Leverage data to keep up with the way customers search
Prioritizes your search results based on an individual shopper’s search behavior, browsing patterns and personal affinities
Use continuously learning technology that understands the way people search and helps surface what they are looking for
Modify search results by boosting/burying products based on trends, predictions or upcoming promotions.
Personalize using cross-device behavior and offline customer data, including in-store purchase history.
Machine learning algorithms listen for trends outside of your organization and continuously improves the search results.
Natural language processing capabilities help match products on your site to what consumers are searching for.
You don’t know Jack (or Jill):
The State of Online Personalization
How should you measure site search?
1-1 personalization is the key to crushing the digital experience