Customer analytics

In today’s highly competitive and every changing business environment, it become extremely important to leverage all the information the company had to understand and serve its customers better to retain their business or increase sale or margin thru cross-sell and up-sell opportunities.

InnoLitica can help you understand your customer using analytics and leverage that information in the following ways

Model customers across all the channels and target them with relevant advertisements/coupons/promotions to increase customer retention and revenue.

Increase customer engagement thru right channel, at right time with the right message

Measure customer sentiment emerging over time and spot cross-sell and up-sell opportunities in real-time using social media analysis and customer survey analysis.

Predict customer churn/loyalty using predictive probability modelling techniques (e.g. logistic regressions, Bayes modelling etc.) and action needed to prevent or reduce customer churn.

Use brand modelling to identify customer preference and relation to particular brands and effect of brand positioning

Maximize customer life time value thru cross-sell and up-sell offers.

Some of the analytics methods we use are

Advanced customer segmentation using latest machine learning techniques such as K-Mean clusters.

Advanced analytics and visualization to view customer interaction with multi-channel and omni-channel analysis.

Automatic feature extraction using advanced data analysis techniques to enrich knowledge about customers.

Trend detection using analytical techniques such as time-series analysis and knowledge discovery techniques.

Customer performance analysis by revenue, cost, profit margin etc.

Customer value measurement and analysis

Customer channel preference and brand preference tracking and analysis

Customer behavior analysis and tracking purchasing trends across demographic and other features.

Customer scoring system development for various business objectives (e.g. customer churn probability, promotion responsiveness etc.)

Customer link analysis to fill and rank marketing pipeline.

Customer analytics