Our analytics tools help leading technology, media, and telecom companies to deeply analyze customer churn and improve customer engagement using data-driven methods.

Use cases

insight

Analyze textual, audio, and video data

We build customer analytics solutions that are able to extract useful signals from virtually any source - call transcripts, customer reviews, camera footage, and many more. These signals can be automatically converted into meaningful attributes and tags and then used in downstream models and analytical processes.
insight

Analyze event patterns

Most traditional personalization and customer analytics methods use aggregated customer features losing the valuable information about individual interactions and events. We use state-of-the-art machine learning algorithms that account for individual event in the customer history providing deep insight into behavior driver and improving prediction accuracy.
predictive analytics

Analyze the dynamics of the churn risk

We develop models that not only identify at-risk customers, but estimate how the risk level is likely to evolve in the long run. This helps to determine optimal treatment and intervention time.
prescriptive model

Automatically optimize next best action

We extensively use prescriptive models to determine optimal marketing actions for each customer. These models incorporate a wide range of signals and optimize both customer engagement and value.
Ready to improve your customer engagement?

Our clients

Retail
Hi-tech
Manufacturing
Finance

How our customer analytics platform works

A powerful array of models
We provide a comprehensive array of models that help to analyze, quantify, and predict various aspects of the customer behavior. These models help to detect and prevent churn, complaints, and other customer relationship issues.
Efficient productization
Our solutions are designed for efficient productionzation and integration with marketing and customer support processes. We develop models and services that produce precise and actionable prescriptions rather than complex scores and fragmented pieces of analytics.

How to get started

We provide flexible engagement options to help you build a personalization platform faster. Contact us today to start with a workshop, discovery, or proof of concept.
Workshops

We offer free half-day workshops with our top experts in marketing technology and customer analytics to discuss your customer intelligence strategy, challenges, optimization opportunities, and industry best practices.

POC

If you have already identified a specific use case that can be solved using data science and other customer intelligence technologies, we usually can start with a 4-8 weeks proof-of-concept project to deliver tangible results for your enterprise.

Discovery

If you are in the stage of requirements analysis and strategy development, we can start with a 2-3 weeks discovery phase to identify right use cases for customer intelligence and personalization, design your solution using industry best practices, and build an implementation roadmap.

Learn more

Read more on price and revenue management
Would you like to learn more about economic and algorithmic foundations of customer experience optimization? We published a 500-pages book on enterprise data science that is available for free download, and there is a whole chapter on price and promotion management in it.
Read more on advanced customer intelligence

This report provides an overview of recent advances in customer intelligence by examining 10 industrial case studies. These case studies were selected from the consulting practice of Grid Dynamics and public reports to cover the most important, common, and innovative trends in data science and machine learning methods used in modern customer intelligence and marketing analytics.The report covers the following 4 major areas of active research and industrial adoption:

  • Deep learning models that incorporate a wider range of signals and data, including textual and visual data.
  • Deep learning models that process sequences of events, including User2Vec models.
  • Reinforcement learning models for dynamic and strategic optimization of marketing actions.
  • Econometric and deep learning models that quantify financial and operational risks.

Get in touch

If you have any additional questions, please feel free to reach out to our experts directly

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