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A one-to-one approach to managing customer lifetime value

Matthew Nolan, Log in to subscribe to the Blog

If you’re an exec with revenue-generation responsibilities, you’re getting massive top-down pressure to improve customer experiences, do more with less budget, and create value for the organization – and it’s frustrating. Every internal conversation is about poor experiences, broken journeys, or fatigued customers. Leadership is buzzing about personalization, relevance, and putting the customer first. Everyone, everywhere in the company is hyper-aware of your NPS and CSAT scores, response rates, and depth of engagement.

It’s pretty obvious you’re in a no-win situation. Underneath it all, the legacy technology and approaches marketers used were never designed to “put the customer first” – they were actually designed the complete opposite way.

Your tech evolved out of the marketing automation boom of the 1990s – when “experience” meant simplifying things for the business user, NOT the customer. Segmentation waterfalls and campaign tools, audience managers, journey builders, and web analytics software – it was all designed to make it easier to target and engage customers en masse – to PUSH them stuff all at once in big batches, fast. Your tech is designed to talk about the things you, as a business, want to sell. Not what that customer, as an individual, actually wants to hear about… which requires a much more sophisticated level of intelligence and timing.

Doing anything at a 1-to-1 level, especially at a scale of millions feels impossible. So we let ourselves off the hook and think “that’s just never going to happen,” because we know what things are really like at our companies behind the scenes. Silos of data, channels, functions, and people. Huge batch campaigns that take weeks or months to launch. Many organizations are still delivering engagement through a marketing automation lens versus a self-optimizing lens that is enabled by AI and real-time data inputs.

It takes a super-human effort just to get communications out the door and prove out value… much less make them “customer-centric.”

But imagine if you could. Imagine if you had a Customer Decision Hub to make smart decisions in real-time across the organization every time you touched a customer, on any channel. If you could take all your data and analytics, add a healthy dose of real-time decisioning, operationalize it in a way that balanced customer versus business needs, allowing you to really influence the overall experience.

If you had such a thing, WOW…. nice! You could have a monstrously large impact on fundamental business challenges, like these:

  • New Customer Acquisition: Before a prospect ever identified themselves, you could start knowing them – every action, click-through, page view, and browsing behavior would fuel your machine-learning models, adding intelligence, and telling you more about that individual’s unique propensities to purchase. You’d present more relevant offers and messages – giving them a simpler and much more compelling path to conversion. And once they made their first purchase, all that intelligence would simply carry over into the rest of your relationship. The cost per customer acquisition would plummet, and you could re-allocate that budget towards new platforms and eyeballs, and test in places you’ve never been able to before.

  • Upsell and Cross-Sell: All of the data you had about a customer (first-party, third-party, and everything in between) could be operationalized for analytics. You could model a customer’s propensity to purchase every product, not just the big ones, or the categories. You could identify the offers and messages that really stimulated demand, and the channels in which they were most effective. And most importantly, you could monitor propensities for each individual customer, in the moment – as they changed. When one spiked, you’d know the customer was in market and exactly what to show them. You could deliver a perfectly timed offer during the customer’s exact moment of need. You wouldn’t have to wait for a campaign, as you’d trigger outreach in real-time – when that customer was engaged and actively listening. Your response and conversion rates would skyrocket.

  • Customer Retention: You could monitor each individual customer’s likelihood to churn, and when it started trending the wrong way, you’d take action pro-actively, before the problem went nuclear. You wouldn’t have to rely on static offers to “save” angry customers – instead, you’d know exactly the things they needed, which offers were likely to keep them – and you could deliver those to agents while they were engaging with the customer, in real-time. You could make those agents heroes instead of villains. And best of all, you could analyze each customer’s potential, and invest most heavily in those with high lifetime value – which would protect your most precious, profitable relationships, without lowering your profit margins.

  • Reducing Cost-To-Serve: Overall you’d understand much more about which channels and experiences each individual preferred, and how the customer wants to interact with you. You could anticipate who needs more incentive, who needs less, who prefers to interact online versus a call-center…. With this kind of knowledge, you could begin right-channeling your customer towards cost-effective experiences, while still giving them exactly what they needed to stay happy. This would not only increase their satisfaction levels, but it would decrease your labor and marketing investment – and the overall cost to serve each individual customer.

If you had a Customer Decision Hub, your organization could be much more effective at solving these kinds of problems, and many more. So, the real question is… why don’t you? What’s stopping you?

This kind of tech isn’t science fiction... It’s very real, available, and cost-effective – and companies are putting it into play millions of times per day, billions of times every year. They’re using it to completely re-structure how they think about customers and structure each interaction. They’re changing everything about how marketing and engagement works, today – and in the process, re-architecting their customer relationships for the better.

Learn More:


Industry: Financial Services Product Area: Customer Decision Hub Topic: AI and Decisioning Topic: Personalized Customer Experiences

About the Author

Matthew Nolan, senior director of product marketing and decision sciences at Pega, helps organizations orchestrate customer journeys, personalize engagement, and maximize customer lifetime value with AI and next-best-action intelligence. He is also regular keynote speaker who shares his professional insights on nearly two decades of marketing technology experience.

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