Shoptalk 2025: What Ecommerce Leaders Really Need From Their Data
Picture hundreds of retail leaders comparing notes on AI, bottomless trays of cookies, and booths stacked with vendor swag (and one with puppies). That’s ShopTalk. After a few days wandering the expo floor in Chicago, I came home with a clearer sense of what’s actually happening with ecommerce data right now. In short, the industry is flooding with new data streams and flashy AI promises, but the discipline and culture needed to make that data meaningful are lagging behind.
Here’s what we learned about AI, data quality, and what’s next for ecommerce leaders from Shoptalk 2025.
Database Tycoon CEO & Founder Stephen Sciortino and COO Heather Rametta
The Data Deluge in Retail
Every retail leader I spoke with described the same challenge: Data is streaming in from dozens of platforms (marketing, loyalty, logistics, point-of-sale, customer support). It isn’t empowering decisions. It’s noisy! Teams are still toggling between spreadsheets and half-configured dashboards, trying to stitch together a single version of truth. We found ourselves having the same conversation again and again: more data isn’t the answer, usable data is.
Without a common model and accessible layer, even the best analytics tools can’t deliver insight when it matters.
AI Is Not a Magic Wand
You can probably guess that AI was the buzzword of the week. Many executives were refreshingly candid. “Garbage in, garbage out” is still the AI vibe. Most leaders see AI as a speed multiplier, not a replacement for thoughtful analysis. Product-description generators and predictive models can be powerful, but only if the underlying data is clean, consistent, and well-governed.
One CTO put it bluntly: “We’re budgeting more for data quality than for AI pilots this year.”
“ We’re budgeting more for data quality than for AI pilots this year.”
The Data Migration Hangover
Many companies invested in major “data migrations” or hired agencies to implement modern analytics stacks, only to watch adoption stall. People changed roles, training never stuck, and documentation never came. Months later, the expensive new platform is collecting dust and causing anxiety. These same teams are reverting to their trusty 100k row excel sheets.
The lesson here? Adoption requires more than tooling and trust me, we love tooling. Training, ongoing support, and internal champions are critical.
Insights Are Never One-Size-Fits-All
Every team’s “must-have metrics” were different. Some want deep visibility into returns and warranties. Others are more focused on competitor pricing signals. There are products that do seemingly everything, from tracking the customer journey on a website with heat mapping to locating a product with a spoken query using an agentic AI agent. What do we do with all this data? No single dashboard can hold it all effectively, or surface the right insights.
As consultants, we start every engagement with a listening tour:
What decisions are you actually trying to make?
Which numbers move the needle for your business?
Culture Beats Tooling
The most mature data organizations weren’t bragging about their stack, they were bragging about their habits. Shared definitions, data governance, and regular best practice training creates trust in the numbers which builds a reliable decision-making culture.
As one VP of Operations told me, “Our dashboards are boring, and that’s a good thing. Everyone knows where to look and what it means.”
“Our dashboards are boring, and that’s a good thing. Everyone knows where to look and what it means.”
Looking Ahead
A handful of forward-thinking brands are already exploring real-time personalization, dynamic pricing, and AI-driven merchandising that updates sites minute by minute.
It’s exciting, but every one of those initiatives depends on the fundamentals: clean pipelines, a semantic layer, and a team that can read and act on the data.
So much of how we work and shop is digital, but I kept thinking about the physical world while I walked Shoptalk’s floor. If you ran a physical warehouse, you wouldn’t toss pallets into a dark room and hope for the best. You’d label every aisle, track inventory, and know exactly where each item lives. Without that order, even the fanciest forklift can’t help. You’d waste hours digging through piles of stuff.
A data warehouse is no different. If your data isn’t organized, labeled, and measured, your BI tools are just forklifts with nowhere to drive. Clean pipelines, clear naming, and shared definitions turn a chaotic heap of data into an inventory you can actually use.
Final Thought
For me, Shoptalk 2025 confirmed a simple truth: a modern data stack isn’t just a collection of the best tools. It’s a culture and a process. The companies that win aren’t the ones with the flashiest dashboards or biggest AI budgets. They’re the ones who make data reliable, accessible, and central to every decision.
How Database Tycoon Helps Retailers
That’s the work we love at Database Tycoon: helping brands move from merely collecting data to confidently using it.
We help ecommerce teams cut through the noise and build data cultures that last:
From spreadsheet chaos → to trusted dashboards
From failed migrations → to lasting adoption
From flashy AI promises → to real results