While modern open source search engine technology has become very robust, search platforms like Solr and Elasticsearch require businesses to tune their product content and complex relevancy matching rules in order to optimize search result rankings. These adjustments often require specialized technical expertise and significant time investment. In contrast, Convert bases its rankings on user behavioral data about what users have actually purchased when they encountered a list of products. Furthermore, Convert allows merchants to manage these search tuning adjustments through a user-friendly business tool.
Articles in this section
- What does it mean when Convert says that a rank model is unavailable?
- How much data needs to be provided to obtain accurate rankings from Convert?
- How long does it take to start seeing recommended product rankings from Convert?
- Is Solr performance impacted when Convert's rankings are implemented?
- Which areas of the shopping experience can be optimized by Convert?
- How do I tweak the results that Convert recommends? For example how do I make sure that my sale and new items still end up on top of lists?
- Can Convert help with offline purchases or collect data from offline purchase channels?
- How much effort is involved in integrating Convert with my existing commerce and search platforms?
- Is replacing our commerce platform, analytics tools, or search platform required in order to use Convert?
- That’s great that it works with our site's existing tools, but that sounds like an expensive implementation project, right?