’s Medium reviewed products were back enjoying more aggressive discount levels, albeit the discount variance across all three cohorts was minor.

    Amazon’s discounting strategy for its Men’s Fashion products was in stark contrast to its strategy in Women’s Fashion. Here, Amazon additionally discounted its High and Medium reviewed products on Thanksgiving. While there was no specific discernible pattern on Black Friday, Amazon’s discounting was most consistent across its three popularity cohorts on Cyber Monday.

    We also looked at Amazon’s discounting activity across its private label products relative to other brands. Unsurprisingly, Amazon discounted its private label fashion products at an aggressive 30%, while the other brands benefited from, on average across all days and all categories, an additional 15% discount.

    Online drives shifting tides in holiday sale events

    While traditionally the holiday shopping season sees a peak around Black Friday and Christmas, retailers are increasingly seeing the demand spread across the entirety of the sale season of November and December. As a result, retailers need to stay on their toes to drive increased sales and gain market share over an extended period of time.

    Certainly, in 2018, we witnessed a more focused approach to mine margins in Women’s Fashion while still discounting aggressively. As expected, both Macy’s and Bloomingdale’s featured prominently in the discounting stakes while both Amazon and Target appeared to implement a more nuanced approach to juggling a reputation for low prices and driving increased margin.

    If you’re curious about how DataWeave aggregates data from eCommerce data at massive to deliver actionable insights to retailers and consumer brands, check us out on our website!

  • Decoding Alibaba’s Singles Day Sales

    Decoding Alibaba’s Singles Day Sales

    An average of $11.7 million per second was the rate at which Alibaba clocked $1 billion in sales during the first 85 seconds of Singles’ Day. As Alibaba’s annual sale event continues to grow in scale, referring to it as a global retail phenomenon is an understatement. Alibaba closed the day having shipped 1.04 billion express packages based on sales of merchandize worth 213.5 billion yuan ($30.67 billion).

    This performance shredded any lingering concerns analysts may have harbored about the prospects of this year’s sale, given the international backdrop of the ongoing trade skirmish between the US and China.

    Along with attractive discounts across a range of product categories, Singles’ Day also promised an integrated experience fusing entertainment, digital and shopping, in stark contrast to other large global sale events like Black Friday, which focus predominantly on discounts.

    At DataWeave, we set out to investigate if all the hype resulted in actual price benefits to the shoppers and how the various categories and brands performed in terms of sales during the event. To do this, we leveraged our proprietary data aggregation and analysis platform to capture a range of diverse data points on Tmall Global, covering unit sales (reported by the website) and pricing associated with Tmall Global’s major categories over the Singles’ Day period.

    Our Methodology

    We captured 5 separate snapshots of data from Tmall.com during the period between October 25 and November 14, encompassing over 15,000 unique products each time, across 15 product categories.

    To calculate the average discount rate, we considered the percentage difference between the maximum retail price and the available price of each product. We also looked at the additional discount rate, for which we compared the available price during Singles’ Day to the available price from before the sale. This metric reflects the truest value to the shopper during Singles’ Day in terms of price.

    Our AI-powered technology platform is also capable of capturing prices embedded in an image. For example, the offer price of ¥4198 was extracted accurately from the accompanying image by our algorithms and attributed as the available price while ¥100 from the same image was ignored.

    This technology was employed across hundreds of products using DataWeave’s proprietary Computer Vision technology.

    Domestic Appliances and Digital/Computer Categories Powered Turnover

    The Domestic Appliances and Digital/Computer categories dominated the Singles Day Sale in terms of absolute sales turnover. This isn’t surprising, since the average order value for these categories are typically much higher compared to the other categories analyzed.

    What clearly stands out in the above infographic is that the two largest categories in terms of sales turnover had average additional discounts of only 2 per cent and 0 per cent — a rather surprising insight. In general, with the exceptions of Women’s skincare, Men’s skincare, and Women’s bags (11 per cent, 10 per cent, and 9 per cent respectively), all other categories saw low additional discounts during Singles’ Day.

    However, the absolute discounts across the board were consistently high, with only Luggage (6 per cent), Digital/Computer (9 per cent) and Women’s wear (12 per cent) staying significantly below the 20 per cent mark. In fact, eight categories enjoyed absolute discounts greater than 30 per cent.

    Among common categories between Men and Women, the Men clocked more sales in Men’s wear, shoes, and bags. Only skincare proved to be an exception, where Women’s skincare generated twice the turnover of their Men’s equivalent.

    The Infants category was another intriguing sector to emerge during the sale. Both Diapers (38 per cent) and Infant’s Formula (25 per cent) were substantially discounted, despite only receiving low additional discounts of 2 per cent and 0 per cent respectively – indicating aggressive pricing strategies in this category even during non-sale time periods.

    The biggest takeaway from our analysis is the lack of any correlation between sales turnover and additional discounts, or even the absolute discounts.

    International Brands Make Gains

    International brands continue to penetrate the Chinese market showing up amongst the Top 5 brands of 13 of the 16 categories on sale.

    In the Diaper category, Pampers delivered nearly twice the sales turnover of its next biggest competitor. As expected, Apple and Huawei battled it out for honors in the Digital/Computer category although Xiaomi enjoyed pleasing results, nearly matching Huawei’s sales to go with its sales leadership of the Domestic Appliances category. Local brands, though, swept the Domestic Appliances, Furniture and Women’s Wear categories.

    The challenge posed by Chinese brands was illustrated by Nike’s spot in the second place in the highly competitive Men’s Shoes category after Anta.

    International brands topped only five of the 16 categories and Top 3 positions in ten categories. Still, there’s a growing presence of international brands in China’s eCommerce.

    Gillette won handsomely over its competition in the Personal Care category while Skechers enjoyed a similar result in Women’s Shoes, racking up nearly twice the retail sales of its nearest competitor. Another category dominated by international brands was the Women’s Cosmetics category where international brands accounted for 4 of the Top 5 brands.

    Similarly, Samsonite’s acquisition of American Tourister gave it two top 5 brands in the Luggage category. Other global brands to make the cut during the Singles’ Day sale included L’Oréal, Canada’s Hershel, Playboy, South Korea’s Innisfree and Japan’s Uniqlo.

    It’s Not All About Price On Singles’ Day

    The dramatic rise in shopping during Singles’ Day is not driven solely by price reductions. Alibaba’s commitment to its “New Retail” strategic model has led the Chinese giant to channel its impressive resources to focus on bringing together the online elements of its business with the more traditional offline aspects of its retail distribution. This is combined with entertainment to create a larger story based around the shopper’s overall “experience” rather than just driving “attractive prices” as a short-term retail hook.

