Guidelines for merchandisers to improve search by enhancing NLP data
As a merchandiser, you must review the search results and their relevancy from the storefront. You must then teach the Natural Language Processor (NLP) to learn about your business data so that the NLP function can provide more accurate search results to shoppers at the storefront.
Enhancing the NLP capabilities
- Add custom noun and classification to NLP Name-Entity-Recognition.
- Add custom configuration to Color Matchmaker.
- Add custom configuration to Measurement Matchmaker.
- Add custom range filter to Matchmaker.
For more information, see Natural Language Processing (NLP) in Version 9.1.
Search based merchandising with Search rules and STA
Search relevancy and merchandising is the process of controlling the search results that are returned to shoppers in the storefront, and the order in which they appear. There are several techniques that can be used to influence search relevancy, which lets you return products in the order that best suits your business needs. For more information, see Search relevancy and merchandising.
You can also use search rules, which trigger some action when the customer does a specified search. For more information, see Managing search rules.