Now, this isn’t a blog post that’s going to explain what customer retention is and the importance of it. You already know this, and if you don’t, there are about a million resources online that will explain exactly that. No. This is different. This is a love story between customer retention and your predictive insights.
A few important bullet points to get us aligned before we begin this modern rendition of Romeo and Juliet.
- Not all customers are created equal. Obviously. Some are more profitable than others, some less, you get it
- You can divide your customers into 3 groups:
- Those who only purchase once
- Those who purchase a few times
- And those who absolutely love you and purchase repeatedly. Like I do on Asos. In fact, it is estimated that 80 percent of your future profits will come from just 20 percent of your existing customers.
Retention is more than just retaining your most valuable customers; it’s also about acquiring more customers with the same characteristics and tendencies as your most profitable segment.
It’s about leveraging your data in a way that will let you understand which channels work best to acquire those customers and the kind of tactics and strategies you need to implement in order to get customers to make not just one purchase, but 3, 4, 5, and more!
You had me at hello
You sure did. You knew exactly what you were doing when you targeted me with special promotions and offerings that would peak my interest and encourage me to be an active shopper. You knew what to say to bring me to your store and turn me from a browser to a customer. And you know all this because you leveraged your historical customer data to understand my potential value and what motivates me to buy. You made data-driven decisions to ensure your efforts were not just random attempts at catching my heart.
And how exactly did you do all this?
- Channel Analysis: What you did was understand where your valuable customers came from in the first place because you knew that it was most likely you would find your best prospects in those same channels. And by understanding this, you could reduce your A/B testing budget, increase conversions, and lower your CAC.
- Behavioral Incentives: You segmented your valuable customers to understand which incentives, messaging, and offering worked best in pushing them to make a purchase. Based on the behavioral characteristics of each segment, you knew how to make more personalized and targeted offers to increase conversion rates with new prospects and potential customers.
- TouchPoints: You worked so hard to bring me along the customer journey, wouldn’t it be a shame if I just fell out in the middle? But you knew this. That’s why you used historical data to understand where your vulnerabilities were in the customer journey and optimize my path to purchase.
- Predictive Models: I didn’t really know if to start or end with this one, but it’s definitely the most important step. You see, here is where you took all your customers’ behavioral data to build predictive models; these predictive models told you the exact type of customers to look for, the customers that will bring you the most value. Once you knew what you were searching for, you focused your efforts on bringing those people in.
You always have a second chance to make a first impression
You want your customers to make a second purchase …then a third, fourth, fifth, and more, right? But did you know that 68% of your customers will never actually make a second purchase? That’s sad. But the good news is there is something you can do about it; actually, several things.
- Uncover your window of opportunity: This is super cool. So listen, you can actually spot patterns to understand when the optimal time for remarketing is, that is to say when to remarket to your customer to encourage a second purchase. To do this you take your customer’s historical purchasing data to understand the time frame it took for repeat customers to make their second purchase. You also understand the dropout rates and the point of dropout as discussed in Touch Points in the previous section. During that optimal window between purchases- that is when you should be remarketing.
- Give them what they want…or at least what they think they want: This is similar to the Behavioral Incentives section up top. However, this is truly about taking that first purchase and integrating it with not just customer data but also regional data, weather data, and more. Think about it; you could say that people who bought sweater X have a tendency to buy socks Y. Or you could segment the group of people who bought sweater X, understand what region they are in, understand the weather conditions, understand the fashion style, and make sure that your second purchase promotion is truly fit for each customer’s specific needs.
- Change in lightning speed: In short, do everything fast, iterate fast, and test everything you do. Gather as much data as you can to not only understand what works, but what does not work as well in order to ensure you don’t repeat past failures and only build off what you know works.
- Build campaigns that work: Imagine knowing how to optimize your campaigns before they go live. With past advertising and campaign data you can actually discover the best parameters for your campaigns. Know what the duration of the campaign should be, what the best performing copy is, how to segment your audience, the promotion or offering, etc. You know how much money you would save on A/B testing? Let alone the increase in conversions and a happy boss.
To sum it up
Customer retention is more than just retention. And you can’t initiate any successful customer retention strategies without data. Data! Data is your friend, your family, your true love. Without data you can’t see the future, and if you can’t see the future you might not end up where you need to go.
And as Doc Brown once said: “Your future is whatever you make it, so make it a good one.”