    Alibaba is betting big on erasing the line between online and offline and its futuristic vision of structuring retail around the way people actually want to shop. Based on the consistently impressive results of Singles’ Day year after year, “New Retail” has a promising future.

    If you wish to know more about how DataWeave aggregates data from online sources to provide actionable insights to retailers and consumer brands, check out our website!

  • Evolution of Amazon’s US Product Assortment

    Evolution of Amazon’s US Product Assortment

    As with many other product categories, Amazon has made a significant incursion in Apparel — a key battleground category in retail today. Recently, DataWeave once more collaborated with Coresight Research, a retail-focused research firm to publish an in-depth report revealing insights on Amazon’s approach to its US fashion offerings.

    Since our initial collaborative report in February this year, we have witnessed some seismic shifts in the category at both the brand and the product-type level.

    Research Methodology

    We aggregated our analytical data on more than 1 million women’s and men’s clothing products listed on Amazon.com in two stages:

    Firstly, we identified all brands included in the Top 500 featured product listings for each product subcategory in both the Women’s Clothing and Men’s Clothing sections featured on Amazon Fashion (e.g., the top 500 product listings for women’s tops and tees, the top 500 product listings for men’s activewear, etc.). We believe these Top 500 products reflect around 95 percent of all Amazon.com’s clothing sales. This represents 2,782 unique brands.

    We then aggregated the data on all product listings within the Women’s Clothing and Men’s Clothing sections for each of those 2,782 brands. This generated a total of 1.12 million individually listed products. This expansive list forms the basis for our highlights of the report.

    Third-Party Seller Listings Are Rising Sharply

    We identified a total of 1.12 million products across men’s and women’s clothing — a significant increase of 27.3 percent in the seven months between February and September 2018. The drivers of this sharp spike are third-party seller listings. In contrast, the report indicates only a 2.2 percent rise in first-party listings over the same period, compared to a 30.5 percent jump in third-party listings.

    In addition, Amazon has listed just 11.1 percent of all clothing products for sale, with third-party sellers offering the remaining 88.9 percent — an indication of the strength of Amazon’s open marketplace platform.

    A Major Brand Shift On Amazon Fashion Is Underway

    In just over six short months, major brand shifts on Amazon Fashion have taken place. The number of Nike listings has plummeted by 46 percent, driven by a slump in third-party listings following Amazon’s new partnership with Nike — a story recently covered by Quartz. Limited growth in Nike clothing first-party listings failed to compensate for this decline.

    Gildan’s spike in total product listings appears to be fueled by increased first-party listings off a low base. Calvin Klein’s 2017 agreement to supply Amazon with products appears to be driving the Calvin Klein brand’s double-digit uptick in first-party listings on Amazon Fashion.

    Aéropostale’s decline appears to be entirely driven by a drop in its third-party listings. The brand itself is not listed as a seller on Amazon.com.

    Amazon Is Rebalancing Its Apparel Portfolio and Switching Its Focus from Sportswear To Suits

    As its Fashion footprint rapidly matures, Amazon now appears to be rebalancing its portfolio with strong growth being shown in listings for formal categories such as suits and away from sportswear. We recorded a 98.6 percent increase in listings of women’s suits and blazers complemented by a 52.2 percent rise in men’s suit and sports coat listings between February and September 2018.

    Generic “Non-Brands” Are Surging On Top 25 Brands List

    Over the past six months, low-price generic brands have made major inroads into Amazon’s listings. Four unknown “brands” captured the top positions on the list of brands offered on Amazon Fashion. The WSPLYSPJY, Cruiize and Comfy brands appear to be shipped directly to customers from China.

    Source: Coresight/DataWeave (Amazon Fashion: Top 25 Brands’ Number of Listings, February 2018 vs. September 2018)

     

    Source: Coresight/DataWeave (Amazon Fashion: Top 25 Brands’ Number of Listings, February 2018 vs. September 2018)

    WSPLYSPJY alone accounts for fully 8.6 percent of Amazon men’s and women’s clothing listings. Cruiize accounts for a further 3.2 percent of listings while Comfy chips in another 3.1 percent.

    Amazon Appears To be Executing A Strategic Pivot

    Amazon’s fashion offering is fast maturing. We saw substantial growth in the number of listings for more formal categories. The realignment in third-party listings by Nike together with increased first-party listings for Calvin Klein and Gildan appear to be driven by alliances with Amazon.

    Simultaneously, ultralow-price generic clothing items delivered on order from China have inundated the “Most-Listed Products” rankings. Third parties now represent nearly 90 percent of Amazon Fashion’s offering.

    While Amazon Fashion shoppers enjoy a wider choice than they did even six months ago, we believe a stronger emphasis on first-party listings would grow the products eligible for Prime delivery. This tactic could strengthen Amazon Fashion’s long-term appeal as a shopping destination.

    If you’re interested in DataWeave’s technology, and how we aggregate data from online sources to provide unique and comprehensive insights on eCommerce products and pricing, check us out on our website!

  • Inside India’s eCommerce Battle: Attractive Offers Usher In The Festive Season

    Inside India’s eCommerce Battle: Attractive Offers Usher In The Festive Season

    It’s festival season in India again and shoppers took advantage of aggressive cutthroat competition between Indian online retailers to drive sales to unprecedented highs.

    All the major Indian eCommerce websites including, Amazon, Flipkart, Myntra, and Shopclues opted to go head to head by holding their first sale event this season over 4 to 5 days starting on the 10th of October. Still, as industry reports indicate, one retailer came out on top during this event — an insight supported by our analysis as well.

    A New Battleground

    The highlight this year was seeing how the announcement of global retail colossus Walmart’s acquisition of Flipkart would impact the sale events. The acquisition was the most influential development in India’s eCommerce sector, and it has transported a decades-long U.S. rivalry between Amazon and Walmart to Indian soil. As a result, this year’s sale event held out the promise of more attractive pricing and vast product selection for India’s consumers than ever before.

    Industry analysts estimate that the sale generated a cumulative Rs 15,000 crore in sales over the spread of the five sale days, a whopping outcome. In 2018, this translated into around a 64 per cent year-on-year growth outcome compared to the USD 1.4 billion (around Rs 10,325 crore) generated by the 2017 sales.

    The DataWeave Analysis

    At DataWeave, we analyzed the performance of each of the major eCommerce platforms including Amazon, Flipkart, Myntra, Paytm, and Shopclues. For each eCommerce website, we aggregated data on the Top 500 ranked products for over 40 product types spread across 6 product categories (Electronics, Men’s & Women’s Fashion, Furniture, Haircare, Skincare).

    We focused our analysis on only the additional discounts offered during the sale and compared them to prices prior to the sale, to reflect the true value of the sale to India’s shoppers.

