A boutique sells dresses, blouses and jackets in small collections that change every few weeks. Scnario reads each customer’s style cluster, size and return behavior, so new arrivals reach the customers most likely to keep them, and serial returners stop getting the same offers as loyal buyers.
Small runs sell out. The first customers to hear about a drop should be those whose style cluster and size match it.
A customer who orders five dresses and keeps one looks active. Net value after returns shows who is growing, and Zero-Order contacts show intent without value.
A dress buyer who adds a jacket is building a wardrobe with the boutique. RFC tracks that breadth across dresses, blouses and outerwear.
Each scenario starts from a lifecycle phase and a segment move in RFM, RRM or RFC. The signal says when to act, the scenario says what to do, and the metric shows whether it worked.
Dress customers carry the most value and return the most. Jacket buyers order twice a year at a high basket value, which makes the season change their main moment.
Open the CD report →Estimates for a typical boutique store running the five scenarios above for 12 weeks. Each number is one of the metrics the scenarios are measured by.
Estimates based on typical ranges for the category. Actual results depend on base size, channel mix and starting point.
See how Scnario can turn your customer data into a living understanding of every relationship — and a clear decision about what should happen next.
