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 an web-based environment with real time updates and alerts.

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 more actions.

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

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 or items, which helps in finding frequent patterns, associations, correlations or casual structures among the set of items or 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 and cross-sell or up-sell opportunities and customer behavior diagnosis.