     

    The battle of the discounts was led primarily by Flipkart and Amazon. Flipkart’s average additional discounts by category actually exceeded Amazon’s in three out of six categories, and it discounted more products that Amazon across all categories.

    Clearly, the focus for all e-tailers was skewed towards the main battlegrounds of Electronics and Fashion, compared to mainstream FMCG categories such as Hair and Skin Care. However, this is not surprising given FMCG functions on rather skinny margins.

    Across retailers, the Men’s and Women’s Fashion categories were the most aggressively discounted, attracting both the highest additional discounts and the highest percentage of products with additional discounts.

    The Furniture category too was an interesting battleground between Amazon and Flipkart, attracting attractive discounts on a wide range of products, particularly in Flipkart’s case.

    Prospective shoppers in search of relatively more expensive clothing products on discount during the sale would have established Myntra as their ideal destination, as it carried more premium products on discount during the sale, relative to all its competitors. For shoppers in search of an electronics bargain though, they would have done well to opt for Flipkart.

    Shoppers may have found some interesting deals on Paytm Mall too, especially in Men’s Fashion, while Shopclues largely held itself back from any dramatic price reductions.

    While Myntra capitalized on its niche though aggressive discounting in the Fashion category, most of the discounting action revolved unsurprisingly around Amazon and Flipkart. To drill down for a more complete understanding of just how the Amazon and Flipkart discounted their products, we conducted a more detailed follow-on analysis.

    We normalized additional discounts and popularity using a scale of 1 to 10 and plotted each product on a chart to analyze its distribution characteristics. Popularity was calculated as a combination of the average review rating and the number of reviews posted. Products with a popularity score of zero, as well as zero additional discounts were excluded from this analysis.

     

    The most obvious insight yield through this analysis is how Flipkart elected to distribute its additional discounts across a larger range of discount percentages. By contrast, Amazon went all in on the more limited range of products it decided to provide additional discounts on. This is a strategy we have seen Amazon adopt previously.

    One other intriguing insight is Flipkart’s decision to go for a much higher distribution of products falling below a popularity score of 0.5 compared to Amazon. Amazon’s strategy resulted in more of its discounted products having a higher popularity score, relative to Flipkart, albeit only by a comparatively minor amount. However, a shopper’s chances of buying a popular, positively reviewed product at a lower price were higher on Amazon than Flipkart during this sale.

    Achieving a Consistent Competitive Edge

    Flipkart claims to have recorded a 70 per cent plus share of entire Indian e-commerce market in the 4 day-BBD’18 sales. Flipkart further claimed to have cornered an 85 per cent share in the online Fashion category together with a 75 per cent share in the Electrical category’s large appliances during the sale. This includes a contribution by Flipkart’s subsidiary Myntra.

    As these numbers reflect, Amazon still has some way to go to entrench itself in the Fashion category of the Indian market. However, Amazon appears content to continue its surgical discounting philosophy.

    Overall, this year witnessed an impressive participation by Tier II and Tier III Indian city consumers — a sign of things to come in Indian online retail.

    With increasing competitive pressure, retailers simply cannot adopt discounting and product selection strategies in isolation and be successful. Having access to up to date insights on competitors’ products dynamically during the day is emerging as key to ensuring they’re able to sustain their lowest priced strategy for appropriate products. These insights are also proving critical in identifying gaps in their product assortment, which can hamper customer conversion and retention.

    During sale events, modern retailers need to rely on highly granular competitive insights on an hourly basis (or even more frequently) to inform their pricing and product strategies to ensure they consistently maintain a competitive edge for the consumer’s wallet. And while access to reliable competitive intelligence is critical, true value can only be derived when it gets integrated with a retailer’s core business and decision-making processes, such as assortment management, promotions planning, pricing strategies, etc.

    DataWeave’s Competitive Intelligence as a Service helps global retailers do just this by providing timely, accurate, and actionable competitive pricing and product insights, at massive scale. Check out our website to find out more!

  • Prime Day Sale: Unraveling the Highs and Lows of Amazon’s Flagship Event

    Prime Day Sale: Unraveling the Highs and Lows of Amazon’s Flagship Event

    Another year, another round of media frenzy, and another set of records broken.

    In only three years, Amazon’s Prime Day has evolved into one of the landmark sale events of the shopper’s calendar. Reports indicate that this year’s sale made a major splash, raking in over $4.2 billion in sales — a 33% increase compared to last year. Also, the retail behemoth shipped over 100 million products during the 36-hour sale. Amazon stated that they “welcomed more new Prime members on July 16 than on any other previous day in Prime history.”

    The much talked about website outage added some spice and drama to the proceedings during the first hour. However, this was fixed quickly.

    This year is also the first Prime Day with Whole Foods, Amazon’s most expensive acquisition, giving US shoppers unprecedented incentives to shop at the physical stores of the grocery retailer.

    However, Prime Day is not just about the US, but a truly global event. In India, as part of its promotions for Prime Day, Amazon leveraged VR to have people experience the products in their true form factor at select malls.

    At DataWeave, our proprietary data aggregation and analysis platform enabled us to keep an eye on the pricing and discounts of products during the sale. We tracked Amazon.com, Amazon.co.uk, and Amazon.in before (14th July) and during the sale (16th July) and monitored several product types in Electronics, Men’s Fashion, Women’s Fashion and Furniture categories. We captured information on the price, brand, rank on the category page, whether Prime was offered or not, etc. and analyzed the top 200 ranks in each product type listing page. To best indicate the additional value to shoppers during the sale, we focused our analysis only on additional discounts on products between the 14th and 16th of July.

    Scrutinizing the data yielded some rather interesting insights:

    Amazon UK was more aggressive with its discounts than the US and India across most categories, with Furniture being the only exception (highest discounts in the US).

    In the US, Women’s Fashion observed the steepest discounts (12%), though there were discounts available on a larger number of Men’s Fashion products (5% additional discount on 20% of products).

    While disparity between discounts on Prime products vs non-Prime was quite evident, it was surprisingly low for many categories. In fact, the Electronics category in the UK and the Furniture category in India witnessed sharper discounts for non-Prime products than Prime.

    Top categories by additional discount include Women’s Handbags, Sports Shoes, and Pendrives in the US, Sunglasses and Tablets in the UK, and Women’s Tops, Men’s Jeans, Women’s Sunglasses, and Refrigerators in India. Top brands include Nike, Amazon Essentials, Sandisk, and 1home in the US, Oakley, Toshiba, Belledorm, and rfiver in the UK, and Adidas, Sony, UCB, and Red Tape in India.

