This excerpt is from an interview conducted by Lars Fiedler and Jan Middelhoff, originally published in Volume 1 of McKinsey’s “Perspectives on Personalization at Scale.”
Liad Agmon is the CEO of Dynamic Yield. Kelsey Robinson is a partner in McKinsey & Company’s San Francisco office and a leader of the Personalization Practice.
Why is personalization such a hot topic these days?
Liad: We live in the age of individual expression, and we expect, as consumers, to be addressed as individuals. Why should companies send us mass messages when they can tailor them to actual consumer behavior? Recent advances in technology have made it possible for companies to move their communications approach away from single standardized messages toward an engagement that delivers the content most relevant to each consumer in whatever context they find themselves at any given time.
Research has shown that individualized communication increases customer satisfaction, engagement, and—eventually—lifetime value. Hence, CMOs across the globe are trying to master personalization at scale. Under increasing pressure to reduce acquisition costs, they’ve shifted their focus to maximizing the potential of existing customers, and for me, personalization is one of the most cost-effective and ROI-driving strategies to do that.
A guide on the complexities of personalization and what it takes to drive growth using advanced tech, people, and processes.
Kelsey: We’ve asked consumers what’s most important in how companies interact with them, and two answers come out on top. One is convenience. The other is personalization. So consumers are actually asking for it. And that has big implications for how companies communicate. In the retail sector as an example, this might mean asking, “What products do I show consumers?” But basically, at every point of interaction along a customer’s journey, it’s about relevancy for the individual vs. mass marketing or messaging to all. And now, unlike past eras in marketing, we have technology and data to fuel this personalized approach.
How does Personalization at Scale affect the bottom line?
Liad: The real impact of personalization is an increase in revenue and in customer lifetime value, which makes it possible for companies to invest their resources better and farther.
It’s not atypical to see a 15-percent increase in revenue per user by deploying a set of personalization tactics that work well.
However, a lot of the impact is dependent on the rigor with which companies implement personalization and make it part of their DNA.
Kelsey: Personalization is a key driver of top-line growth. It is a core driver of cultivating better relationships with customers and driving both incremental revenue from those customers today and incremental loyalty from them over time as well. There are also moments and occasions where personalization can assist on the cost side as well. If a service rep has a deep understanding of a customer’s preferences, then that employee should be able to spend less time resolving the customer’s issue more quickly, time that can be used to identify and propose the right-up or cross-sell opportunity.
What are the key considerations or requirements in launching Personalization at Scale?
Kelsey: It takes two things to put a strong personalization operating model in place. One is commitment. The most successful companies have leaders who make personalization a really high priority and encourage their teams to go ahead and try, and fail, and succeed.
Getting started is the second major challenge. We have this concept of an agile war room, which is (to simplify) putting a marketer, a technologist, a creative developer, and a data scientist together in one room. They just start to test one or two things.
It’s great to have a source of inspiration—competitors or adjacent-industry leaders who have already built successful personalization operating models.
It’s also really important to have at least one or two people who have been in a war room before and can show the rest of the team how it works. They’re the ones who are up at the wall asking, “What do we need to do to actually get this out the door?” They role-model how we run stand- up meetings, which begin each day with a focus on what needs to be accomplished. In the early stages of any war room, they are the leaders.
Liad: I agree with Kelsey on the issue of commitment. Executive buy-in is a must! Personalization requires organizations to make some fundamental changes, and they can’t happen without support at the top. One approach is to create a “personalization steering committee” to initiate and coordinate customer communication across all channels and consumer touch points.
Companies also need to get a realistic picture of their current organizational capabilities before embarking on a personalization project.
Can they connect their various data silos into a coherent customer view? Can their IT architectures support personalization? I am always amazed to see how easily it can be done in the end, if it’s done right. One of the biggest urban myths is that you need lengthy and costly preparation to start personalization. Start with customer transaction data, add a few additional data points on customer behavior, and give it a try.
What’s the role of data and analytics in driving better personalization performance?
Kelsey: Analytics plays a few important roles in personalization. First, it shapes the pilots a company will actually run, and the personalization tactics that will be tried. Say, for example, that you know [from the data you already have] that valuable customers make a second purchase within two weeks. That’s a great analytical insight to use as the starting point for a test to see whether you can get more customers to make a second purchase within two weeks. Analytics enters the process again, to measure what worked and what didn’t when you actually launch those tests. We always use a test group and a control group to make sure the personalized treatment a customer receives actually drives different behavior and produces more value for the company. When a test doesn’t work, we can still use data and analytics to figure out things like, “Did it work for a subsegment of customers? Who did it work for? Who did it not work for?” That might shape a brand-new test. So analytics becomes a very iterative, continual process in personalization.
For the full interview and answers to questions about the next frontier of personalization, download the whole eBook for free.