SAS® enables Max New York Life to maximize share of wallet, retain valuable customers
Sales to existing customers include up to 40 percent more premium revenue
In India's recently liberalized life insurance market, fast-growing Max New York Life (MNYL), a joint venture of two leading global businesses, (Max India Limited and New York Life International), has adopted SAS technology to transform its efforts to strengthen customer retention and cross-selling to a tightly segmented customer base. With SAS as the heart of its marketing process, Max New York Life has access to the right data, the right models, and the right execution. As a result, high-margin revenue from cross-selling has tripled.
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Dr. Nagaiyan Karthikeyan, PhD
Head of Business Intelligence & Analytics
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Since its inception in 2000, MNYL has recognized that, even as it continues to grow, the greatest revenue opportunity lies within its current customer base, which was vulnerable to exceptional levels of churn. According to Nagaiyan Karthikeyan, PhD, Head of Business Intelligence and Analytics, there were two major challenges. "First, we wanted to be able to identify our best customers and ensure we take appropriate steps to retain them," he said. "But beyond just keeping them, we want to expand our relationship with them – our share of wallet. These are mutually beneficial aims because, by selling more products and services, we improve the likelihood that the customer will remain with us."
Not just retention – expansion
Achieving these ambitious targets started with one important objective: a centralized repository of customer data. "Getting that single view of the customer meant pulling all of our data into a unified data warehouse," Karthikeyan explained. "We'd then need to give our business users the right analytic tools to make good, strategic decisions. But, from a tactical level, addressing the quality of the data was essential for executing our selling initiatives. Address and contact data in India is notoriously inconsistent, so to make cross-selling feasible, we needed to ensure we knew the correct addresses and phone numbers."
SAS: The heart of the marketing information flow
One of the key advantages that SAS provides is improved speed and precision. "Before, we needed at least three weeks just to build a model," he said. "Now, we can build and run a model in two days. What's more, we're able to target our customer segments much more logically and granularly. We've identified about 25 separate cells, and we see their demographics and previous transaction behaviors. That lets us tailor specific cross-sell offers and script different contact scenarios based on their value, their propensity to buy, their propensity to pay, and their propensity to lapse. Previously, we conducted two broadly targeted campaigns each quarter. Now, with these tightly defined customer segments, clean data, campaign management, and rapid modeling, we're executing 60 separate campaigns a month. That's a level of agility that we directly attribute to SAS."
Through this broad initiative, MNYL has achieved remarkable improvements in retention and cross-selling. Earlier, only 7 percent of revenue came from existing customers. "In the first quarter after implementing SAS, sales to existing customers jumped to more than 20 percent," Karthikeyan said. "Depending on how the macro economy performs, we think we can get that number closer to 25 percent or 30 percent. Our senior management team is very pleased with that performance."
Revealing the business insights
"This has been an ideal solution for Max New York Life, and I would strongly recommend it to other enterprises. If you're in an environment that changes constantly, where the decisions you made three months ago are no longer valid, you need a system that can provide senior management with timely data and insightful analyses. That's what SAS has been able to provide our organization."
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.
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Max New York Life
Need an accurate data warehouse of viable information for use in increasing customer retention and improving cross-selling efforts.
SAS Business Analytics, including SAS Campaign Management, SAS Enterprise Miner and SAS Enterprise Guide.
Using SAS, Max New York Life has increased the number of new sales from existing customers from 7 percent to more than 20 percent and improved the premium revenue by nearly 40 percent with shorter sales cycles. With a favorable economy, the company believes it can generate 25 percent to 30 percent of all new sales from existing customers.
Partners for success
The MNYL implementation was a success in large part because of the added team effort of Mahindra Satyam Limited. The firm is a SAS Global Systems Integration Alliance Partner with extensive SAS expertice in analytics, business intelligence and performance management. Mahindra Satyam’s complementary skills and adherence to agreed upon timelines helped SAS ensure MNYL ‘s successful implementation.
“In the first quarter after implementing SAS, sales to existing customers jumped to more than 20 percent.”
Nagaiyan Karthikeyan, PhD
Head of Business Intelligence and Analytics
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