Ugam Solutions’ Marketing Analytics team blends deep analytical skills with the capability to deal with high volume complex data sources, integrate data across platforms, and extract business intelligence using-high end data mining tools and techniques. This enables clients to take better informed decisions at a strategic, tactical, and operational level.


Ugam Solutions provides best in class Marketing Analytics solutions to global clients across diverse industries that include Banking, Consumer Finance, Retail, Telecommunication, Information Technology, and Contact Centers. Our solutions span across the customer life cycle, enabling our clients to get a better understanding of their customers.


We use a combination of modeling techniques such as, Statistical modeling, Operation Research, Mathematical modeling along with Advanced Data Mining methods, to provide top-notch decision support to our clients. Our talent pool has expertise in varied analytics tools like SAS, SPSS, STATA, CART, CHAID (Knowledge Seeker), MARS, Treenet, Minitab, Neuralware (Neural Networks tool), and many more.


By leveraging the skills of our domain and technical experts, our clients can solve complex business problems such as:



Customer Acquisition
Using Logistic regression/ CART analysis, we can help contact centers / telemarketing companies compute the likelihood of converting a prospective lead into a customer. With this information in hand, companies can focus their attention on those leads who display a higher possibility of transitioning into customers. This significantly increases the contact ratio and the conversion ratio of telemarketing companies.




Services Bundling in the IT Industry
In the IT industry, quite often the purchase of one product / service leads to the purchase of another product / service which is complimentary or supplementary to the original product / service purchased. We use segmentation analysis and homogeneity analysis to help identify such product bundles which would be of interest to the customer.




Lifetime Time Value (LTV) analysis for Credit Cards
It has been established that high spend and high balance accounts do not necessarily ensure high profitability. Rather than build on the traditional ‘balance’ and ‘spend’ models, we build the ‘life time value’ model that targets profitable customers. With this model companies can put together a strong service differentiation strategy for rewarding premium customers and they can also create and use cross sell opportunities.




Pricing Analysis for Automobile, Consumer Appliances, and Credit Card companies
Using OLS regression and segmentation analysis, we can help you to determine the right price for your product/service by optimizing the price elasticity of a given customer segment.




Customer Churn
Using advanced statistical techniques like logistic regression and segmentation, we can help groups like cellular phone service providers to identify ‘high risk’ customers, i.e. those who display signs of discontinuing their current subscription. Armed with this functional data, companies can take the necessary preventive and preemptive steps.




Customer Attrition
Using Time-series forecasting and logistic regression, we can help companies pin-point trends like ‘soft attrition’. This is of immense benefit to credit card companies as it helps them identify customers with a higher propensity to significantly slow down the spending on their credit cards in the months to come. As ‘soft attrition’ is usually a precursor of actual attrition, companies can make timely use of this information and even create a marketing campaign targeted at retaining these specific groups.




Credit Risk Evaluation
By conducting regression analysis/ segmentation analysis, we can help Financial Services companies build customer score cards to identify the high credit risk customers. This can help prevent and reduce the number of bad loans and significantly improve the company’s profitability.




Bad Debt Collection
Using clustering/ regression analysis, we can help customers such as Commercial Equipment leasing companies identify the accounts that show a higher propensity for repaying dues. This insight helps them better organize their collection efforts by giving priority to easy accounts over the more difficult ones.