Blueshift provides a complete view of your users by aggregating data from the various touch points - activity on web/mobile, user data, campaign activity, etc.
To see an example in your account, navigate to the Customer Attributes tab, search for a user and click on view.
We organize a user's information into 4 buckets.
1. Overview: Comprises of standard and custom user identifiers, key lifetime stats, predictive stats and visual representation of recent activity with your content/products.
2. Campaigns: Messaging activity for all campaigns sent to the user
3. Activity: User generated actions/events
4. Recommendations: Preview recommended content/products based on pre-defined algorithm
Blueshift builds a 360-degree user profile by tracking both anonymous and logged in behavior across devices, as well as sessions and merging them using explicit first-party data.
Blueshift merges anonymous user profiles based on sign-in activity (i.e. using first-party login data). Blueshift uses explicit, deterministic methods to merge user profiles.
Blueshift uses a hierarchy of user identifiers for profile merges. They are, in order:
- uuid: Blueshift internal uuid for each user
- customer_id: Unique customer id from your system
- email: Email address
- device_id: One or more device ids associated with the user
- cookies: One or more cookies associated with the user
User profiles get merged when either a customer_id or email (or both) are available, with the customer_id getting a higher priority.
Consider the example below:
- An anonymous user browses the /about-us page on your website. This information is sent to Blueshift using a pageload pixel. The cookie is sent automatically for every website event.
pageload(cookie: 5b3f64aa-717c-4e75-ace6-8f610821b098, url: domain.com/about-us)
- The same user opens the mobile app later in the afternoon and views a few products. This information is sent to Blueshift using the Mobile SDK with a item view event. The device_id is sent automatically for every mobile SDK event.
view(device_id: e9cc01a4-3473-4df2-a715-30da584ac398, product_id: 123)
|[e9cc01a4-3473-4df2-a715-30da584ac398]||[viewed product 123]|
- The user signs in to the mobile app with email firstname.lastname@example.org and USERID1. This information is sent to Blueshift using an identify pixel. We find the user with the matching mobile device_id and update that user's customer_id and email address.
identify(customer_id: USERID1, email: email@example.com, device_id: e9cc01a4-3473-4df2-a715-30da584ac398)
|[viewed product 123]|
- The user returns next day and signs in to the website with firstname.lastname@example.org and USER1. At this point, we detect that there are two profiles for the same USER1 and trigger a merge resulting in a single customer profile with all attributes and behaviors merged.
identify(customer_id: USERID1, email: email@example.com, cookie: 5b3f64aa-717c-4e75-ace6-8f610821b098)
|USERID1firstname.lastname@example.org||[5b3f64aa-717c-4e75-ace6-8f610821b098]||[e9cc01a4-3473-4df2-a715-30da584ac398]|| [viewed /about-us,
viewed product 123]