Behavioural merchandising
Locayta ESP uses behavioural merchandising algorithms to provide recommendations in real-time, based on users’ behavior on your site. Behavioural merchandising works at both an anonymous “collective intelligence” level and at a personalised level.
This means that Locayta ESP can provide both generic recommendations based on the collective intelligence of the site, as well as more personalised recommendations based on an individual’s past and present behaviour.
“Weighted user journey” algorithms track user actions on your site and associate a weight for each action such as Viewed, Added to basket or Checked-out. Recommendations are based on what has been searched for, viewed, added to basket and purchased by the user in relation to both that user’s previous actions and the actions of all the other users of the site.
Recommendations are constantly updated, so actions such as viewing, adding to basket and purchasing, will affect recommendations on your site in real-time. The weighting can be adjusted to raise the importance of any one of these actions – e.g. you might want to promote an expensive high margin item that is viewed but seldom purchased by increasing the weighting attached to viewing that item.