Data analysis: Comfama's key to knowing its users
About the client
It is a Family Compensation Fund of Antioquia, Colombia that was born 65 years ago due to a voluntary pact between employers and unions to improve the quality of life of the working population. The company provides its members health, credit, housing, education, and cultural services.
Currently, its purpose is to consolidate and expand the working middle class of Antioquia to make it conscious, free, productive, and happy.
What was the challenge?
Comfama has traditionally delivered bulk emails to its subscribers without doing an in-depth analysis. However, when the company recognized the need to reach out to their prospects with a personalized message, they created a customer relationship staff. They found a digital partner to build a customer loyalty strategy. At this point, they came to us.
Outcome: Our impact
01.
Converted 1,997,728 enrollment registrations to 315,627 unique users
3,698 users were enrolled in Comfama's programs
81.6% was the conversion rate
Based on the data, we identified the need to activate the cross-thematic group of art and sports. Thus, hand in hand with the creative area, the 'Complementarte' campaign was born, which seeks to encourage people to enroll in various programs and not limit themselves to just one.
With data analysis, we sent 48,168 segmented mailings, with an open rate of 32.4% and a click rate of 6.5%.
What did we do?
We partnered with Comfama to analyze and segment users participating in their education, sports, and cultural programs. Then, we decided to offer intelligent campaigns based on data analytics to boost the number of people registered for Comfama's courses.
As input, our data analytics specialists worked with a database containing 1,997,728 enrollment records from Comfama's programs over the past three years.
The first thing we did was turn that information into clusters of users utilizing data analytics methods. From that analysis, 315,627 people remained, with additional variables we created depending on the goal we were looking for user continuity, age categories, and courses of interest.
The data also enabled us to get to know consumer behavior and uncover combinations of topics they prefer. Consequently, this information also allowed us to find cross-referenced topics. Art, athletics, and gastronomy are a few examples.
Based on the conclusions of the analysis, we decided to activate sign-ups for two complementary topics: arts and sports. Therefore, the creative department launched a campaign inviting prospects to register for many programs rather than just one.
Roles
Data consultant
Data architect
Data scientist
Engineers
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