This release marks the general availability of the real-time web tracking and personalization feature. This feature enables two key capabilities: website personalization for known and unknown users, as well as conversion of unknown users to known users.

Track unknown user activity. When users return to your site, personalize it based on their previous browsing behavior on your site.
Personalize your website using a pro-code API-driven approach for experienced development teams or use built-in integration with Optimizely to personalize your site using a no-code approach.
When an unknown user provides you with contactable details like an email address or phone number, you can convert the unknown user into a known profile that persists the tracked activity data from when they were an unknown user.

Scenario

Susan wants to convert more browsing activity on her site into sales. She copies the tracking script from the web tracking and personalization feature in Customer Insight - Data and sends it to her web administrator who adds it into the company’s website header. Within seconds, Susan can see website traffic showing up in Customer Insights - Data as unknown user profiles. Detailed logging for each unknown user is recorded in Dataverse tables.

She considers having her web team write code to personalize the homepage based on the browsing behavior but decides to use her company’s Optimizely license to customize the site. Her web team has already added the Optimizely script to the site’s header, so she selects Set up Optimizely integration in Customer Insights and is taken to the Optimizely site where she customizes her website to show returning users a special deal on a product they previously viewed. This results in an uptick in customers making a purchase.

Later, Susan works with her team to add a few lines of code to the site so that when a customer makes a purchase and provides their email or phone number for shipping status, she is able to create a unified profile that brings in all the user's activity from when they were still anonymous. Instead of new "known users" starting with a fresh profile, Susan sees their activity and discovers other products and services each customer showed an interest in.

Susan creates some additional marketing segments that groups these known users based on prior browsing activity while anonymous. She launches new campaigns in Customer Insights - Journeys that offer more incentives to users based on what they indicated an interest in and is able to convert more passive browsing to sales.