Machine Learning Models Reduce Customer Churn at Socialbakers

Reduced

Monthly churn rate

Improved

Customer retention rate

The Challenge

Customer Churn Was Eroding Recurring Revenue with No Early Warning System in Place

Socialbakers needed to minimise customer churn through predictive analytics and identify the most effective retention offers for at-risk customers before they cancelled their subscriptions.

Our Approach

ML Models Predict Which Customers Will Churn Next Month, Enabling Proactive Intervention

Blindspot developed multiple machine learning models designed to capture and predict customer churn patterns on a monthly horizon, enabling the client to proactively address retention risks with targeted interventions and personalised offers.

Results

Churn Rate Measurably Reduced Through Timely, Targeted Retention Strategies

Customer churn was measurably reduced and the overall retention rate improved. The models enabled the Socialbakers team to identify at-risk customers in advance and deploy the right retention strategy at the right time.

"Blindspot supported us on a machine learning project that helped improve customer retention rate and reduce churn."

Yuval Ben-Itzak, CEO, Socialbakers

Generative AI Gives Mountain Gorillas a Voice in Global Conservation

Blindspot and AWS helped Tehanu deploy Claude 3.5 Sonnet via Amazon Bedrock to process gorilla behavioural data — identifying species-specific preferences at expert accuracy and enabling the first-ever digital financial transactions conducted by a non-human species.

Expert Accuracy on gorilla preferences

Integrating Generative AI Helps Ataccama Become a Leader in the 2024 Gartner® Magic Quadrant™

Over nine months, Blindspot integrated LLM technology into Ataccama's data management platform — building a natural language interface for non-technical users and an AI co-pilot for bulk data quality rules — contributing to Ataccama's Gartner Magic Quadrant leadership position.

Gartner Magic Quadrant Leader 2024

Criminal Behavior Model Powers Effective Patrolling Routes and Strategies

Blindspot collected crime and demographic data to build a machine learning model of criminal behavior, integrated directly into Avata's intelligence-led policing platform to help law enforcement allocate resources more effectively.

Optimized Patrol route scheduling

Next Steps

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