Product managers can define searchandising rules to align search results to their business objectives – whether by profitability, supplier, availability, or popularity.
Businesses can promote some products by boosting their search ranking, so they appear on the top of the list or bury them at the bottom.
Searchandising rules can be quite complex and consider categories, touchpoints, margin, available inventory, product attributes,.
Some slots on categories pages can be reserved for a specific purpose, such as promoting products from important suppliers.
For example, a travel aggregator, Booking.com, needs to find the right balance between satisfying customer needs, revenue generated for business partners, and its own margin.
With recommendations and search tied together and empowered by AI, the recommendation logic can adjust to each customer in real-time by combining customer data with customer behavior. System analyses clicks, shopping cart content, search terms used by customers, demographics, previous purchases, and even the weather. Thanks to AI, search results can be personalized for individual customers promoting to the top her preferred brands, colors, or categories.
Every digital commerce system has some built-in merchandising and Searchandising tools. However, that may not be enough if you want your business to benefit from advanced techniques utilizing artificial intelligence and empowering business users with powerful tools.
In that case, you will need to look at specialized systems like Bloomreach, Algolia, Factfinder, and others.
It is a good idea to continually monitor how customers are using the search on your site and adjust your Searchandising strategy based on changing customer preferences, business objectives, or new additions to the catalog.