Tag: Argos

Black Friday 2025 UK: In-Depth Analysis of Discount Strategies and Brand Performance Across Major Categories
Black Friday 2025 saw British shoppers spend an average of £430 each this year representing a £91 increase from last year and totaling over £10.2 billion across the sales period.

The 2025 sales event arrived at a pivotal moment for UK retail. Retail sales fell 1.1% in October 2025 as consumers held back spending in anticipation of Black Friday promotions, according to the Office for National Statistics. Over 2 in 5 UK adults participated in Black Friday shopping, with 45% planning to pick up Christmas gifts at a discount, according to a Barclays study.

Against this backdrop of cautious optimism and strategic consumer behavior, how did retailers and brands perform across key categories this Black Friday? At DataWeave, we conducted a comprehensive analysis of Black Friday 2025 discounting trends across five major categories in the UK market: Consumer Electronics, Home & Furniture, Health & Beauty, Grocery, and Apparel. Our AI-powered pricing intelligence platform monitored over 71K SKUs across leading UK retailers like Costco, Selfridges, Boots, Debenham’s, Carethy, Argos, John Lewis, Amazon, and more, revealing fascinating patterns in how retailers and brands approached this year’s sale season.

Our Methodology

For this analysis, DataWeave monitored average discounts across leading UK retailers during two distinct periods:
- Pre-Black Friday: November 6 – November 23, 2025 – capturing early holiday deals and baseline pricing
- Additional Discounts During Black Friday Week: November 24 – December 1, 2025 – covering Thanksgiving week through Black Friday (November 28) and Cyber Monday (December 1)
Our sample encompassed the top-ranked products across subcategories on major retail sites. We also analyzed Share of Search data, which measures brand visibility by monitoring which brand names appear in the top 20 search results for critical keywords.

Black Friday 2025 UK: The Big Picture

Our analysis covered 71,642 SKUs across five major categories. Here’s the snapshot of average discounts during the Pre-Black Friday period compared to Black Friday Week:

Key Insight: Pre-Black Friday discounts were substantial across all categories. This suggests UK retailers front-loaded their promotions to capture early holiday shoppers, with additional discounts during Black Friday Week adding to the baseline discounts already in place. The extended promotional period transformed Black Friday from a single-day event into a month-long campaign, with 60% of UK shoppers beginning their deal searches as early as October.

Consumer Electronics

Consumer electronics remains a cornerstone of Black Friday shopping in the UK, with technology accounting for 48% of planned consumer spending during the sales period, according to PwC.

AI is transforming how consumers shop for electronics, with AI-driven traffic to retail sites expected to rise 410% year-on-year during the 2025 holiday season. Younger shoppers particularly embraced AI tools, with 17% of Gen Z consumers using AI platforms like Chat GPT and Gemini to source and compare deals. Our analysis of 10,297 SKUs reveals how discounts varied across subcategories and which brands dominated search visibility.

Subcategory Discount Analysis

Pre-Black Friday discounts averaged 11.1% across subcategories, while Black Friday Week saw an additional 2.3% discount on average. Audio & Video products led the pre-sale discounting at 16.3%, indicating retailers were eager to move inventory early in the season.

During Black Friday Week, Home Automation saw the highest additional discount at 2.8%. Wearables and Computers both saw solid 2.5% additional discounts, making them attractive categories during the peak shopping period.

Share of Search: Brand Visibility Trends

Our Share of Search analysis reveals significant shifts in brand visibility during Black Friday Week:

Bose dominated with its Share of Search more than doubling from 11.3% to 23.8%, a remarkable +12.5% gain. Lighting brand Philips Hue followed, gaining by +5.4% in share of search during Black Friday week. Notably, Meta, with it’s range of wearables, stands out for a +3.1% increase in visibility.

Apple’s Share of Search jumped from 10.1% to 16.4%, a gain of 6.4%. At the same time, Fitbit’s share dropped nearly 11%, the steepest decline in the entire electronics category. Meanwhile, Samsung and HP also lost on visibility this Black Friday in the UK.

Home & Furniture

The Home & Furniture category continues to attract UK consumers during Black Friday, though with a more measured discounting approach compared to other categories. Our analysis of 16,487 SKUs shows how discounts were distributed across subcategories.

