It’s no secret that it’s much cheaper to retain a customer than get a new one — 5 times cheaper, according to Forbes. The paradigm however seems to be changing: retaining is not enough when there are a lot of easily reachable competitors out there. You need to go one step further: make customers loyal.
If there is something we can attribute to the digital age we live in, it is the convenience it comes with. The speed and ease with which we can do processes today, which up until not very long ago was done on a face-to-face basis, is just outstanding. So, obviously, we all want to digitize as many aspects of our lives as possible.
Changing our behavior so that everything we do is now online leaves a mark, a digital footprint of sorts that compiles who we are and what we are doing.
And he who knows us, has the key to give us what we need. Therefore, the data derived from everything we do online — all the data points we generate by even simply unlocking our devices — are a potential gold mine that businesses are eager to tap on.
Read next: Why Retention Analytics is an Important Parameter in Measuring Customer Success.
The gold mine comprising bytes and code is a source of revenue that no organization wants to (or should) relinquish. Companies know that when they increase their retention of customers by only 5%, they can increase their revenue by at least 25% and up to 75%.
But let’s take a step back: what is customer retention exactly?
According to Salesforce, it “refers to the rate at which customers stay with a business in a given period of time”. For the purposes of product analytics though, retention is a type of engagement analysis that breaks down your users’ session and event behavior, starting from their very first session, and analyzing subsequent ones through time.
Metrics derived from retention analysis are key to analyzing churn rates and, when put into context correctly, enable user loyalty analysis. However, keep in mind that retention is only one of the many approaches you must have to understand the digital customer journey, as many things can influence users’ behaviors or actions in your app: crashes, lagged performance, inefficient UX/UI, interactions with the sales or customer care teams, etc. Therefore, you should always look at retention in context with other analytics.
While retention measures how many of your gained users stick with you through time, churn tracks something equally crucial but quite the opposite: users that stopped doing business with you.
The rates resulting from the calculation of both variables are sometimes confused with one another because basically a low churn rate indicates a higher retention rate and vice versa. But they are not exact opposites of each other. As Indeed notes, “the difference between churn rate and retention rate is that churn rate calculates the percentage of customers a business loses, while retention rate calculates the percentage of customers a business keeps”.
Determining churn, though, as opposed to just tracking retention, gives you a fuller picture of your ability to maintain a healthy growth in your customer base. Plus, churn rates help you calculate user-generated revenue over a period of time.
As noted previously, retention and churn are just two ways to try to make sense of the customer experience by means of digital product analytics and user analytics. But knowing if and when a customer comes to you for the first time, comes back to you for the nth time, and/or eventually never comes back to you is just not enough. Because they could be using any of your competitors’ products or services in parallel. You must ensure that not only are you the first option a customer thinks about when satisfying a need, but the only option.
Loyalty to your brand is what makes or breaks your business in the long run and for that loyalty to be established you need to ensure that everything you do works for and not against an outstanding customer experience.
The customer experience as a unit can be measured as the sum of all the interactions and actions the customer had to do in order to obtain something from you.
Think of it as buying shoes on a retailer’s app: you wanted shoes, so you went to the app, looked for what you needed, paid for it, and eventually received it. But what about the process of downloading and using the app, or the different emails you received from the first login to the one with the sale that made you want to buy the shoes, or the contact with customer service when your package got lost in the mail, or the survey you received to rate the shopping experience?
All those multi-channel, individual experiences are part of the digital customer journey of the user. And since the example above probably feels close to home, you can think of how many things can go wrong in any of those situations and affect how much you would want to interact again with that company.
One thing is certain: only when analyzing the entire digital customer journey will you know what it takes for your users to not only return for more but also to never leave you again. Your organization must see the entire customer journey to determine possible risks that may affect user loyalty, and that means gaining a 360° view over all the points of contact of every single customer.
And organizations that are armed with the correct product analytics tools can streamline the process of getting these insights on their individual customers.
To make sure you don’t get lost in this process and you make a difference in every single customer experience, get a walkthrough of the tools you need or just contact us to answer all your questions.