Blueshift: Cross-Channel Customer Identity

Overview: Blueshift's solution helps you maintain a 360-degree profile of customers that updates with every customer interaction. This profile is linked to customer identifiers on each channel: email address, phone number, mobile app device tokens, as well as 3rd party identifiers like Facebook or Display RTB ids.

Blueshift automatically merges anonymous (logged-out) activity of users with their known behavior whenever possible (e.g. in the case of an anonymous web user who logs in or creates an account). After a few days, Blueshift will merge the anonymous browsing data with the known customer profile Similarly, using email click data, Blueshift is able to map some anonymous sessions to known email addresses.

Blueshift's SDK (for mobile apps), Javascript library (for web front-end events), and API (for all other actions) give you a comprehensive set of tools to track known and anonymous customer behavior on the web, mobile and offline platforms.

Raw data is automatically enriched with inferred attributes like gender or location. Based on the first name, our solution can infer with high confidence that John is male and Amy is female. However, it might be hard to determine the gender for a unisex name like Beau. Likewise, the solution will automatically infer the city or country from IP addresses or lat/long.

Finally, the solution also maintains user preferences (e.g. unsubscribe from emails) on all marketing channels.


1. Does the solution provide a consolidated view of each customer’s identity on different channels: email address, mobile device tokens, phone numbers, addresses, and identities on 3rd party ecosystems like Facebook & Display Retargeting?

Yes, Blueshift keeps track of email address, phone number, mobile app device tokens, as well as 3rd party identifiers like Facebook or Display RTB ids.


2. Does the solution maintain unsubscribe or opt-out information for each channel?

Yes, Blueshift maintains opt-out information for all the supported channels.


3. Is the solution capable of identity resolution between known and anonymous user data?

Yes, Blueshift automatically merges anonymous (logged-out) activity of users with their known behavior whenever possible. In the case of an anonymous web user who logs in or creates an account after a few days, Blueshift will merge the anonymous browsing data with the known customer profile. Similarly, using email click data, Blueshift is able to map some anonymous sessions to known email addresses.


4. Does the solution automatically append relevant data like location and gender based on raw data like IP address, lat/long or first name?

Yes, the raw data you send into Blueshift is automatically enriched with inferred attributes like gender or location. Based on the first name, our solution can infer with high confidence that John is male and Amy is female. However, it might be hard to determine the gender for a unisex name like Beau. Likewise, the solution will automatically infer the city or country from IP addresses or lat/long.



});