Seeing the big picture with data fusion

Multi channel marketing with multiple touch-points means several data sources to query and separate analytics reports, resulting in fragmented insights. Wouldn’t it be great to see the big picture, and have a unified visualization of all the relevant data combined into one report, regardless of where the data set comes from? With Data Fusion all of this is possible.

With fusion reports visualized as cohort, funnel, path or table, you can analyze your event-based behavioral data in conjunction with the online campaign data and possibly cross it with the users’ personal information or payments history.

Sure, you could take care of it on the server side, with data integration or connection, or on the client side using linked data sources. But with the need to be agile and get quick insights – data fusion on the visualization level gives you a serious advantage.

Fusion of users’ behavioral data with contact details from CRM

A great example for the efficiency of the data fusion widget would be of a company that realized a serious issue with the Help section of their app. To reduce the damage and encourage users to stay, they decided to reach out by email and phone to those users who tried to access Help and failed. However, the users’ contact information was stored on another database, outside the big data behavioral analytics platform. Using the fusion widget in the behavioral analytics dashboard, they were able to join the external contact information with the report of users’ identified with this event action.

The analyst first turned to the behavioral data to create a report of all user id’s who ended their session with the event HELPThe assumption was that these users tried to get Help and failed, that caused them to leave.
CQL query of users funnel ended with request help
The second step was to query the external data set for users’ phone numbers and emails identified by userid. This was achieved using the the Linked Data source of the behavioral analytics platform. CQL query of user details
The two queries resulted in two separate reportsBig Data analytics reports
The fusion widget was used to join the reports. as simple as that. no SQL involved.. Fusion between datasets
The fusion report gave them a serious advantage with providing a quick response to a technical error that was reflected in users’ behavior. Surely the damage was reduced with the help of the big data behavioral analytics solution.
Big Data fusion analytics report

Fusing Data Without SQL

Another use case would be of a marketing campaign manager, a non-SQL user, who wanted to create a report for one major KPI – The Average Revenue Per Paying Active User (ARPPAU). This report was previously achieved by the analysts using CQL querying language. Thanks to the Fusion widget the marketing manager was happily able to perform the report himself.


He created the first KPI report (no SQL!) counting the paying users; COUNT DISTINCT users breakdown by day where event_name= payment. Next, he created a second KPI report summing the total payments per day- SUM (payment_amount) by day where event_name=paymentBig data fusion source reports

Finally, he created a fusion report joining the results from the two first reports and calculated the ARPPAU by dividing the revenue per day (from the second report) by the number of active paying users (from the first report). It’s that easy.
Big data fusion graph reports

In the frantic marketing and BI climate that is so common with online companies, agility, fast insights and quick actions are often crucial to the online success. Surely you can imaging a dozen of cases where you could have used the data fusion widget as part of your big data analytics, to facilitate the unification of data from two or more sources.

To experience big data behavioral analytics Sign up for a free trial, or request a private demo 

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