Subcategory Discount Analysis

Home & Furniture saw Pre-Black Friday discounts averaging 9.1%, with Black Friday Week adding just 1% on average, the lowest additional discount among all categories. Furniture led pre-sale discounts at 13.7%, followed by Bedding at 11.9%. This suggests retailers aggressively promoted larger home goods early in the season to capture deal-seekers.

During Black Friday Week, Kitchenware saw the highest additional discount at 1.9%, making it attractive for holiday cooking and gifting needs. Conversely, Lighting saw minimal additional promotion at just 0.5%.

Share of Search: Brand Visibility Trends

Made.com, the contemporary furniture brand, saw visibility surge during Black Friday with an impressive 8.9% increase. Similarly, emerging mattress brand Vesgantti gained 5.4%. Rug specialist Gooch Oriental also made significant gains with a 4.9% increase.

On the flip side, British heritage brands faced challenges. Both Laura Ashley and Julian Bowen saw share of search drop 2.2%. Premium mattress maker Vispring also declined 2.1%, while French cookware brand Le Creuset fell 1.9%.

Health & Beauty

Health & Beauty has emerged as a growth engine during Black Friday in the UK. The beauty industry is projected to grow 5% annually through 2030 according to a McKinsey survey. The category continues to demonstrate resilience even as consumers show caution in other discretionary categories. Our analysis of 15,816 SKUs reveals fascinating subcategory-level insights and dramatic brand visibility shifts that highlight evolving consumer preferences in the beauty space.

Subcategory Discount Analysis

Health & Beauty presented a unique discounting pattern compared to other categories. Pre-Black Friday discounts averaged 14.4%, the second-highest among all categories. But Black Friday Week discounts were also robust at 6.1%, the highest additional discount increase.

Hair Care led both periods with 16.4% pre-sale discounts and an additional 6.4% during Black Friday Week. Skincare saw the highest Black Friday Week discount at 6.9%, suggesting retailers strategically saved their best skincare promotions for the main event when consumers are actively seeking holiday gift sets. Men’s Grooming stood apart with strong pre-sale discounts of 12.5% but more modest Black Friday Week additions of just 2.3%.

Share of Search: Brand Visibility Trends

The UK Beauty category saw some of the most dramatic Share of Search swings in our analysis.

Himalaya, the Ayurvedic skincare brand, dominated the category with a stunning 16.8% gain. British cult favorite Dr. Pawpaw exploded from 3.7% to 11.8%, a gain that reflects the brand’s growing mainstream appeal. Face the Future, the skincare specialist, also gained significant ground with a 4.9% increase.

Budget-friendly British brand Q+A continued its momentum, rising 4%, while prestige names like Guerlain and Tous each gained 3.8%.

Italian natural beauty brand L’Erbolario saw the steepest decline, with visibility dropping by 9%. Haircare brand Noughty fell 6.1%, and eco-beauty brand So Eco declined by 5.1%.

Grocery

While Grocery typically sees more modest discounts compared to discretionary categories, the sector remains a critical part of Black Friday shopping in the UK, particularly as consumers prepare for holiday entertaining and gifting. Our analysis of 11,979 SKUs shows how UK retailers approached promotions across essential and indulgent subcategories.

Subcategory Discount Analysis

Grocery had the lowest discounts across all categories, reflecting the already-thin margins in food retail. Pre-Black Friday discounts averaged just 5.7%, with Black Friday Week adding only 1.2%. Pet Products led pre-sale discounts at an impressive 13%, significantly outpacing other grocery subcategories.

Beverages and Household Essentials followed with 9.4% and 7.7% pre-sale discounts respectively, and maintained their lead during Black Friday Week with 1.7% and 1.5% additional discounts each. Fresh categories like Meat & Seafood (1.4% pre-sale, 0.6% Black Friday Week) and Frozen Foods (1.7% pre sale, 0.6% additional discounts during Black Friday week) saw minimal promotional activity, consistent with perishable inventory constraints and tight margins.

Share of Search: Brand Visibility Trends

Doritos led with a 7.3% surge in visibility. Pepsi delivered an equally impressive performance, rising from 3.6% pre Black Friday to 10.7% during Black Friday week. Fanta too saw 5.2% gain in share of search.

Conversely, Coca-Cola gained more modestly at 1.6%, while its Sprite brand actually declined 0.9%.