    As indicated in the following infographic, some of the most discoverable brands during the sale include Canon, Apple, Nike and Casio in the US, Sandisk, Amazon, Levi’s, and Ray Ban in the UK, and Nikon, UCB, Whirlpool, and HP in India. Discoverability here is measured as a combination of the number of the brand’s products in the top 100 ranks and the average rank of all products of the brand. Also in the infographic, is a set of products with high additional discounts during the sale.

     

    Amazon’s competitors though aren’t ones that simply roll with the punches.

    Flipkart, Amazon’s largest competitor in India (recently acquired by Walmart), announced its own Big Shopping Days sale between July 16 and July 19. On Prime Day, the company joined in with some attractive offers:

    • 8%, 10%, and 7% additional discounts on 11%, 29%, and 16% of Electronics, Men’s Fashion, and Women’s Fashion categories, respectively.
    • 35% off on Perfect Homes 3-seater Sofa
    • 27% additional discount on Acer Predator Helios Gaming Laptop
    • 25% additional discount on Sandisk 16GB Pen Drive

    Propelling the Amazon Flywheel

    While Amazon clearly benefits in the short-term with this sale, the long-term effect of feeding its famous flywheel is evident as well.

    Amazon’s flywheel is a framework through which the company looks to build a self-feeding platform that accelerates growth over time. Attractive discounts and a broad selection of products improves customer experience, which increases traffic to the website, which attracts more merchants on its platform, who in turn broaden the selection of available products.

    Sale events like Prime Day create the sort of hype needed to draw a lot of traffic to Amazon’s website, generating momentum that has a compounding effect on Amazon’s growth. Not surprisingly, more than half of the people surveyed in the US by Cowen last December said they lived in a household with at least one Prime subscription.

    As Amazon’s stock traded at an all time high following Prime Day, it’s only a matter of time before the company becomes the world’s first trillion dollar company.

    Check us out, if you’re interested in learning more about our technology and how we provide Competitive Intelligence as a Service to retailers and consumer brands.

  • How to Win the Coveted Amazon Buy Box | DataWeave

    How to Win the Coveted Amazon Buy Box | DataWeave

    Did you know that over 80% of purchases on Amazon.com is via the buy box?

    While Amazon is all the rage today, raking in 43% of all eCommerce dollars, thousands of merchants on the online marketplace look to seize every opportunity to attract shoppers and drive sales each day. And for these merchants, getting on the buy box is more than half the battle won.

    Recently, Forbes.com published our study of how online merchants can plot their strategy to win the buy box. In this article, we’ll explore some of the key takeaways from this study.

    What is the Amazon buy box?

    The buy box is the section on the right side of Amazon’s product page, where shoppers can add items for purchase to their cart. Since multiple merchants often offer the same product, they compete to win the buy box spot on the product page, which is where customers typically begin the purchasing process — a huge competitive advantage.

    How can merchants win the buy box spot?

    At DataWeave, we aggregate and analyze billions of data points from the Web to deliver Competitive Intelligence as a Service to retailers and consumer brands. Using our proprietary technology platform, we aggregated data for a large sample of products in the mobile phones, clothing, shoes and jewelry categories on Amazon and collected information on all merchants (over 700 in number) selling these product over a period of 10 days.

    We looked closely at several factors that could possibly impact the choice for the buy box:

    • Was Amazon a merchant or not?
    • The effective price (list price + shipping charges — offer/cashback amount) — after all, a common assumption is that the lowest priced merchant has the best chance of winning.
    • Were Prime benefits offered?
    • The quality of review ratings
    • The stock status
    • The number of products offered by a merchant

    We parsed through the data to unearth some interesting insights and found that some factors influenced the move to the buy box spot more than others.

    We see that when Amazon is a merchant, it’s twice as likely to win the buy box compared to other merchants. Further analysis revealed that for around 95% of instances where Amazon was a merchant but was NOT the in the buy box, Amazon was selling at a price 20% greater than the minimum price.

    When the effective price is the lowest, relative to other merchants, the chances of the merchant winning the buy box increased 2.5-fold. Essentially, for the set of merchants who were the lowest priced for each product, only 26% of them won the buy box.

    Merchants who provided Prime benefits to shoppers were 3.5 times more likely to win compared to other merchants. And lastly, if the percentage of positive reviews for a merchant are decreasing over time, the merchant is 5X less likely to win. All other factors analyzed failed to yield statistically significant results.

    Interestingly, no single factor played an overwhelming role in influencing the buy box criteria. So, with the help of statistical modelling, which considers and weighs all factors, we better understood the relationship between all factors, and traced a path for merchants to win the buy box.

    The Cheat Sheet

    While it isn’t quite possible to develop a fool proof framework, the following flowchart can act as a fairly useful guide.

     

    Clearly, the path to the buy box is not a straightforward one.

    If Amazon itself is a merchant for a product, chances of other merchants winning the buy box are low (35%). However, if a merchant is looking to compete with Amazon for the buy box spot, offering Prime benefits is key (82% probability). Without offering Prime, chances of winning the buy box are almost negligible, even if the merchant is the lowest priced. It’s interesting to note that when Amazon does occupy the buy box spot, it’s the lowest priced in 79% of the cases.

    When Amazon is not a merchant for a product, and competition is only between third-party merchants, offering Prime benefits is still the most influential factor (78%). When Prime isn’t offered, the price is the primary determinant of the buy box merchant (86%).

    Evidently, reducing the price is not always the best course of action. It appears that offering Prime benefits has the biggest impact on a merchant’s chances of winning the buy box, across various scenarios.

    However, it’s important to keep in mind that moving up the “merchant ladder” is a gradual process, based on how merchants perform consistently over time.

    If you’re interested to learn more about DataWeave’s technology, and how we help retailers and consumer brands optimize their online strategies, visit our website!

  • Clearance Sale Analysis: Retailing Woes Stagger H&M and Toys “R” Us

    Clearance Sale Analysis: Retailing Woes Stagger H&M and Toys “R” Us

    Confidence amongst retailing analysts was rocked last month by two successive announcements.

    H&M’s most recent quarterly report, which revealed it had accumulated over $4.3 billion in unsold inventory, shocked retail analysts. In an era of on-the-fly inventory replenishment where stocks are closely matched to sales, a spike in unsold inventory is a strong indicator of trouble ahead. The news left analysts questioning H&M’s competitiveness in the fiercely contested global apparel category, where ever-changing consumer preferences demand agility in managing inventory levels.

    In the other major announcement, Toys “R” Us officially closed its doors to shoppers. The retailer’s losses continued to pile up and the chain groaned under a mountain of debt, leaving it little choice but to close down. “The stark reality is that the (chain is) projected to run out of cash in the U.S. in May,” it said in its bankruptcy filing.

