Q&A: Alex Considine Tong, Chief Product Officer, Retail Insight
At Retail Insight, they turn data into smarter, faster decisions. Their AI-powered analytics platform helps retailers optimise sales, reduce waste and improve execution across store, shelf and supply chain.
What experiences on your journey shaped the way you approach retail innovation today?
My career has been shaped by working at the intersection of technology, data and real world operations. Early on, I saw how often retailers had huge amounts of data but no clear way to turn it into actionable decisions. That stuck with me. I’ve also experienced the challenges of scaling digital products in high-growth environments where demand outpaces systems and clarity is everything.
Those experiences taught me the importance of building for value, not just velocity and creating the right culture and frameworks so teams can innovate sustainably. At Retail Insight, that translates into a relentless focus on impact, helping retailers cut through the noise, act on what matters most and scale their decision-making with confidence.
How would you sum up what you do and what makes your solution stand out from the pack?
At Retail Insight, we turn data into smarter, faster decisions. Our AI-powered analytics platform helps retailers optimise sales, reduce waste and improve execution across store, shelf and supply chain. What sets us apart is that we’re built specifically for retail; our models and solutions are grounded in decades of retail science and refined with live operational data. At Retail Insight, we marry deep retail experience (many team members have run stores themselves) with advanced data science to pinpoint exactly where availability and waste intersect and create verified fixes that reduce losses while growing margin.
What is it about your platform that really makes a difference for retailers?
Retail is full of complexity and it’s easy for data to overwhelm rather than enable. Our platform makes a difference by simplifying the signal-to-noise ratio. We show retailers what happened yesterday of course but more importantly we give them actionable insights on what to do today and predictions about tomorrow. That means they can optimise promotions before they underperform, reduce waste before it hits margins and keep shelves full without overstocking. The real difference is speed to value. Our solutions are deployable quickly, integrate with existing systems and deliver measurable ROI without the long lead times retailers often fear with AI projects.
Can you share a few examples of retailers you’re working with and how they’re turning data into results?
We work with many of the world’s top grocers and FMCG brands. For example, one leading supermarket chain used our waste optimisation tool to refine its offer strategy. By shifting from a blanket discounting model to one based on predicted performance, they saw millions in incremental margin while reducing wasted stock.
Another global retailer uses our shelf execution analytics to ensure availability across thousands of stores. Instead of waiting for manual audits, they get real-time signals on where shelves aren’t meeting demand so they can intervene before sales are lost. These examples share a common theme; turning complex data into clear, practical actions that make a measurable difference on sales, waste and customer satisfaction.
What’s the smartest first step retailers can take to get more value out of the information they already have?
The first step is to ask the right question. Too often, retailers start with ‘What data do we have?’ rather than ‘What problem are we trying to solve?’ Whether it’s waste or availability effectiveness, clarity on the problem helps unlock the value already sitting in their systems. From there, the smartest move is to focus on a small, high-impact area and prove the value quickly. For example, analysing promotion data in one category can reveal patterns that drive immediate margin improvement. Once retailers see that impact, it becomes easier to scale across the business.
2025 hasn’t been an easy ride for retail so far. From your perspective, what are the biggest challenges retailers are wrestling with right now?
Retailers are grappling with margin pressure from all sides, specifically inflationary costs, shifting consumer demand and changing regulatory requirements. At the same time, the operational complexity of omnichannel retail continues to rise. Customers expect more choice, faster delivery and consistent availability, while retailers are under pressure to be more sustainable and reduce waste.
Data is central to solving these challenges, but many retailers are still struggling with fragmented systems, latency and the skills gap to make sense of it all. The problem is not about having enough data but about making it usable, actionable and scalable across the enterprise.
Looking ahead five years, how do you see the balance between human decision-making and AI shifting in retail? And what will be the must-have solutions for retailers?
I see AI taking on more of the heavy lifting in decision-making, particularly in areas where speed and scale exceed human capacity, such as inventory optimisation, demand forecasting or promotion modelling. But I don’t see AI replacing human judgment, it will augment it. The best outcomes will come from humans and machines working together, where AI generates the recommendations and humans apply context, creativity and empathy.
In terms of must-have solutions, I believe predictive analytics, real-time shelf execution and AI-powered margin optimisation will move from nice-to-have to business as usual. Retailers won’t be able to compete effectively without them.
But the real differentiator will be platforms that combine these capabilities seamlessly, making insights simple to act on at every level of the business, from head office strategy to in-store execution.
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To find out how Retail Insight can help your retail operation, visit them online here.
