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Shoppermotion

Glossary

Shopping mission

A shopping mission is the purpose of a store visit, such as stock-up, fill-in, urgent item or fresh food, inferred from the trip's path, duration, shopping tool and basket.

A shopping mission is the goal of a particular shopping trip. The same store serves very different shoppers at different times, and the reason they came in says a lot about how they will behave: a stock-up trip covers most of the store, usually with a trolley, while an urgent-item trip is short and direct.

Shoppermotion uses four standard missions: stock-up (long trips covering most of the store), fill-in (medium trips to replenish a handful of categories), urgent item (short trips for one or two products) and fresh food (trips focused on produce, bakery, butcher or fish). Each visit is assigned a mission by a model trained on millions of trips, which takes into account variables such as time and day, shopping tool, duration, zones visited, stops, order of categories and the items on the matched ticket. See the shopping missions article.

Knowing which mission prevails in each store and daypart lets category managers adapt assortment and layout, and lets media teams target in-store screens to the right audience. Missions are also one of the ways to build smart audiences for retail media.

The blog has several examples. For a new non-alcoholic ready-to-drink brand in Brazil, choosing the display spot and launch time by mission raised campaign sales by 18.3% (why analyse shopping missions). In a Shanghai retailer, 68% of the traffic reaching the shampoo category came from a secondary aisle, and placing the promotion on that aisle's end cap increased qualified traffic by 14% (the best spots for in-store activations).

FAQ

Questions, answered.

What are the main types of shopping missions?

Shoppermotion uses four standard missions: stock-up, fill-in, urgent item and fresh food. Some blog articles group them slightly differently, for example with a daily shop mission.

How is the mission of a trip identified without asking the shopper?

From the trip itself: a model trained on millions of trips classifies each visit using variables such as time and day, shopping tool, duration, zones visited, stops, order of categories and the matched ticket.

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