Many people talk about "smart pricing," but this often hides either an overloaded BI system or a "black box" that's difficult to trust. RetailGrid wins by positioning itself as an "AI-powered retail workbook"—an environment where AI assists, but decisions remain transparent to humans. And this is an important nuance: in retail, the "just trust the algorithm" approach doesn't work. The team needs logic, context, and the ability to quickly test hypotheses.
What I like about RetailGrid is its focus on connecting factors. Price isn't considered separately from demand, promotions, and assortment—which is exactly how real retail works. When you can see the product, sales trends, margins, the impact of past promotions, and current price movements in one place, it's much easier to make decisions and defend them internally. The sales department understands the logic, marketing sees what's happening with promotions, and purchasing understands which items are pulling the product mix down and where adjustments are needed.
Another advantage is the process's manageability. When everything is structured in a "notebook" format, iterative work is possible: first, identify a problem or opportunity, then generate a set of options, assess risks, select an action, and then test the results. This turns pricing into a repeatable practice, rather than a series of stressful changes. And this is how a culture of data-driven decision-making gradually emerges: people aren't afraid of numbers because the tool doesn't complicate life, but rather makes it clearer.
Simply put, RetailGrid helps retail teams think faster and more confidently. It's a modern pricing intelligence software tool, where the focus isn't on grandiose promises, but on a user-friendly, easily understandable logic for managing prices and market signals in one place.