This article is provided by BRC Associate Member, Valcon.
__________________________
Retail has never been more complex. Few industries have experienced a more dramatic transformation in the last ten to fifteen years. The death of the high street, the meteoric rise of online retail, increasing regulation and the rapid pace of technological change have made staying competitive harder than ever for retailers. Add on volatile supply chains, inflation and understandably price sensitive consumers, and the challenges rise exponentially. And in recent weeks, retailers have been facing a fresh wave of pressure, with M&S, Co-op and Harrods all battling high profile cyber-attacks.
This is a harsh reminder of how vulnerable and fast moving the retail landscape can be. In this environment, every commercial lever matters – and pricing is one of the most powerful.
Traditional pricing tools are no longer fit for purpose
While many retailers have embraced digital transformation, pricing strategies are often outdated – lots of retailers are still relying on traditional pricing models that can’t keep up. Manual processes, static spreadsheets, siloed data and slow decision-making mean prices often lag behind the market and don’t reflect what’s happening in real time, or what customers are willing to pay.
This delay can be costly. Misaligned prices erode margins, damage customer trust and risk compliance issues. In some cases, they can even undermine brand positioning or wider commercial objectives. Retailers need a pricing approach that’s dynamic, data-driven and capable of responding to constant change.
That’s why, according to Gartner, 91% of retail IT leaders plan to prioritise AI by 2026. Smarter pricing decisions, powered by AI, are already helping retailers improve margins, build loyalty and stay ahead of fast-moving market conditions.
What smarter pricing actually looks like
AI can help retailers to transition from reactive pricing to something far more predictive, responsive and customer centric. Effective AI powered pricing strategies are built on three pillars:
• Strategic factors
These set the direction and intent of your pricing strategy – from identifying key value items (KVIs) that shape customer perception, to creating localised price zones and ensuring consistency across channels.
• Hygienic factors
These help maintain logical, trustworthy price relationships. That might mean setting consistent gaps between private label and national brands or using rounding rules that feel familiar to the customer.
• Dynamic factors
This is where AI shines. By analysing live competitor pricing, demand trends and external signals like fuel costs or weather, pricing engines can adjust prices in real time, across categories or channels.
A great example of this shift is John Lewis, which has modernised its ‘never knowingly undersold’ price promise using real time data and AI driven tools. While the pledge itself is familiar, it’s now supported by dynamic pricing engines that scan competitors’ pricing models and analyse market signals and economic factors to make live adjustments across all its channels. Since the relaunch, John Lewis has reported a six-point rise in its Net Promoter Score, as highlighted by Marketing Week, evidence that the strategy is improving customer satisfaction and reinforcing trust. It’s a clear example of how AI can help to blend commercial agility with brand heritage.
Why AI pricing succeeds and where it can go wrong
AI can unlock major gains in pricing performance, but it’s not a plug and play solution. Success depends on more than just the technology. It needs the right ecosystem around it. The first thing to address is people - retailers need dedicated pricing teams that understand both commercial context and data science. These teams can translate AI outputs into action and work closely with merchandising, supply chain and marketing. The second building block is processes - agile workflows allow retailers to trial AI recommendations and scale what works. Fast, flexible decision-making is key to keeping up with market shifts. And the third is technology - a centralised data platform brings together inputs from ERP, CRM, e-commerce and external sources, which can enable near real-time updates, pricing automation and full visibility across the business.
Without this foundation in place, even the most sophisticated algorithm will struggle to deliver real-world results.
Getting started with AI powered pricing
Whether you're fine-tuning price zones or overhauling your entire model, the first step is clarity. What’s your ambition? What’s achievable now? And do you have the in-house capability, or do you need an expert partner to help?
One thing is certain: pricing complexity isn’t going away. AI-powered pricing is no longer a future ambition, it’s the new baseline. The retailers that act now will be the ones who are best placed to protect margins, build trust and respond quickly to whatever the market throws at them next.
