Black Friday 2.0: Why Retailers Are Betting on Data Over Discounts

Black Friday 2.0: Why Retailers Are Betting on Data Over Discounts

Real-time data streaming—not margin-eroding price cuts—is now the key to Black Friday online success.

When Black Friday first took off as a retailing event, it was almost entirely focused on headline-grabbing sales and doorbuster deals. Price—above all other commercial considerations—was the primary battleground between retailers as they discounted heavily to get customers through their doors.

Fast forward to today and the Black Friday free-for-all has evolved from a single day of discounted shopping to a broader, more complex retail event.

Thanks to the advent of comparison tools, apps and year-round comparison and monitoring, price no longer commands the dominance it once had. Instead, it’s been replaced by data-driven marketing, which has allowed retailers to create tailored experiences built around hyper-personalised services and seamless omnichannel experiences.

It means retailers are increasingly focused on creating one-of-a-kind customer service—everything from bespoke adverts to tailored product recommendations—to get the payment machines pinging.

But this can only be achieved if they can gather, process and utilise quality customer data at speed. In other words, real-time data streaming—not margin-eroding price cuts—is now the key to online success.

For those at the forefront of this retailing revolution, nothing highlights the role of data streaming better than hyper-personalisation, which takes customer data such as browsing patterns, past purchases, and personal interests to deliver highly targeted promotions.

Growing Demand for Hyper-Personalised Offers

Retailers like Amazon, Walmart and fashion brand ASOS are often cited as leaders in bespoke digital retail. They use real-time streaming to generate flash sales or limited-time offers which would lose their impact if not sent at the right moment. And they’re not alone.

“Our customers are happiest when we respond instantly to their individual needs,” said Jon Vines, Engineering Lead at AO.com, one of the UK’s largest electrical retailers, which has seen customer conversion rates jump by up to 30% thanks to hyper-personalisation.

“With data streaming, we can create a single view of each customer, giving them what they want right in the moment, including product suggestions and relevant promotions to help guide their shopping decisions. That hyper-personalisation is a huge differentiator for us and goes right to the heart of AO’s mission.”

What makes this approach so compelling is that while retailers are pressing ahead with greater personalisation, consumers are actively demanding it. Consumers expect a more tailored service online. And they’ll vote with their digital wallets if they don’t get what they want.

AI has become a Hard-Working Sales Assistant 

This includes AI-driven product recommendations that analyse customer behaviour around the clock to offer recommendations shaped by recent browsing or purchases. Someone looking to buy a specific pair of gym shoes, for example, may be offered other brands to consider. Or—based on their search history—they may be tempted with a too-good-to-miss offer on sports clothing. Or protein shakes and energy bars. Or even gym equipment or membership.

These cross-selling opportunities could all be done at the point of sale. However, hyper-personalisation means that well-timed push notifications — such as flash sale reminders or price-drop alerts — can also be triggered at other times to increase the number of consumer touch points.

Fed a constant stream of customer data, AI-powered virtual shopping assistants can offer help and advice to turn online window shoppers into confirmed sales. But hyper-personalisation isn’t solely about online shopping.

Harking back to the time when price was used to tempt people into stores, data is now being used as part of an orchestrated omnichannel experience with customers targeted with time-limited offers and discounts that can only be redeemed in store.

Take Toolstation, for example. It’s an omnichannel retailer of building tools and materials with more than 500 branches in the UK plus more than 100 in the Netherlands, Belgium, and France.

“Everything we do as an organisation is done from either the CX point of view — to improve the customer experience — or for profit,” said Stuart McGrogan, Toolstation’s Head of Architecture. “Our mantra across the business is to prioritise things that will generate revenue.”

And once purchases have been made — whether online or in-store — personalised thank you messages, tailored loyalty offers, or relevant newsletters are used to help brands cement their relationship with customers.

While many of these techniques are becoming increasingly common throughout the year, they peak in the weeks on either side of Black Friday.

Using Data Freely is Key

What underpins them all are AI-enabled, real-time data streaming platforms, which, when done well, are completely invisible to consumers.

“We don’t want our customers to notice our technology,” said Michael Huber, Architect, Cloud Service Platform, BestSecret, a leading European online destination for off-price fashion. “We want them to experience a high-quality, stable and intuitive customer journey on our website and apps.”

And that’s the key. Real-time data streaming allows retailers to process and analyse customer behaviours instantly—tracking everything from clicks, wish lists, and search history to in-store footfall.

It allows brands to operate 24/7—not just selling but marketing, advertising and promoting their goods by recommending the right product, offering exclusive discounts, or ensuring customer service is available when a shopper is hesitating before a purchase. It’s all part of the increasingly sophisticated and complex world of retail. And it all comes to a head on Black Friday.