Better Customer Engagement with Artificial Intelligence

Relativity6 assists insurance companies and other enterprise clients in better understanding their customers.

  • Prioritize customers and enterprise accounts by likelihood to purchase.
  • Receive real-time notifications of life or company events.
  • Deploy highly accurate win-back, pre-churn and cross-sell models.
  • Increase Top Line Revenue by up to 5-15% and improve combined ratio savings by 3-5 points.

Relativity6 proprietary algorithms predict when and what your most profitable lapsed customers will re-purchase, with above 80% accuracy.

Relativity6 converts customer transactions into customer relationships.


Identify customers' propensity to repurchase.


Recognize accurate cross-sell and upsell opportunities.


Know when each customer is most likely to return.


Recommend most efficient sales channel per customer.

Behavioral Listening Technology developed at MIT

Relativity6 Artifial Intelligence and Machine Learning Dashboard

Through our research at MIT, Relativity6 concluded that in order to generate the most accurate predictions possible, we needed to tune our algorithms strictly into objective, unbiased data.

This is why we focus our data inputs on internal customer data, specifically the actions and behaviors taken by your customers in the past. Our technology is able to seamlessly ingest both structured and unstructured data sources and filter out only the variables that are directly related to purchasing activity.

We call our proprietary system of algorithms 'behavioral listening algorithms' because we've trained our models to tune into strictly action based variables, leaving subjectivity aside. We have been able to help businesses prioritize and target sales prospects across industries.

Case Studies

Coachup Case Study Logo

Coachup achieves 85% increase in Sessions Booked

Relativity6 worked with Coachup to identify and reactivate customers who hadn't purchased in at least 6 months.

Utilizing Coachup's existing data we ran our automated machine learning algorithmss and pinpointed lapsed customers with at least a 60% probability of repurchasing in September.

Nutraclick Case Study Logo

Nutraclick more than triples their ROI

Nutraclick provides leading health and wellness products. We worked with them to identify and reactivate former customers of their subscription service.

Utilizing our proprietary machine learning algorithms, we were able to identify which inactive customers had the highest probability of subscribing again. These predictions included the most likely product recommendation per customer.

Magellan Jets Case Study Logo

Magellan Jets achieves 90% accuracy to prioritize sales team efforts

We worked with Magellan Jets to identify the buying patterns and signals of lapsed customers willing to re-purchase a jet membership or book a charter flight.

Our predictions achieved above 90% accuracy and our insights helped Magellan's sales team prioritize their efforts and brought significant incremental revenue with minimal effort.

Zipcar Case Study Logo

Zipcar achieves 15% Increase in Revenue per Member

Relativity6 worked with Zipcar to identify which inactive members had the highest probability of making a booking and analyzed the type of vehicle these customers were most likely to request.

Using Relativity6's proprietary machine learning algorithms, we launched a targeted campaign to these members to increase their incentive to make an immediate purchase.

What our customers say

Discover how Relativity6 can partner with you on insurance and reactivate lapsed customers. We are backed by MIT research and development, experience and knowledge.

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