If there is one part of digital commerce that still refuses to fall neatly into place, it is pricing. For all the progress made across platforms, personalisation, and customer experience, pricing often remains slightly out of step, more reactive than strategic, and more constrained than it probably should be. As we move further into 2026, that gap is becoming harder to ignore.
In a recent episode of The FODcast, Meghan Stabler, Co-founder of alentr and former SVP of Global Marketing at BigCommerce, shared a perspective that will feel familiar to many retailers. Pricing is not broken, but it is lagging behind the rest of the ecosystem, and that is starting to have a real commercial impact.
Why pricing still lags behind
When you look across the digital commerce landscape, most areas have evolved quickly. Front-end experiences are more refined, personalisation is more accessible, and there is certainly no shortage of data. And yet, pricing is still often managed in ways that feel surprisingly manual. It is reviewed periodically rather than actively optimised, and in many cases it is shaped as much by internal limitations as it is by market conditions. That creates a disconnect. Particularly in a market where margins are under pressure and customers are more informed than ever, the ability to respond with precision, rather than broad adjustments, becomes incredibly important.
The reality retailers are navigating in 2026
The underlying challenges have not changed dramatically, but they have become more pronounced. There is a constant tension between staying competitive and protecting margin, and discounting remains an easy, if not always sustainable, lever to pull. At the same time, metrics like conversion rate do not always tell the full story.
A strong conversion rate can just as easily suggest that pricing is too low as it can that it is right. Layer on top of that the continued unpredictability in supply chains and cost bases, and it becomes clear why static pricing models are starting to feel increasingly fragile.
AI in retail pricing: promise and practicality
Unsurprisingly, much of the conversation has shifted towards AI in retail pricing, and with good reason. The potential is there to analyse vast amounts of data, respond to competitor movements, and adjust pricing in a way that simply has not been possible before. But in practice, things are a little more nuanced.
The challenge for many retailers is not access to AI tools, but the ability to embed them effectively into decision making. That requires clean data, clear ownership, and a commercial framework that defines how pricing should behave in different scenarios. AI can absolutely enhance pricing strategy, but it works best when it is supporting a well defined approach, not trying to replace one.
Towards a more considered pricing model
What is emerging is not a need for constant change, but for more controlled flexibility. The retailers making progress here tend to have a clear baseline built around their cost structure and margin expectations, combined with defined guardrails that prevent unnecessary erosion. From there, pricing can be adjusted more selectively, based on where it will genuinely make a difference. It is a subtle shift, but an important one. Moving away from reactive discounting towards more deliberate, informed decisions changes the role pricing plays within the business.
Why this matters now
For a long time, pricing has sat slightly outside of digital transformation conversations, often seen as something separate from the technology stack. That is changing. As platforms become more standardised and experience becomes more consistent across the market, pricing is one of the few remaining levers that can materially influence commercial performance. It is also one of the least mature areas in many organisations, which makes it both a challenge and an opportunity.
The talent behind the shift
One of the more interesting themes that continues to come through is the role of people in all of this. Technology is advancing quickly, but the capability to interpret data, apply commercial judgement, and bridge the gap between systems and outcomes is still in relatively short supply. Pricing, in particular, sits across multiple disciplines, data, finance, and trading, and that makes it harder to define, and often harder to hire for.
As AI becomes more embedded, that gap does not disappear. If anything, it becomes more important to have the right people shaping how those tools are used.
Final thought
What came through clearly in this conversation is that pricing is not a new problem, but it is becoming a more visible and more complex one. As Megan highlighted, the combination of margin pressure, customer expectation, and the growing role of AI is forcing retailers to rethink how they approach it.
From our side, what we continue to see across the market is that this is not just a technology challenge. It is a capability one. The retailers making the most progress are those who are able to bring together data, commercial thinking, and the right people to make sense of it.
Those who start to treat pricing as a strategic capability, supported by both technology and talent, are far more likely to protect margin and drive sustainable growth. Those who do not risk staying in a cycle of reactive decision making in a market that increasingly rewards precision.
A big thank you to Megan for sharing her time and insight on this topic. If this is an area you are currently exploring, it is well worth listening to the full episode for a deeper dive into the thinking behind it.