    While the emergence of the online shopping phenomenon hasn’t helped Toys “R” Us, its ongoing afflictions largely reflect strategic missteps that predated the online shopping boom. In a category where the shopping experience is all, the retailer failed to adapt to changing consumer expectations. The warehouse context which shaped the retailing did little to promote toys sales or communicate the sheer breadth of inventory carried by Toys “R” Us.

    So, as Toys “R” Us begins to wind down its operations, the company has shuttered its online store and is channeling customers to its remaining physical retail outlets. However, prior to the closure, shoppers enjoyed some amazing bargains during their clearance sale.

    H&M’s problems appear less terminal. Its management claim to have implemented a strategy to slash its accumulated inventory and reign in its aggressive store expansion strategy.

    At DataWeave, we leveraged our proprietary data aggregation and analysis platform to analyze the clearance sales of both H&M and Toys “R” Us. We tracked the pricing, product categories, discounts, review ratings, stock status and more between 29-Mar and 3-Apr.

    The Toys “R” Us Sale

     

    Although the dolls and stuffed animals category carried the most products, its average discount was along the mid-range point for the sale at 28 percent. Games & Puzzles and Action Figures and NERF were the most heavily discounted categories at 40 percent and 36 percent respectively.

    As anticipated, products with lower review ratings were sold at slightly higher discounts. However, even exclusive products were sold at comparatively high discounts. Not surprising, given this was effectively a clearance sale.

    Hasbro, Mattel, and Spin Master were the highest represented brands during the sale, while for their part, Kid’s Furniture and Outdoor Play had fewer products participating in the sale. Other popular brands such as Fisher-Price and LEGO had a presence during the sale but offered fewer products.

    Zuru was the most aggressive in offering discounts with Spin Master the least aggressive. The remaining brands offered discounts of between 30 and 36 percent.

    Reports suggest that last year, toymakers Mattel and Hasbro each sold around $1 billion worth of their toys at Walmart, more than the volume they achieved selling through Toys “R” Us. Strategically, these leading brands seem to have their bases covered even though Toys “R” Us is closing down.

    Interestingly, some products were seen to go out of stock during the sale week, only to be replenished a day later, as illustrated in the above infographic.

    The H&M Sale

    Overall, H&M’s clearance sale was more aggressive in Women’s Apparel with three times more products on offer than for Men’s Apparel. However, there wasn’t much difference between the two in terms of the discounts on offer which hovered around the 45 percent range. Women’s Tops, Cardigan’s and Sweaters offered discounts on the most products during the sale period.

    Little difference was observed tactically, between how the different product categories, were handled.

    We saw a significant movement of products in Women’s apparel during the week, with over 330 newly added products and close to 200 products that were effectively churned. This pattern indicates H&M achieved a faster shelf velocity for this category than for Men’s, possibly due to a more aggressive approach to the selection of items on sale.

    Customer focus is key

    Reports indicate that despite a series of widespread and aggressive markdowns as shown in the analysis above, H&M is struggling to sell off its mountain of accumulated merchandise. Changing consumer tastes and increasing competition seem to have taken their toll on the once agile Swedish retailer. If it is going to weather this storm, H&M needs to revisit its fast fashion approach to assortment and inventory management. The retailer would also appear to need to improve its demand forecasting expertise.

    The bankruptcy filing by Toys “R” Us presents yet another lesson for eCommerce and bricks-and-mortar retailers alike, to address evolving consumer expectations and focus closely on the customer experience aspect of their business, which are supported by appropriate pricing and product assortment strategies.

    At DataWeave, our technology platform enables retailers to do just that, through comprehensive and timely insights on competitive pricing, promotions, and product assortment. Check out our website to find out more!

     

  • Recognize Product Attributes with AI-Powered Image Analytics

    Recognize Product Attributes with AI-Powered Image Analytics

    Anna is a fashionista and a merchandise manager at a large fast-fashion retailer. As part of her job, she regularly browses through the Web for the most popular designs and trends in contemporary fashion, so she can augment her product assortment with fresh and fast-moving products.

    She spots a picture on social media of a fashion blogger sporting a mustard colored, full-sleeved, woolen coat, a yellow sweatshirt, purple polyester leggings, and a pair of pink sneakers with laces. She finds that the picture has garnered several thousand “likes” and several hundred “shares”. She also sees that a few other online fashion influencers have blogged about similar styles in coats and shoes being in vogue.

    Anna thinks it’s a good idea to house a selection of similar clothing and accessories for the next few weeks, before the trend dies down.

    But, she is in a bit of a pickle.

    Different brands represent their catalog differently. Some have only minimalistic text-based product categorization, while others are more detailed. The ones that are detailed don’t categorize products in a way that helps her narrow down her consideration set. Product images, too, lack standardization as each brand has its own visual merchandising norms and practices.

    Poring through thousands of products across hundreds of brands, looking for similar products is time-consuming and debilitating for Anna, restricting her ability to spend time on higher-value activities. Luckily, at DataWeave, we’ve come across several merchandise managers facing challenges like hers, and we can help.

    AI-powered product attribute tagging in fashion

    DataWeave’s AI-powered, purpose-built Fashion Tagger automatically assigns labels to attributes of fashion products at great granularity. For example, on processing the image of the blogger described earlier, our algorithm generated the following output.

    Original Image Source: Rockpaperdresses.dk

    Vision beyond the obvious

    Training machines is hard. While modern computers can “see” as well as any human, the difference lies in their lack of ability to perceive or interpret what they see.

    This can be compared to a philistine at a modern art gallery. While he or she could quite easily identify the colors and shapes in the paintings, additional instructions would be needed on how the painting can be interpreted, evaluated, and appreciated.

    While machines haven’t gotten that far yet, our image analytics platform is highly advanced, capable of identifying and interpreting complex patterns and attributes in images of clothing and fashion accessories. Our machines recognize various fashion attributes by processing both image- and associated text-based information available for a product.

    Here’s how it’s done:

    • With a single glance of its surroundings, the human eye can identify and localize each object within its field of view. We train our machines to mimic this capability using neural-network-based object detection and segmentation. As a result, our system is sensitive to varied backgrounds, human poses, skin exposure levels, and more, which are quite common for images in fashion retail.
    • The image is then converted to 0s and 1s, and fed into our home-brewed convolutional neural network trained on millions of images with several variations. These images were acquired from diverse sources on the Web, such as user-generated content (UGC), social media, fashion shows, and hundreds of eCommerce websites around the world.
    • If present, text-based information associated with images, like product title, metadata, and product descriptions are used to enhance the accuracy of the output and leverage non-visual cues for the product, like the type of fabric. Natural-language processing, normalization and several other text processing techniques are applied here. In these scenarios, the text and image pipelines are merged based on assigned weightages and priorities to generate the final list of product attributes.

