Customer churn sometimes referred to as attrition is a metric that quantifies how many users have uninstalled an app or are no longer actively using it.
It costs 5 times more to acquire new customers than it does to keep existing ones and it will cost you 16 times more to bring a new customer up to the same level as a current one. Yet up to 80% of businesses have no clear strategy to address it. On average, a 5% increase in customer retention rates results in 25% – 95% increase in profits.
According to a study by Gartner, a staggering 80% of a company’s future revenue will come from just 20% of its existing customers. Meanwhile, Marketing Metrics claims that the probability of selling to an existing customer is 60-70%, and only 5-20% to sell to a new prospect.
The norm is such that retention efforts are allocated limited or no resources and thus only a tiny fraction of the subscriber pool is ever contacted.
Causes of customer attrition
- Social influence; A single churning customer might influence other customers to churn as well. Social influence on churn is prevalent in relatively tight knight social environments. Information flow among these groups flows at a rapid pace and is generally considered reliable.
- Bad user experience; Unfortunately many mobile apps have a horrible user experience, difficult to use, one simple example is an app where a user is required to input their date of birth and the user has to scroll all the way from 2019 to 1991.
- No value; A lot of fanfare during product launch can lead to a spike in user signups, however when the users realize the app does not provide them any value, the logical step is to move on
- Storage; Not every mobile user has the latest iphone, limited storage space means something has to give.
- Landscape; The rules for most sports have been around for hundreds of years, in tennis we are looking at 800 give or take. In some cases some people want to apply the rules in sport and bring them to technology which is counter intuitive. The landscape is always changing, the needs are constantly evolving, and the competitors in the marketplace are not sleeping. One needs to know the lay of the land in order to figure out how they can remain relevant in an ever evolving environment.
- Change versus Transformation; Change is when a tadpole becomes a frog, Transformation is when a caterpillar becomes a butterfly. A completely new species which is a clear manifestation of a transformative process. Is your mobile app making a change to the status quo or transformative? This is a question that needs to be asked at the design stage.
Steps for reducing customer churn
- The most effective way to reduce churn is to prevent it from happening in the first place. There’s always a group of at risk users who need to be engaged.
- Improve the user experience by performing user tests
- Offer incentives; these can include discounts, loyalty points. This needs to be done with a lot of care as such programs can eat up your profits. The costs of your retention program should not outweigh the benefits.
- Improve your customer service; Poor customer service has been identified as the leading cause of churn.
- Precision targeting; your retention strategies need to be laser focused and target the right audience otherwise you are writing on water.
- Improve customer engagement; by showing your customers value gained through using your product, you can learn valuable insights especially if you a way to capture feedback.
- Increase the length of your contracts; For subscription based models, providing long term options such as 6 -12 months is likely reduce the attrition rates.
- Setup tests and control groups; Here you can segment customers to send “30% discount on select items” campaign and they send this campaign to only 10,000 of them (“test group”), put aside a randomly-selected 5k customers (“control group”) who will not receive it. Once the campaign is over, you can then analyze the effectiveness of the campaign by comparing the additional revenues generated by the test group with those generated by the control group.
Introducing a churn prediction system
The mainstream approach to churn prediction considers each customer individually. The goal is to predict each customer’s likelihood of churning in the near future, where usually a forecast horizon of a month to three months is analyzed. Key Performance Indicators (KPIs) are generated per customer; these KPIs usually span the customer’s personal characteristics as well as trends in their usage analytics over this period. The information then serves as input to a statistical regression model such as a logistic regression variant that outputs a churn score.
A good churn prediction system should not only pinpoint potential churners successfully, but also provide a forecast in its predictions. Once a potential churner is identified, the retention department can then make contact and, if the customer is established to be a churn risk, mitigation measures can be introduced to retain them. Using a long forecast horizon provides an obvious advantage since the further down the line the customer is from actually making the churn decision, the easier it is to prevent a churn at a lower cost. Incentives can be introduced or improvements can be made to the mobile app to address the user’s needs.
Using a supervised machine learning model a predefined forecast horizon is used with a goal of predicting future churners over that horizon, using data associated with each user. The input includes data on demographics, together with all personal and business information that is logged by the application. In the training phase, labels are provided in the form of a list of churners together with their corresponding churn dates.
