Marker.io integration Marker.io integration END

Reducing churn for a European media company

Reducing churn by 30% in 3 months: how a leading media company used AI-powered analytics to reveal thousands of clues that identify which reader was likely to churn, and why.

The Challenge

Sweden’s leading media company’s digital subscription base was stagnating: 14.8% monthly churn nearly overcame its 10-15% monthly growth. 

In their words, they were 'busy dying'. The Chief Editor reached out to SparkBeyond to understand the root causes of the problem, and build a sustainable business model with targeted proactive retention activity.

SparkBeyond helped infuse Dagens Nyheter with artificial intelligence (AI) and methodologies that identified patterns — to a level whereby we can identify within 86% accuracy who will likely churn.

Peter Wolodarski
Chief Editor
Dagens Nyheter

The Approach

SparkBeyond Discovery was embedded into a cross-functional team of business stakeholders and data analysts. The team used the Discovery platform to automatically augment diverse internal datasets (subscription, billing, status) with external data sources (Wikipedia, census).

Within a week, the team identified >200 actionable drivers of churn, which were then featured on a real-time dashboard, empowering the media company with fast iterations to take action every day.

Using data-driven mapping to quantify and select high-potential initiatives, the cross-functional team built a model that accurately predicted 86% of churners.

Drivers of high churn:

  • Subscribers receiving monthly reminders (paper/digital invoice)
  • Subscribers acquired via telemarketing

Drivers of low churn:

  • iPhone & iPad users
  • Subscribers for longer periods (i.e.students)
  • Subscribers with electronic and automated payments

Results

By testing millions of patterns per minute, SparkBeyond Discovery revealed the root causes behind the cohort of customers who churn.

Examples include:

  • Cross-page links in the iPhone app crashed -- leading to disengagement and churn.
  • Monthly invoice reminders led to churn

Peter Wolodarski and his team were able to interpret the root causes and take action with the following initiatives:

  • Create autopay flow
  • Migrate stock to autopay
  • New sales channels
  • Telemarketing optimization
  • Broader payment options
  • Subscription optimization

By employing the above actions, the media company reduced its churn by 30% within a week.

As new root causes emerged over time, the team ran a hackathon every two weeks to interpret emerging patterns and continuously improve its retention activity. This once-struggling media company wasn't busy dying: it was busy growing.

Features

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Business Insights

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Predictive Models

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Micro-Segments

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Features For
External Models

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Business Automation
Rules

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Root-Cause
Analysis

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