    The Technology Pipeline

    Our Fashion Tagger can process most clothing types in fashion retail, including casual wear, sportswear, footwear, bags, sunglasses and other accessories. The complete catalog of clothing types we support is indicated in the image below.

    Product Types Processed and Classified by DataWeave

    One product, several solutions

    Across the globe, our customers in fast-fashion wield our technology every day to compare their product assortment against their competitors. Our SaaS-based portal provides highly granular product-attribute-wise comparisons and tracking of competitors’ products, enabling our customers to spot assortment gaps of in-demand and trending products, as well as to better capitalize on the strengths in their assortment.

     

    Some other popular use cases include:

    • Similar product recommendations: This intelligent product recommendation engine can help retailers identify and recommend to their shoppers, products with similar attributes to the one they’re looking at, which can potentially help drive higher sales. For example, they can recommend alternatives to out-of-stock products, so customers don’t bounce off their website easily.
    • Ensemble recommendations: Our proprietary machine-learning based algorithms analyze images on credible fashion blogs and websites to learn the trendiest combinations of products worn by online influencers, helping retailers recommend complementary products and drive more value. Combining this with insights on customer behavior can generate personalized ensemble recommendations. It’s almost like providing a personal stylist for shoppers!
    • Diverse styling options: The same outfit can often be worn in several different ways, and shoppers typically like to experiment with unconventional modes of styling. Our technology helps retailers create “lookbooks” that provide real world examples of multiple ways a particular piece of clothing can be worn, adding another layer to the customer’s shopping experience.
    • Search by image: Shoppers can search for products similar to ones worn by celebrities and other influencers through an option to “Search by Image”, which is possible due to our technology’s ability to automatically identify product attributes and find similar matches.
    • Fast-fashion trend analysis: Retailers can study emerging trends in fashion and host them in their product assortment before anyone else.

    The devil is in the details

    DataWeave’s Fashion Tagger guarantees very high levels of accuracy. Our unique human-in-the-loop approach combines the power of machine-learning-based algorithms with human intelligence to accurately differentiate between similar product attributes, such as between boat, scoop and round necks in T-shirts.

    This system is a closed feedback loop, in which a large amount of ground-truth (manually verified) data is generated by in-house teams, which power the algorithms. In this way, the machine-generated output gets more and more accurate with time, which goes a long way in our ability to swiftly deliver insights at massive scale.

    In summary, DataWeave’s Image Analytics platform is driven by: enormous amount of training data + algorithms + infrastructure + humans-in-loop.

    If you’re intrigued by DataWeave’s technology and wish to know more about how we help fashion retailers compete more effectively, check us out on our website!

     

  • Study of Brand Inconsistency in Furniture eCommerce

    Study of Brand Inconsistency in Furniture eCommerce

    From initially lagging well behind early high-penetration categories such as consumer electronics, books, and apparel, furniture is now emerging as a key growth category.

    Online furniture purchases are growing at a rapid clip, estimated to currently be around 14 percent rate annually and is anticipated to reach 7.6 percent of total category sales in 2018.

    Savvy furniture brands are becoming increasingly aware of this shift in consumer shopping patterns and are taking steps to embrace the importance of creating a seamless online customer experience consistent across all eCommerce websites.

    Selling furniture online remains logistically complex. It requires the disciplined coordination across an ecosystem teeming with bricks and mortar stores, salespeople, warehouses merchants, and a network of delivery systems.

    All this complexity poses challenges for brands looking to deliver a consistent brand experience for consumers across multiple eCommerce websites.

    One frequent outcome of this complex ecosystem is the emergence of white labeling.

    The Invasion of White Labeling in the Furniture Category

    A white label product is one that is manufactured by one company only to be bundled and sold by other online merchants using different brand names. The end product is positioned as having been manufactured by the brand marketer.

    These white label products are frequently sold at a significant discount, compared to more mainstream name brands in the category.

    Electronics brands have often been victims of this phenomenon. Typical electronic white label products now commonplace range from radios and DVD players to computer mice and keyboards, through to TV remote controls.

    Increasingly, the furniture vertical is no longer a stranger to white label packaging and marketing as well.

    At DataWeave, using our proprietary data aggregation and analysis platform, we analyzed a range of factors of the furniture vertical, specifically the emerging phenomenon of white labeling.

    Our analysis spanned a sample set of over 20,000 products that we tracked across the websites of two of our eCommerce customers (whom we don’t wish to name) that have a large assortment of furniture products. Let’s call these eCommerce companies Retailer A and Retailer B.

    We identified white labeled products as being those that featured the exact same image between the two retailers but were sold under different brand names. Here, our AI-powered advanced image analytics platform matched the images of various products at an accuracy of more than 95%.

    The following infographic summarizes our analysis.

    Clearly, not only is white labeling quite prevalent here, but in almost every instance, we identified price variation. Some of the white labeled products were sold by lesser-known brands with significantly lower price points. This pricing strategy could potentially damage the customer experience for well-established consumer brand franchises in several ways.

    The shopper sees through the branding exercise where the same product is repackaged and presented as having been “produced” by a different brand, potentially eroding brand loyalty.

    As some 71 percent of the products studied were identified as white labeled products, this exposes the category as a whole to this risk.

    The shopper may be confused by the price difference as well, undermining the brand’s carefully constructed pricing perception. The average spread of 21 percent between competing white labeled products is potentially a major source of consumer dissonance and confusion.

    A Closer Look at Pricing

    While the inconsistent experience potentially created by widespread white labeling is almost characteristic of the furniture vertical, other eCommerce areas such as pricing and promotion have also been demonstrated as being key influencers of the shopping experience.

    Today, brands have little control over how their products are priced on eCommerce websites and are susceptible to pricing decisions taken by either the merchant selling the product or retailers themselves. Here, price change decisions have little to do with providing a consistent brand experience, as it’s not really a priority for merchants and retailers.

    In a hyper-competitive retail environment, retailers often discount heavily or change prices frequently to drive sales and margins. The following infographic summarizes the differences in pricing approaches between the two retailers we analyzed.

    Both retailers demonstrated quite divergent approaches in their pricing strategies. The key point of difference appeared to be Retailer B’s discount execution, which proved more aggressive than Retailer A’s, routinely exceeding the latter by five percent or more.

    This discounting strategy is focused on the 40+ percentile (by price, with 100 percentile being the most expensive product), and above price bands, while both retailers displaying similar strategies to their Top 20 and Top 20 to 40 percentile ranges.

    We also observe how Retailer B is more inclined to offer higher discounts on products with higher review ratings, compared to Retailer B’s strategy — a play on developing a “low price” perception among shopper.

