How would you recommend setting up a dynamic product block feed for a win-back flow to send targeted recommendations based on what customers purchased or viewed? The issue I’m running into is that the product feed skews toward women’s clothing, even if the purchased items are all male. One option I’m considering is splitting the flow paths based on the gender of the purchased items—for example, showing male products for male-only purchases and female products for female-only purchases.
However, I’m unsure how to handle orders that contain both male and female items. My thinking is that when an order contains only male products, the dynamic feed can focus on men’s recommendations, and vice versa for female products. But what would be the best way to handle mixed orders? Should I create a separate flow path for those, or use a weighted logic to determine which gender to prioritize? Also, would relying on browse data or predictive analytics in Klaviyo be a more effective fallback for mixed or ambiguous cases?
