Collaborative Filtering Recommendations
Marketers know that they can drive nearly 10 times greater conversions by personalizing their marketing messages based on each user’s purchasing and browsing history. Collaborative Filtering helps you leverage the power of your website or app’s community of shoppers to help craft useful recommendations for your users based on the behavior of “People Like You” who browsed or purchased similar items.
Collaborative Filtering Recommendations can take a few different forms, including:
- View-> Purchase: For users who were browsing/viewing products, collaborative filtering helps find the items that were purchased by others after viewing the same items as the user
- View -> View: If you are interested in driving more engagement instead of purchase, you can use collaborative filtering to recommend the items that others viewed after viewing the same items as the user
- Purchase -> Purchase: For users who recently purchased something, collaborative filtering can be used to find the items that others purchased after purchasing the same items as the user
Automating Collaborative Filtering With Blueshift
Blueshift’s Interaction Graph makes various forms of collaborative filtering readily available for your use.
Once you create templates for email, push notifications, SMS etc, you can simply select from the various forms of collaborative filtering to personalize the content of your messages.
Free Download: Marketer's Playbook on Collaborative Filtering
Download this PDF Playbook & Learn:
- How to develop collaborative filtering recommendations
- How to automate collaborative filtering across every marketing channel