    The Consumer Experience Matters

    Today, consumers expect a truly seamless shopping experience right across a brand’s entire integrated retail community, regardless of whether it is physical or digital. Consumers have evolved beyond being merely time poor and have emerged as a group of impatient shoppers, unforgiving of inconsistencies in their experience.

    With retail evolving to embrace multiple consumer touch points with a brand, the practice of white labelling represents a dangerous source of potential confusion and disillusionment. This raises the degree of difficulty involved in converting website visitors into buyers. Further, inconsistent pricing between eCommerce websites, due to dissimilar pricing strategies adopted by each website, only compounds the problem for furniture brands.

    Technologies like DataWeave’s Competitive Intelligence as a Service, that can provide furniture brands with timely insights on white labelled products, unauthorized merchants, and price disparity between ecommerce websites, can assist furniture brands in their efforts to better manage their online channel.

    Visit our website to find out more on how we help consumer brands protect their brand equity and optimize the experience delivered to their customers on eCommerce websites!

     

  • Amazon’s Fashion & Apparel Product Assortment | DataWeave

    Amazon’s Fashion & Apparel Product Assortment | DataWeave

    Apparel remains one of the key battleground categories in retail today, and like in most other product categories, Amazon has made significant in-roads here. Beyond expanding the range of product offerings and brands in its marketplace, Amazon has also launched several private label brands in this vertical and looked to drive more sales as a first-party seller.

    Recently, DataWeave collaborated with Coresight Research, formerly known as Fung Global Retail & Technology, a retail-focused research arm of Li & Fung Group, to publish an in-depth report revealing Amazon’s strategic approach to product assortment in its fashion and apparel category.

    In this blog post, we’ll summarize some interesting insights into Amazon’s strategy from the report. For an in-depth and detailed view, check out the original article at — “Amazon Apparel: Who Is Selling What? An Exclusive Analysis of Nearly 1 Million Clothing Listings on Amazon Fashion”

    Research Methodology

    Our analysis focused on several critical areas, including the presence of Amazon’s private label, the demarcation between Amazon as a seller and its third-party sellers and the top brands and categories in women and men’s apparel.

    We aggregated data from Amazon.com in two stages:

    Firstly, we identified brands with a meaningful presence in Amazon’s clothing offering by identifying all brands included in the top 500 ranks of featured product listings for each product type in the Women’s Clothing and Men’s Clothing sections on Amazon (e.g., the Top 500 product listings for women’s tops and tees, the Top 500 product listings for men’s activewear, and so on.). This generated a total of 2,798 unique brands.

    Secondly, we aggregated our data on all product listings within the Women’s Clothing and Men’s Clothing sections for each of the 2,798 brands identified previously. This returned a total of 881,269 individually listed products. This extensive list forms the basis for the highlights in Coresight’s report.

    Coresight’s Analysis — Some Interesting Insights

    Strategically, Amazon remains heavily reliant on its third-party sellers in the clothing category. In total, just 13.7 percent of women’s and men’s clothing products featured on Amazon Fashion are listed for sale by Amazon itself (first-party sales), while third-party sellers account for 86.3 percent of listings.

    In womenswear, third-party sellers account for 85.7 percent of listings, while in menswear, they account for 87.1 percent of listings. Moreover, Amazon appears to be focusing its first-party clothing inventory on the higher-value categories. Clearly, the retailer’s reliance on third-party sellers underscores its opportunity to grow its sales of apparel volumes by bringing more of its current inventory in-house.

    The analysis found 834 Amazon private-label products on Amazon website, equivalent to 0.1 percent of all clothing available through Amazon Fashion. The company’s private labels appear to be clustered tightly in specific clothing categories.

    Womenswear brand Lark & Ro is by far the biggest of Amazon’s apparel private labels, as measured by the number of items.

    Nike is the most-listed brand on Amazon Fashion, with 16,764 listed products spanning womenswear and menswear. Lower-price brands such as Gildan and Hanes also rank very highly in terms of the number of products listed.

    Value-positioned brands that have traditionally focused on wholesaling to retailers, such as Gildan and Hanes, also rank very highly in terms of the number of products listed.

    What is clear is that currently, Amazon’s clothing listings are highly diluted, with no one major brand dominating the listings.

    Interestingly, casualwear and activewear clearly lead Amazon’s category rankings. Women’s tops and tees are the most heavily listed clothing category on Amazon Fashion, with 138,001 products listed.

    Men’s shirts, which includes a large number of casual shirts together with polo shirts and some T-shirts, comes in second, with 109,043 products listed. Echoing the prominence of the global Nike and Adidas brands on the Amazon website, activewear has achieved a centre of gravity status as a category, accounting for 76,930 men’s activewear products and 51,992 women’s activewear products listed on the site.

    Several Opportunities for Growth

    Amazon Fashion remains heavily dependent on third-party sellers. It’s a fair assumption that more first-party listings would attract greater numbers of shoppers, especially Amazon Prime members. Amazon’s private-label ranges represent another potential lever for growth.

    Also, the 30 most-listed brands on Amazon Fashion comprise 30 percent of all clothing products listed on the website, while just 189 brands have more than 1,000 products each listed on the website.

    This data indicates the presence of major growth opportunities across the board, be it Amazon private label brands, Amazon as a seller, and for several mid-range clothing brands.

    If you’re interested in DataWeave’s technology, and how we aggregate data from the Web to provide unique and comprehensive insights on eCommerce products and pricing, check us out on our website!

  • Boxing Day Sale: How UK’s Top Retailers and Brands Fared

    Boxing Day Sale: How UK’s Top Retailers and Brands Fared

    Following a successful Black Friday in November, the United Kingdom geared up for the 2017 Christmas season in December. Analysts estimate the total splurge in December at about £45 billion, beating last December’s record of £43 billion.

    Online sales hit £1.03billion, passing the £1billion threshold for the first time and up 7.9 percent on 2016’s £954million, according to the Centre for Retail Research. The rise of online shopping together with the timing of Christmas in 2017 meant shopper footfall in physical stores was lower than in previous years as people increasingly moved to shopping online.

    Total shopper numbers were 4.5 percent down on the previous year, according to research group Springboard, which may reflect the growing strength and reliability of online’s product range and delivery responsiveness.

    Major online retailers though continued to pull out the big discount guns across categories in an effort to attract online shoppers on Boxing Day, the biggest sale event in December.

    At DataWeave, we focused our proprietary data aggregation and analysis platform to analyze the top 500 ranked products in over 20 product categories across electronics and fashion retailers in the UK. Our analysis included several top UK retailers, which include Amazon, Argos, Currys, Tesco, Asos, Marks & Spencer, and Topshop.

    The discounts in the infographic below indicate the magnitude of reduction in prices during the sale (26th Dec), compared to before the sale (19th Dec), in order to best represent the additional value derived from the sale for shoppers.

