Torgeir is segment lead for commercial sectors at Frontkom. He works closely with retailers, B2B companies and financial institutions, and this is a pattern he sees in almost all of them.
The average retailer with both physical and digital presence holds data from their online store, point-of-sale system, loyalty programme, email list, social media channels and Google Analytics. In theory, this is a goldmine.
In practice, it rarely is.
And the reason is almost never that the data is missing.
The problem is not data volume, it is infrastructure
The data lives in separate systems that do not talk to each other. The point-of-sale system does not know the customer is also registered in the loyalty programme. The email platform does not know which product categories she bought last week. And the online store does not know she visited the physical shop four times before placing an order online.
The result is that the insights that could actually lead to better decisions are only available to people willing to run three manual exports and spend two hours in Excel. And nobody does that consistently.
This is not a data volume problem. It is an infrastructure and ownership problem. And it is solvable.
What retailers who win on data do differently
After years of working with retail, Torgeir sees three clear patterns in the companies that actually manage to use data to grow:
One source of truth. Not five dashboards showing slightly different numbers where everyone can argue for their own version of reality. One platform where all relevant data is collected and standardised. Whether that is a CDP, a strong BI solution or a well-defined data architecture does not really matter. What matters is that it exists and that everyone uses it.
They understand the purchase journey, not just the transaction. What happens in the 14 days before a purchase? Which touchpoints are decisive? Which channels drive loyal customers versus those who buy once and never return? These questions are far more valuable than "What did we sell most of last month?"
They act on insight quickly. Data has a shelf life. An insight that a particular customer segment is not returning after their first purchase is valuable when you can launch a retention campaign this week. It is far less valuable when it is presented at the next quarterly review.
AI is changing what is possible
In 2026 the opportunities for data-driven retail are greater than ever, and growing fast. AI makes it possible to analyse purchasing patterns, predict churn and personalise communication at a scale that was simply not possible three or four years ago.
But AI tools are only as good as the data they receive. Garbage in, garbage out. Retailers who invest in clean, connected and accessible data now are laying the foundation to use AI effectively when they are ready.
Those who wait on data infrastructure until they are "ready for AI" are putting their AI investment at risk.
Where do you start?
It does not need to begin with a large transformation project. Start with one question you genuinely want answered: Who are our most loyal customers, what defines them, and where did they come from? Then map out what data you need to answer that, and whether you have it available today.
Want to know how your retail business stands on data infrastructure, and what the next steps with the highest impact look like? Get in touch with Torgeir and our team for an assessment.