Marketing Technology has undergone a technological revolution over the past 10 – 15 years. Today marketers are able to track the smallest of digital footprint like scrolls on mobile or web apps. Armed with the digital trove of user behavior data, marketers are trying to nudge and retain their users across the customer lifecycle.

But, why are conversions per campaign in low single digits? Why does an app lose 90% of the newly acquired users in the first month?

A marketer of a medium sized app (MAU ~ 20,000 and 50 events per user per month) has to analyze atleast 1 million data points monthly. In order to be agile, marketers tend to cut corners and take sub-optimal data driven decisions. As a result, conversions rates are poor. A sub 1% conversion rate is quite common i.e. 99 users out of 100 are not interested in the app’s messaging. This not only means that the marketer has poorly allocated the resources and runs the risk of underachieving the target KPIs but also antagonize the user experience which could result in churn or uninstalls.

CleverTap is a leading Customer Lifecycle Management and Engagement Platform which help apps retain their users for life. The solutions that we develop have to be best-in class, generic (usable by any app) and highly actionable. This talk will discuss our approach to solve 2 keys issues faced by marketers:

  1. Identify that elusive segment that gives the maximum ROI based on pre-defined goal within a pre- defined time
  2. Hyper personalized messages that resonate with their users resulting in increased conversions

The key takeaway for the audience is the use of temporal user behavior to create:

  1. Dynamic User Clusters
  2. Recommender Engine
 
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Outline/Structure of the Talk

  • Brief about CleverTap
  • Current State of the Industry
  • Challenges faced by Marketers on Segmentation
  • CleverTap’s solution for Intelligent Segmentation with Machine Learning
  • Case studies showing the real impact of CleverTap’s solution
  • Challenges faced by Marketers on Campaign Content
  • CleverTap’s solution to Automating Campaign Content with Recommender Engine
  • Case studies showing the real impact of CleverTap’s Recommender Engine

Learning Outcome

Application of Tree-based models and NLP in Clustering and Recommendation Engine

Target Audience

Machine Learning enthusiasts eager to solve business problems

Prerequisites for Attendees

Basic Machine Learning

schedule Submitted 2 months ago

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