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Analytical Arm In Your Growth Journey

Analytic Consulting in different Verticals

We have expertise and provide analytics consulting work across all important different verticals like Retail, Telecom , Healthcare, Human Resources, Insurance , Automative, Education and Energy sectors.

Analytic Consulting in different Horizontals

We also provide consulting horizontally in the areas of Survey data Analytics, Market and Competitive intelligence, Social media analysis, Preventive maintenance, CAPA Analysis, Supply Chain Analytics, Churn Analysis, Warranty Analytics and CRM Analytics.

Technical competency

We have extensive technical knowledge in Business Intelligence, Statistics modelling , Data mining, Predictive & Machine learning, Text Mining, Big data, Sentimental Analysis and Visualization. We can work on both structured and unstructured data.

Product competency

We have in depth product knowledge in R, SAS, SPSS, Excel ,Tablaeu, SAP Business Objects,and Qlikview and other open source tools.

Customer behavior

Response, churn, product up-sell and cross-sell, best marketing creative, days to next purchase, days to next visit.


Fraud or suspicion of fraud, debt repayment period, debt repayment amount, insurance claim repayment likelihood, claim amount of repayment.


We can help in CRM analytics like Value-Based Segmentation, Behavioral Segmentation and Propensity Score-Based Segmentation. Also by analyzing product complaints , buying patterns predicts what customers will buy and when proper recommendations for products can be pitched, proper promotions can be planned and what kind of campaigns will be effective.

Churn Analysis

Customer churn is a huge area of research. Identifying the characteristics of customers most likely to leave and taking steps to stop it improves the bottom line by reducing the absolute need to acquire new customers just to maintain revenue.

Survey Analytics

We can help in doing advanced analytics  on online surveys, mobile data collection, primary & secondary research data .


We can help in brand management , Instore analytics, by monitoring sales performance, buying patterns and time spent across the different channel by customers and POS data. Also help in identifying and recommend new promotional products thereby increase in sales & revenue of retail chains. Also build longevity to customer relationships. 

Human Resources

We use Analytics to help companies retain employees and reduce turnover rate with reasonable cost. In short we can do Attrition Forecasting Predicting Retention modelling (track and analyze critical skills and predict which skils will be lost and when by predicting turnover) and Attrition segmentation ,talent forecasting and voice of employee analysis. 


We can help companies retain churning customers and improve product cross-sales through data mining. And also provide end-to-end visibility to the improvement of customer relationships and brand management by analyzing the call center data. And also understand why particular customers churn. As it is always costs a great deal more to win new customers than it does to retain current ones.


Today there are multiple channels through which education is being catered. We can analyze past trends across the different channels and combine with demography and discover reasons for the students dropping and likelihood of continuing their courses .

Predictive maintenance

Using Analytics we can find patterns and forecast prior to the actual problem or failure of the component rather than reacting after the failure. Predictive analytics looks at the history of machine failures and compares those instances to sensor data the machine is giving off to spot patterns before the breakdown This will help in proper planning and continuity of the service and reduce unnecessary cost escalations in maintenance. And rather move organizations from preventive maintenance to more predictive maintenance mode.

Health care

Large amounts of heterogeneous medical data have become available in various healthcare organizations (payers, providers, pharmaceuticals). Those data could be an enabling resource for deriving insights for improving care delivery and reducing waste. Also manage inventory doctors schedule planning.