What are merchandising rules?
Merchandising rules are manual conditions that can programmed into an automated product recommendation engine. Although automated recommendation algorithms have a strong track record, merchandisers need the flexibility to override the system and create unique targeting rules to maximize revenue.
Merchandisers may require the ability, for example, to pin a specific item or to include or exclude a particular set of items from the automated recommendation results. For instance, merchandisers can set rules that inform the recommendations engine to:
- Include popular items in a product category a consumer has viewed over a set period of time (e.g. display of a popular item in “mens’ shorts” to a visitor who has viewed at least two pairs of mens’ shorts in the past 30 days)
- Recommend highly profitable items to consumers who have purchased or added to their carts items valued at $200 or more in the past 7 days
- Refrain from displaying clearance items promoted in other areas of the brand’s site to high-value customers
- Prioritize overstock items or promote discovery of best sellers, ensuring they are served to every visitor on the homepage
Manual Merchandising and Personalized Product Recommendations
Merchandisers may also decide to use multiple strategies in the same recommendation unit to engage both returning and anonymous shoppers. To induce engagement among returning customers, merchandisers can create conditions to serve personalized recommendations based on what the visitor has added to their cart, bought, or viewed in the past. To target new or anonymous visitors, the same unit can present items with the highest page views and click-through rates on the site.
Maximize revenue from machine learning product recommendations
At the end of the day, no one knows their products better than your merchandisers. To maximize revenue from product recommendations, merchandisers need to be paired with a machine learning recommendation solution that allows merchandisers to leverage their unique expertise and decision making to make extremely relevant and powerful recommendations.