Apparel

Apparel remains a Black Friday staple in the UK and is projected to deliver the strongest year-on-year growth of any UK retail segment this festive season. With clothing accounting for 39% of planned Black Friday purchases, the category represents one of the most hotly contested battlegrounds during the sales period.

Our analysis of 17,063 SKUs, the largest category in our study, reveals interesting patterns across fashion segments that demonstrate both the opportunities and competitive intensity in UK apparel retail.

Subcategory Discount Analysis

Apparel showed the strongest discounting activity throughout the BFCM period among all categories. Pre-Black Friday discounts averaged 17.2%, with Black Friday Week adding 3.5%, making it one of the most heavily promoted categories.

Activewear led pre-sale discounts at an impressive 26.7%, with an additional 4.5% discount during Black Friday week. Plus Size Clothing and Men’s Clothing tied for second place in pre-sale discounts at 21.9% each. Notably, Plus Size Clothing saw the highest Black Friday Week discount at 5.4%.

Women’s Clothing saw robust discounts throughout, with 20.8% pre-sale and an additional 6% during Black Friday Week (the highest additional discount in the category).

Share of Search: Brand Visibility Trends

White Stuff, the British lifestyle brand, saw a 7.2% surge in visibility during Black Friday. Y2K fashion made a statement as Juicy Couture jumped 5.8 %. Fast fashion player Pretty Little Thing gained in visibility by 5.2%. Comfort brands performed strongly, with Skechers gaining 4.5% and activewear specialist Sweaty Betty rising 3.4%. Even premium denim brand Levi’s gained ground, increasing share of search by 2.2%.

However, retail giants faced significant visibility challenges. John Lewis saw the steepest decline in the Apparel category, with share of search dropping by 10.6% during Black Friday week. Fast fashion giant Boohoo declined 2.5%. Premium accessory brand Coach’s share fell 4.9%.

The data suggests UK consumers gravitated toward distinctive brands with clear identities during Black Friday, whether heritage British labels, Y2K nostalgia, or comfort-focused specialists, rather than generalist retailers or fast fashion platforms.

Want to understand how DataWeave’s pricing intelligence platform can help your business make data-driven decisions during peak sales events? Contact us to learn more about competitive insights, price intelligence, assortment analytics, content analytics, and digital shelf analytics.

Check out our analysis on Black Friday 2025 Pricing and Discount trends in the USA.

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December 16, 2025
Structured and Unstructured data – Benefits of Big Data

The big buzzword of the decade has got to be data. When the untapped potentials of great data were first discovered, experts started calling it the new oil, implying that it is now the most precious resource. And then when the usage of data became more mainstream, where corporations started mining and getting access to piles of data, people started calling it the new soil, insinuating that if all this data isn’t regularly nurtured and optimally used, it would be rendered useless.

But amidst all this hype, all the clutter, and all the buzz around this four-letter word, data is just a bunch of numbers and statistics collected for reference and analysis. Basically, it is just what you, your company, your government, or your country make of it. So how can retailers make the most of it?

Before assessing the use cases, it is paramount to understand the different types of data retailers have access to today. Broadly, it is structured and unstructured. Log files, excel spreadsheets with point-of-sale figures, hierarchies, and inventory data are rich sources of structured data; and information that is derived from in-store sensors, customer reviews, social media posts and hashtags, and even conversations between the store staff and customers serve as unstructured data. While the former sits on well-organized databases for retailers to access, giving them operational robustness, unstructured data gathered from social media and personal interactions helps retailers achieve unprecedented value and gain a competitive advantage. However, the very nature of unstructured data makes the process of obtaining, analyzing and making sense of it rather difficult.

Structuring vs Unstructured

In fact, according to a survey by Deloitte, only 18% of organizations reported being able to take advantage of such data. However, harnessing this data isn’t rocket science (not anymore, at least) as there are a number of tools at a retailer’s disposal today that makes this process convenient and efficient. At DataWeave, we help retailers and brands make sense of unstructured data. Read more about our tech here.

Unstructured data is also qualitative, rather than being quantitative, which in turn makes its use cases more effective, giving businesses a competitive edge. How? Glad you asked!

Customer Behaviour Analytics

What motivates a customer to buy more, or spend more time in a store or online? What is the best time to reach them and where (in an omnichannel world) would they like to be reached? Million-dollar questions, right? Big data gives you insights into this and more, which will then help improve customer acquisition and loyalty.

