We believe that this feature will increase your users’ collaboration and engagement by presenting personalized recommendations with the most relevant content.
The recommendations are based on the following:
- After submitting an idea, recommending for other campaigns by looking for common interest to the current user and other users that were engaged the current campaign (i.e. in which campaigns those users participated).
- After commenting/voting on an idea, recommending for other ideas by looking for common interest to the current user and other users that were engaged the current idea (i.e. in on which ideas those users collaborated).
This is a more detailed explanation:
--> Once a user comments or vote, we are checking which other users also commented/voted on this idea --> we have now a list of X users.
--> Then we are checking on what other ideas, these X users commented/voted.
--> We are sorting these ideas according to the number of users that collaborated on them, by descending order.
The recommendation will be on the 3 top ideas.
The algorithm is based on the assumption that if multiple users that showed interest in this idea, showed interest also on other specific ideas.
These specific ideas might be relevant to the current user (the one that sees the pop-up) as well.
We "borrowed" it from shopping sites:
"Users that purchased this T-shirt also purchased this hat..." :-)
This video highlights the Smart Recommendations feature:
https://qmarkets.fleeq.io/l/ecsfxwn0t8-iah80tmstj
Sysadmins can disable/enable the smart recommendation per subsystem, please go to setting (gear icon on the main menu)-->smart recommendation section.
To access additional resources to support your innovation catalysts, please visit our Innovation Catalyst Kit.