The boost and bury functionality available from the leading merchandising and search tools is great to elevate more relevant products to the top of product results lists. However, this process requires continuous manual effort from business users to identify which items to boost. Convert automates this process by using its machine learning algorithms to evaluate user behavioral data to determine what items should be prioritized for any given product listing. Convert can then apply the rankings it determines without requiring effort from business users or developers.
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?