How Marketing Can Use Big Data To Win Back Users




  • How do you win back lost customers? Columnist Josh Todd reveals some key strategies for using your data to engage with users and invest in the right customer.




    ss-people-dataWhen marketers talk about “win back” strategies, they are usually referring to campaigns created to get churned customers to re-engage. However, this traditional view consistently delivers minimal win backs because the programs are executed after the battle has already been lost.


    Most often in these situations marketers are desperate, and the effort is often accompanied by a deep discount or other incentive that tends to bring back the least profitable and highest-maintenance customers.


    In the end, winning back lost customers is a losing strategy; instead, marketers need to win back customers before they churn.


    So, how can you keep more customers and avoid having to win them back? It’s about thoughtfully engaging with users in the moment during every interaction.


    That may sound obvious…and daunting. But what it really comes down to is being smart about your customer data.


    Here are four sure-fire ways to make sure you are focused on the right areas:


    Embrace The Customer Life Cycle

    If you’re paying attention, you’ll see that your customers leave clear signs about where they are in their journey. It’s up to you to listen and be ready to act.


    One way to do this is to use a customer life-cycle approach. But don’t worry — applying one to your business doesn’t have to be complex.


    First, lay out the stages of the life cycle for your business. (You can get as granular as you want.) An example: suspect, to prospect, to lead, to customer (early, engaged, at risk), to, finally, churned customer.


    Next you need to define exactly what it means to be in each state. For example, the early customer stage may be defined as a paying consumer who is within the first 15 days of his or her first purchase. Whereas an engaged customer may be a paying consumer who has made at least three purchases or visited the app or site a minimum of 10 times over more than 30 days.


    The most important thing to understand is that if you’re doing it right, a customer can only be in one life-cycle stage at any given time. This is critical to making the life cycle actionable.


    Lean On Your Data

    Now that you’ve identified discrete customer stages, it’s important to make sure that each of those stages goes beyond just the “official status” within your company’s system of record. You need to have behaviors that can be measured and used to create segments.


    Think hard about the difference between an engaged customer and an at-risk customer. This is where your data modeling comes in.


    Look at the behaviors and profiles of your customers who have churned — how are they materially different than your most engaged customers? The answers you uncover here will become the most important aspect of making the life cycle actionable.


    Identify who is on the “happy” path — aka your aspirational customer behavior that will shape all of your campaign creation efforts — and obsess over it. Tight definitions, plus measurable behavior, will give you the ability to segment and know what behavior you want your at-risk customers to engage in.


    Identify Your Customer’s Life-Time Value (LTV)

    Do you know a good customer from a bad one? How about those who make you the most money versus those who actually cost you dollars and resources? Getting to an average LTV is the first step, but including some of the costs associated with serving your customers will put you in a much stronger position.


    For example, some customers may be heavy consumers of your free tier of support or may require you to process a disproportionate amount of data. Incorporating these costs will help improve your segmentation and be sure you are focused on keeping the right customers.


    You may choose to create additional life-cycle stages to accommodate the less profitable users and create campaigns that get them to reduce their expensive behavior, or you might exclude them from your engagement campaigns.


    Get The Full Picture

    Your best intentions may be driving your customers away. Avoid relying on campaign metrics to measure success. Instead, focus on the entire picture.


    Take this situation as an example: You run an email campaign that drives a strong increase in immediate purchases, so you celebrate, high-five each other, and get ready to keep pushing the tactic. While that’s great, in reality, the campaign actually increased unsubscribes and had a negative impact on future purchases for the group who received the email.


    That is what happens when you optimize in the moment. You miss the entire picture of your users and their relationship with your brand and run the risk of sacrificing the future.


    Instead, you should take the entire life of the customer into account and measure and track beyond the immediate impact. This can be accomplished today if you keep a control group who are not exposed to the message — and then periodically measure how their value compares with the test group, a critical action when you focus on the long game of retention and engagement.


    Conclusion

    As we move further into the age of data-driven marketing, we will see less “win back” campaigns and more engagement campaigns that focus on driving real LTV. Using the customer journey or life-cycle framework isn’t new, but what is new is the sophistication that can be applied to implementing it because of all the data we have surrounding our customers.


    Put these thoughts to work for your business and you will increasingly be investing that next dollar in the right customer — investing where it has the biggest positive impact.


     



    Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.








    (Some images used under license from Shutterstock.com.)


     


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