A cohort is a group of people who have something in common over a specified period of time. Cohort analysis allows one to dig deeper into groups of like users and model how the business is evolving. For instance, we might see positive trends in Months 1-3, with revenue flattening in Months 4-6, and maybe even a downward trend in subsequent months. In one scenario, a shift in customer mix (perhaps from different sources or markets) could be driving more one-time customers; in another scenario, the downturn could be caused by a diminishing long-term user experience that has run its course.
By extending the cohort analysis, adding new dimensions and measures, the analytics team can understand what cohorts resulted in high LTV (lifetime value) customers. For each possible combination of cohort dimensions, for every possible event date, you can look at: How many devices belong to a specific cohort? How many devices from that cohort were active on that day? What is the retention rate for that cohort? And most importantly what are the characteristics of customers who stick around for a long time?
The key here is to find the inflection point in a customer. When does a customer become a much better customer? What does it take to make that happen?
Gaming companies that produce apps such as Angry birds, Candy Crush, FarmVille, always track Daily Active Users (DAU) and Monthly Active Users (MAU), and data collectors regularly publish rankings of top apps based on these metrics. But DAU and MAU can easily mask more important metrics related to retention and growth. If you can learn where users are dropping off, you might gain the insights you need to build a better gaming experience.
Once you group customers into cohort whether by the most active hour of the day, month they joined, by the day they downloaded, by the operating system they use, you get a much smoother view of your audience, even over very large sets of data. It’s like a cohort is one very big or giant customer, eliminating the noise of all the individuals. Cohort analysis works for any type of business, no matter what type of interactions, giving you the insights you need to execute smarter marketing, to engage with customers effectively, to redesign your product or service, and to focus on your most valuable customers.
Introducing User Centered Design
Setting up “red -routes”; You might ask what are red routes. You might have seen roads with yellow lines painted on them, it means you can’t park on them. In some cities they put red lines on certain routes, By keeping these roads free of obstacles like parked cars, journeys on these routes are completed smoothly and quickly. Motorists aren’t allowed to stop on a red route, even for a minute. Making the mistake of stopping your car on a red route to buy your daily paper and traffic wardens converge on you from nowhere. Software has red routes too. These are the critical tasks that people want to carry out, tasks that need to be completed as smoothly and quickly as possible. Red routes are in essence critical user journeys.
Some tasks are much more important than others. That’s what makes the red route idea mission critical. By focusing on the red routes, we can make sure that less important functions don’t clutter the interface. Those functions are still there, but to use them users need to go to a another part of the interface.
The Agile way of doing things
One might think these approaches are time consuming and can lead to project delays. The reverse is true as with the Agile methodology one is able to us quickly develop new and improved versions of a software application. But this process only works if you know what needs to be improved. By focusing on users and their tasks, everyone on the team knows where to concentrate their efforts.
It’s important to be cognizant of people’s initial opinions. If you want to find out what the problems are with your product, you need to get people to use it and watch them and ask them to complete certain tasks. The key here is not to ask the customer’s opinion of the product. People don’t always know what’s achievable. Henry Ford once said, if I asked people what they want, they would say faster horses.
With a usability test we are looking for three things. First, we measure effectiveness: how many people
manage to complete the red route successfully.
Then, we measure efficiency; how long do people take to complete the tasks.
Why do many companies get these wrong, yet the steps required are seemingly simple?
Most companies think they are customer centric, but when you talk to their customers, very few of them agree. The first secret of user-centered design has four ingredients. You need to focus on users. You need to understand the users’ tasks.You need to do this early. And you need to do the research continuously. Few companies
invest the time and effort in each of these components.
They probably think they know their users. Companies don’t do the research because people in the organisation simply assume that they know what’s best for customers and when they do research, it’s often not the kind of research that’s needed to create better designs. The research often focuses on uncovering demographic factors rather than truly understanding people’s goals and motivations. And when they do it, its usually at the beginning or end of a project.
Focus groups are dead
Many companies perform some kind of research on their products, and they will often ask customers for their opinion in focus groups, But that doesn’t cut it. With interactive products like software, web sites and handheld devices, it’s not what people say that matters. It’s what they do. So activities like focus groups won’t help you find the problems with your product.