The Keys to Customer Acquisition and Retention
Through a Combination of Data & Analytics, Insights and Brand
Martin Lenoir has been leading marketing teams to high performance and growth for over 20 years and has driven highly successful direct-to-consumer marketing campaigns for blue-chip organizations like DISH Network, New York Life, Kaiser Permanente, and Capital One.
During his time as CMO of AAG, Martin was responsible for the enterprise-wide marketing function, including call center operations, digital marketing, marketing operations, lead generation, financials, and analytics. Today, he serves as a marketing and strategy advisor to Sognare, a Brazilian home equity startup, and a consultant to marketing agencies who benefit from his direct-to-consumer experience in telecommunications, financial services, and senior marketing spaces.
The Continuum recently spoke with Martin about the art of customer retention, the pros and cons of working with brand partners who may be more famous than the brand itself and key lessons for leveraging consumers insights and data & analytics.
You studied to be an engineer; did you ever envision a long career in marketing?
I was never going to be a marketer. My background was in engineering, and I was at a start-up at the height of the internet bubble. Companies were beginning to understand data in a new way. Capital One was having huge success with their data-driven approach in the credit card space and investing heavily in its internet capabilities. They offered me a job on the internet team, cross-selling to internet customers and visitors. That quickly expanded to cross-selling at all of Capital One’s touchpoints, including statements, inbound calls, web, and direct mail. We were very focused on “test and learn,” but I didn't realize I was in marketing.
I think the clarity that this was my career came when I left Capital One after eight years and had to put a name to my experience. I realized that I was a data-driven consumer acquisition and retention marketer and a cross-selling guy.
Credit card companies have an enormous amount of data on their customers; how do you tap into that for cross-selling?
Financial services have a lot of great examples of cross-selling because, as you said, they have so much data on each consumer. With Capital One, customers start with a credit card because that’s the main product, and then we used the credit card interactions to sell different products like a personal loan or auto financing. The old-school example is an offer on the credit card statement, but even then, it’s not that simple.
We could make you five different offers, but we need to figure out which one you’re most likely to take. We had tons of data on millions of cardholders, so it was a matter of statistical modeling on probabilities. The math isn’t perfect, but it’s pretty good in predicting which one you’re most likely to agree to.
You also mentioned customer retention; how does data help you do that?
When I left Capital One, I went to Kaiser Permanente. For those not familiar with Kaiser Permanente, it’s an integrated healthcare provider—essentially a provider group and an insurer. Like credit card companies, insurers know a lot about their consumers. The data taught us that two behaviors were key to retention: picking your primary care physician and enrolling in the patient portal. Once we had that consumer insight, we could start marketing the benefits to members with an ROI mindset.
The original insight was a correlation—we knew that people who did these things stayed longer—but we couldn’t prove causation. It was possible that people who signed up for the portal, for example, were more invested in their health in other ways and less likely to leave anyhow. Our challenge was to make it about causation—we needed to make sure that signing up for the portal because they saw one of our campaigns would cause someone to stick around longer.
In this case, we had to think like a traditional marketer and focus on the value proposition. It makes sense; if you use the portal, you get more out of your interactions with Kaiser Permanente, and if you get more out of your interactions, you’re going to feel better about the organization and your premiums, and there’s a good chance you’ll stick around longer. This journey showed the importance of leveraging data and combining it with consumer insights and thinking – you win when you add value to the consumer.
“Ultimately the holy grail of AI in marketing will be when the tools can drive the consumer insights and act on them autonomously.”
You’ve been talking a lot about data-driven marketing and tapping into demand, but how does the traditional branding fit in when you’re working in the healthcare space?
The Kaiser Permanente brand really stood for healthy communities and healthy people. It’s a not-for-profit organization. It invests in communities by doing things like subsidizing farmer’s markets in their service footprint because part of being healthy is eating healthy.
Kaiser also delivers better health outcomes for people with chronic diseases like heart disease or diabetes because of the data it has—Kaiser knows whether you’re taking your medicine or have an appointment for follow-up care. The data can help us know when and how to reach out to you, but the brand side is important too. It’s about building awareness with consumers through traditional advertising that—billboards, TV, and video—about how Kaiser Permanente can help you thrive. All of the marketing we did was built out around that concept and brand story.
After Kaiser, you went to New York Life and were specifically focusing on a product partnership with AARP. What was it like to work with such a well-known partner?
This role was so interesting because it was definitely data-driven; everything about life insurance is data-driven, but there was also a huge aspect of brand awareness and in many ways the AARP brand led the way. Honestly, it was a double-edged sword. AARP is a terrific organization; it does great advocacy work and is highly trusted by consumers, but in a partnership, there are a lot of needs to balance. This meant thinking about two sets of parameters when looking at what these brands stand for, how they show up, and their tone. And, for New York Life, there was the additional challenge of not getting lost under the brand power of AARP.
“This journey showed the importance of leveraging data and combining it with consumer insights and thinking – you win when you add value to the consumer.”
Before we wrap up, what do you see as exciting in data-driven marketing?
I hate to say AI because that’s what everyone is talking about, but I’m not talking about generative AI that makes things. I’m excited about automated tools that can help you improve your campaign and performance. Too many marketers are unable to test and learn at scale, which is a wasted opportunity. The tools can help. You are still feeding in the creative and content, but the tools are figuring out where to put those assets, often in real-time. Today this is also a great force multiplier, freeing up marketing staff to do other things. Ultimately the holy grail of AI in marketing will be when the tools can drive the consumer insights and act on them autonomously. Since marketing is increasingly digital and digital marketing is very data-rich, these are powerful developments for all marketing organizations.
August 2, 2023
