GSTAT software solutions enable B2C companies (Banks, Telecom companies and Retailers) to maximize their customers' value, by identifying the right Next Best Offers/Actions and the optimal retention rewards for each customer, which will maximize each customer's revenues.
GSTAT's customers use GSTAT software for deploying projects, such as :
- Telecom – Recommending high churn risk customers on the optimal retention reward which will maximize customers' ARPU.
- Retail – Recommending personalized promotions/coupons for loyalty program members, out of thousands of possible products sold in the chain, while optimizing budget, suppliers’ and customers' constraints.
- Finance – Recommending the right financial offers in outbound and inbound for customers based on statistical scores for all products and services sold by the organization, generated automatically by GSTAT software.
"We are honored to be part of the EMC Greenplum Catalytics Partner Network and are proud to present the next step in the evolution of customer analytics: End-to-end business solutions for Next Best Action/Offer and retention optimization, based on fully automatic data management and automatic statistical modeling processes. Partnering with EMC Greenplum enables us to leverage Greenplum's high performance and effective data management capabilities for providing automatic data-mining-based decisioning solutions to small organizations as well as large scale organizations with tens of millions of customers and thousands of potential offers required to be optimally matched".
Shamir Segal, Managing Director, GSOFT, a GSTAT Group Company
GSTAT software solutions are based on automatic data management and data mining processes, which marketers can operate in minutes, instead of weeks to months, using classic data-mining tools available in the market, for developing and deploying up to hundreds of cross/up-sell, churn prediction and retention optimization data-mining models.
Using GSTAT solutions, our customers can:
- Benefit from end-to-end business solutions for Next Best Action and retention optimization, based on automatic data mining processes.
- Reduce the preparation time required for developing and deploying hundreds of cross-sell/churn prediction models for different products and churn events, from months to hours.
- Increase response rates for every targeted campaign by up to 50% as compared to campaigns based on manually developed data mining models, using common data mining environments.
- Execute far more targeted campaigns based upon data mining models for customer retention and increased cross-sales. Use of data mining produces higher response rates and increased revenues compared to the use of standard business rules.
- Dramatically increase the productivity of the analytical team so that it can develop substantially more cross-sell/churn prediction models, using the same analytical resources.
- Use one unified, automatic, data mining environment for all cross/up-sell, churn prediction and retention recommendations, which can easily be integrated into any existing campaign management and real-time interaction tools.