Library overview
Personalization Library overview
Personalization Library is one of the core components of Acoustic Personalization. The Library matches the personalization rules (created by the marketer) with the visitor behavior data received from Acoustic Exchange. Based on this comparison, the relevant personalized content or product recommendations are shown on the website.
How Personalization Library works
Personalization Library receives the visitor behavior data and channel events data from Acoustic Exchange. The Library matches this data with the personalization rules created by the marketer, and based on this comparison, suggests results for personalized content. These results are further processed to generate the personalized content as per the content type, and passed over to content rendering mechanism of the channel to be displayed on the zone.
Caching
Caching is a mechanism used by web browsers to store web page resources locally. This improves performance and minimizes the bandwidth consumption.
Personalization Library uses caching mechanism to collect and store the visitor behavior and events data in local browser memory, termed as Local Storage, so that this information can be used to generate relevant personalization and product recommendations.
When a visitor visits the channel for the first time, the Personalization Library is loaded. The Library uses the data stored in LocalStorage variables (rulesData and caricatureData) for one hour. After one hour, data in these variables is auto-refreshed, that is, latest data is fetched and stored in these variables which is used by Personalization Library for the next hour.
If you are using shared audiences, then this one-hour interval is also used to match the visitor ID received from the Library with the X1ID from the Acoustic Exchange.
When you publish a new rule in Personalization, the personalized content generated as per the successful evaluation of the new rule will be displayed on the channel one hour after the initial page load by the visitor.
Updated almost 2 years ago
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