UK-based home retailer Argos uses data to find out exactly how consumers felt about them. After having embarked on an ambitious project of opening 53 new digital stores a few years back, Argos invested in tools that helped them analyze data received from various social media sites based on the demographics and location to assess the performance of each store and identify rooms for improvement. This helped them understand which stores were perceived more favorably and in which areas, quickly identify issues in-store, action feedback, and find resolutions to increase customer satisfaction.

Want to know customer sentiment against your product? Our Sentiment Analysis solution can help! Access in-depth insights sourced from customer opinions with our constantly evolving algorithm.

DataWeave Sentiment Analysis

Personalization and hyper-personalization

The fact that customers are interacting with retailers on multiple platforms today gives retailers access to a wealth of information about their individual customers that could help them tailor their products, offerings, services and communication to these individuals. According to a study conducted by BCG and commissioned by Google, customers increasingly prefer a shopping experience that’s easy and fast and that helps them make purchase decisions.

Target’s popular pregnancy prediction score based on purchase and purchase volume of about 25 different products in-store, such as unscented lotion, large amounts of calcium, magnesium, and zinc, serves as a great example of how they use this information to then target advertising (e.g sending a booklet of coupons related for baby products) to this cohort of their customers. This algorithm got the international limelight when Target started sending such coupons to the irate father of a teenager who had no idea that his daughter was pregnant. Basically, the retailer knew about the man’s daughter’s pregnancy even before he did!

Operations and supply chain

Amazon Go

A healthy mix of structured and unstructured data is key today in achieving operational excellence. Faster product life cycles and ever-complex operations cause organizations to use big data in retail analytics to understand supply chains and product distribution to reduce costs. Combining that with CRM, ERPs, and other log file data can help in real-time delivery management, improved order picking, and overall supply chain efficiency to reduce costs.

Amazon Go, the checkout-free convenience store by Amazon uses AI-powered cameras, computer vision, and sensors to facilitate grab-and-go systems. Now, the store wholly relies on structured and unstructured data in order to function. The sophisticated automated system makes ordering and restocking highly efficient, given that the cameras can track inventory in real-time. The system knows how many picks-per-hour each stocker is completing and exactly when items go out of stock.

The fact that data enables prediction and forecasts can help cater to a prospective rise in demand by managing the supply chain in advance. For example, if a pharmaceutical company analyzed social media content and determined that people in specific geographical areas were discussing cold and flu symptoms, that could give them a heads-up that demand for products to treat those conditions is on the rise.

Price and cost optimization

Machine learning algorithms are not only designed to learn, but over time they get better at finding the optimal price points for retailers. Retailers can use machine learning models to set prices against sales targets. According to an IBM study, 73 percent of companies surveyed plan to optimize their pricing and promotions through smart automation before the end of 2021.

Automation achievers outshine peers in profitability and revenue growth

Walmart has shrewdly utilized powerful proprietary algorithms to make their offers nearly impossible to beat over the last few years. It still reigns in offering the best price match policy for their customers. This strategy has helped it gain a lot of trust, good publicity, and enabled retention of customers. But how do you optimize what you charge without pricing yourself out? That is where data comes into play. You need real-time monitoring across thousands of stock-keeping units (SKUs) to identify key value categories and items. With proper data analytics in your pocket, you can ask and answer the following important questions: Which items’ prices matter most? Which items have the biggest pull on price perception? What pricing strategies are competitors adopting, and how can you match them? And which items can you afford to reduce in price to win loyalty and boost that very perception?

Learn more about how DataWeave can help retailers make smarter pricing decisions.

Seamless shopping journey

Every company uses data to achieve its own personal goals and objectives, but what makes one retailer better than the other is how they use both structured and unstructured data to provide a seamless experience and shopping journey to customers in a way that is effortless, non-intrusive, and innovative. So use your structured data and also find a way, use the tools, and leverage the power of technology to structure your unstructured big data. In today’s competitive retail landscape where retailers – both online and offline – are leveraging cutting edge technologies to deliver close-to-perfect products and services, and innovative concepts, it is only the ability to harness all forms of structured and unstructured data that will result in achieving your ever-evolving customer engagement and experience goals.

Want to learn how DataWeave can help make sense of your unstructured data? Sign up for a demo with our team to know more.

September 17, 2021