AI Agents · Head of Retail
ARC: Head of Retail
ARC studies every store in the network individually, including who walks in, what they buy together and which categories over-index. It uses that profile to decide which of your products belong there, at what price, with how many facings.
31%
Higher sell-through on matched placements
Store-level
Audience profiling
Continuous
Re-scoring as data comes in
What it decides
ARC makes calls, not suggestions in a slide deck.
Learns each store to get the target audience right.
Store profiling
Builds a shopper profile per location from footfall type, basket mix and category affinity.
Product-to-audience matching
Scores each of your SKUs against each store profile, so the right variant goes to the right neighbourhood.
Facings and placement
Recommends how much shelf space a product should hold and when to increase or release it.
Promotions that fit
Suggests bundles, sampling and price tests where the local audience responds, not blanket discounts.
Live decision feed
A sample of the calls this agent makes on a normal day.
What it reads
Accuracy comes from the inputs, not the label.
- Per-store basket and category mix
- Footfall type and time-of-day patterns
- Competing product performance in the same aisle
- Sampling and promotion results
See ARC working on your catalogue.
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