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Most retail execution reporting proves that something happened at the same time as something else. Compliance went up in Q3 and sales went up in Q3, therefore compliance drove sales. Perhaps it did, or the weather was good, a competitor was out of stock, a category promotion ran, and compliance improved because your best representatives were reassigned to your best stores.

The Pitch stage industrializes what good representatives do instinctively. The platform creates a custom pitch for that store buyer, for that moment in time, provides options rather than a single script, tracks the usage of the pitch through breadcrumbs so it can be analyzed later, and automates the administrative process of turning a sales pitch into an order.

Somewhere in the system there are dozens of exception rules firing daily into a representative’s task list. They flag out-of-stocks, price gaps, compliance failures and distribution voids. The rules work. The alerts are accurate. Even so, adoption is somewhere south of forty percent, because the representative opens the list, sees eighteen items, has time for four, and has no principled way to choose.

Every AI recommendation engine in consumer goods rests on an assumption that is almost always wrong: that the state of the store in the system matches the state of the store in the world.

Here is an uncomfortable question to put to your commercial leadership team: what percentage of your field visits this quarter were to stores where there was no meaningful incremental opportunity?

Field selling in consumer goods has an arithmetic problem that no amount of effort can solve.

Your advertising got them through the door. Now everything depends on what happens at the shelf.

From Insight to Impact Across Every Store Visit

As the worldwide liquor marketplace becomes increasingly competitive, staying ahead at the shelf is critical.

See the Future of Data-Driven Retail Execution in Real Time.