Our Customer Analytics Platform uses Machine Learning and AI to answer key questions across the customer lifecycle. It helps you optimize acquisition, improve engagement and prevent churn. Thus, helping you maximize revenues while giving your customers a great experience.

Design for Optimisation

  • 360 View of Customer
  • Get a 360 view of your customers and optimize solutions to maximize returns. Map data from sales, operations and support to understand your customer experience journey.

  • Immersive Visual Environment
  • Visualize KPI's and customer journey states in a web-based environment with real time updates and alerts.

Democratize Analytics

  • Empowered Actions
  • Provide insights to buying channels and routes and spend compliance.

  • Actionable Intelligence
  • State of the art analytics engine powering the insights. Reduced ambiguities and substantially improved actions.

Unlock Experience Drivers

  • Identify Causal Factor
  • Identify the factors causing the events. Knowing the causes helps plan the actions with highest ROI. Identify what causes churn, what products cannibalize others, and which groups are most likely to respond to promotions along with many more valuable insights.

  • What-if Simulator
  • Simulate potential actions and effects to ensure minimal false starts. Identify and plan for actions that have the highest chances of success.

We Help Organizations with

Customer Profiling and Segmentation

Identify different customer segments and the factors that impact them. This can help understand and initiate targeted marketing.

Price Optimization

Determine the optimal price and do a sensitivity analysis based on the volume versus customer spend.

Churn Analytics

Determine the probability of churn of key customer segments. Identify the key factors for customer churn.

Promotion Analytics

Insights to optimize the planning, assessment, forecasting, tracking and execution of promotional campaigns.

Customer Lifetime Value Analytics

Identify the value of a customer over the time frame of his relationship and future potential and hence recommend future marketing spends.

Market Basket Analysis

Identify association between products/items, which helps in finding frequent patterns, associations, correlations or casual structures among the set of items/objects in a transactional database.

Demand and supply forecasting

Forecast the demand products as a function of time. Identify seasonal patterns and variations to help prevent under stocking or over stocking.

Cross Sell and Up Sell

Applying data mining techniques to identify the trends, cross-sell/up-sell opportunities and customer behavior diagnosis.

In the Domains of

  • Retail
  • Banking
  • Insurance
  • Travel & Hospitality


Subhrajeet Das

Associate Director
Marketing & Sales