Contextual Guidance for Autonomous Decision Making in Retail Video Transcription


Using artificial intelligence software to make decisions requires contextual guidance or support to explain the rationale for those decisions. In retail, contextual guidance in merchandise planning includes defining all the retail mechanics that go along with the recommended decision. You want to compare those mechanics to what worked well in the past.

Examples of Contextual Guidance in Retail


For example, AI recommending a price point should be compared to historical price points that worked well or compared to competitor current pricing. Looking at the time of year to say does this product work well at this time of year. Considering the promotional placement, putting it on the front page of the flyer or an end cap, does that work well? And comparing the promotional frequency or cadence. How often have you promoted this product? All of this context will build confidence in the retailers that the AI is making good recommendations. At Daisy, we see what others don’t.


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