     

    Boxing Day Sale Highlights

    In electronics, while Amazon offered discounts on the most number of products, Argos was aggressive in the average size of its additional discounts.

    Surprisingly, Amazon appeared to be much more conservative in the Men’s Fashion category with an average additional discount of 13.8 percent, spanning 341 products. Here, Asos deployed the most aggressive combination of high average additional discounts (36.9 percent) on a large number of products (165).

    Marks & Spencer focused their targeted discounts (43.1 percent) on a tight set of Men’s Fashion products (45), while interestingly, the story almost reverses in Women’s Fashion, where both M&S (43.1 percent, 281 products) and Topshop (40.5 percent, 226 products) were aggressive in what turned out to be a critical battleground category.

    Leading brands weren’t left out of the discounting action either, with the largest discount on offer going to Ruche (48.9 percent on 33.3 percent) women’s tops, closely followed by M S Collection (41.9 percent on 32.3 percent) handbags and Asos’ (37.5 percent on 21.2 percent) men’s jeans.

    Most Discoverable Brands

    We also analysed the most discoverable brands in each product type. This was measured as a combination of the number of the brand’s products present in the Top 500 ranks of a product type, as well as the average rank (lower the number, higher is the discoverability).

    It was no surprise that Canon DSLR cameras were highly discoverable on Amazon with 90 products, along with an average ranking of 93.2, while 34 Asus laptops recorded an average ranking of 85.2. At Argos, 57 Acer laptops recorded an average ranking of 73.4 while 50 LG televisions delivered an average ranking of 124.1.

    Other highly discoverable brands included MS Collection in Marks & Spencer, Apple iPhones and Tablets on Curry’s and Tesco.

    The Online Retail March Continues

    If we look at sales results across the world, from the United Kingdom to the United States, to Asia in countries such as India, Singapore and Indonesia through to Australia, online retail is aggressively cannibalizing traditional bricks and mortar in-store retail sales. Online retail’s demonstrated superiority in exploiting competitive intelligence and a sophisticated suite of analytics that accompany digital transactions, is surfacing in its agile discounting strategies, and its ability to continuously refresh product lines during key sales periods.

    This Boxing Day in the UK, fashion proved to reveal divergent discounting strategies between retailers, while only marginal differences in approach were visible in electronics — both high volume categories around Christmas season.

    Overall, December 2017 in UK marked a strong validation of online retail’s influence and we can expect a continuation of it’s ability to harness discounting with extensive product offerings, in order to lure shoppers away from in-store.

    If you’re interested in DataWeave technology, and how we deliver Competitive Intelligence as a Service to retailers and consumer brands, check out our website!

     

  • Myntra Leads End of Year Promotions in Fashion

    Myntra Leads End of Year Promotions in Fashion

    Following three back-to-back mega-sale events leading up to Diwali, India’s eCommerce companies once again opened the discount floodgates heralding Christmas and New Year. This time around, Fashion was the battleground category of focus for Indian e-retailers.

    Myntra launched its End of Reason Sale held between 22nd and 25th December. eCommerce behemoth Amazon too announced its own grand Amazon Fashion Wardrobe Refresh Sale on the same days, while Flipkart hit the market with its End of Year Bonanza held on the 24th and 25th of December. Paytm and Snapdeal held sale events as well, starting 23rd December. All competing sale events promised consumers up to 80 percent discounts across a range of products, especially in Fashion.

    At DataWeave, we analyzed and reported on the competing pricing strategies of Amazon, Flipkart, Myntra, Paytm, and Snapdeal. In the following infographic, we look specifically only at additional discounts offered on the top 500 ranked products of over 15 product types during the sale, compared to those before the sale events went live.

    Myntra Gets Aggressive

    Myntra elected to discount over 84 percent of its Top 500 ranked Fashion products encompassing each product category, with an average additional discount percentage of over 25 percent offered during the sale.

    A prime example of this discounting approach was the sports shoe segment, which received an aggressive additional discount of 28 percent on over 93 percent of the Top 500 ranked sports shoes. Similarly, Myntra’s additional discounts ranged from between 22 percent and 25 percent across most product types, including T-shirts, Shirts, Handbags, Jeans, Skirts, Sunglasses, and Watches. The fashion e-retailer’s private label brands enjoyed attractive reductions in prices, which include Hrx and Roadster, along with other brands like Red Tape, Nike, and Puma.

    Amazon Discounts To A Different Beat

    Amazon discounted 35 percent of its Top 500 ranked Fashion products in each product type, with an average additional discount percentage of 12.5 percent during the sale. Given Amazon’s track record of dynamic pricing, this was relatively conservative.

    Overall, additional discounts on Amazon ranged between 4 percent and 16 percent across all product types in Fashion. Top brands discounted on Amazon included Adidas, Fastrack, Hush Puppies and Ray-Ban.

    Flipkart Joins The Party

    Flipkart too joined the End of Year discount action with several attractively positioned offers, exceeding those featured on Amazon. Flipkart discounted over 65 percent of its Top 500 ranked Fashion products in each product type, with an average additional discount percentage of over 14 percent during the sale.

    Additional discounts promoted on Flipkart ranged between 8 percent and 22 percent across all Fashion product types, while some of the top discounting brands included Dkny, Metronaut and United Colors of Benetton.

    Conspicuously, other Indian e-retailers like Paytm and Snapdeal chose not to join in the price war. Snapdeal, especially, has consistently offered only moderate additional discounts during recent sale events, choosing to focus more on other areas of improving the user experience for their shoppers.

    Strategic Focus On Profitability

    In contrast to the profit-sapping Diwali sale season, characterized by steep discounts across all product categories, this end of year sale was more concentrated, largely honing in on Fashion. From a strategic and shareholder perspective, limiting the discounting action to Fashion insulated the retailers’ bottom line from another major profit hit.

    Myntra determinedly reaffirmed its leadership status in the Fashion category, with its highly aggressive discounting strategy. This was well received by shoppers, who spent a staggering ₹5 crore in only the first five minutes of the sale.

    Flipkart opted to double down this time around with attractive offers on its own eCommerce platform as well. The e-retailer, currently locked in a battle with Amazon for leadership in India’s eCommerce sector, had acquired Myntra in 2014 in a bid to strengthen its position in the fashion category.

    Amazon, intriguingly, opted for a more conservative approach to its end of year sale than we are used to witnessing from the eCommerce giant. As we enter the new year, and kickstart yet another cycle of aggressive e-retail promotions in India, there will be ample opportunities to see if this is evidence of a rethink in Amazon’s approach to pricing in India.

    If you’d like to know more about DataWeave’s technology, and how we provide Competitive Intelligence as a Service to retailers and consumer brands, check out our website!