You can only reduce your customer attrition rate (a.k.a. your turnover rate or churn rate) with proactive measures. (Not exactly a revelation to you and your marketing team, right?)
No company has ever alleviated attrition (in a meaningful way, at least) by sticking with the status quo with their customer retention marketing and blindly hoping for the best.
The only effective way to prevent customers from “leaving” your sales funnel altogether, maintain recurring revenue (e.g., subscribers, repeat customers), and continually lower your attrition rate over the long term is to maintain good customer relationships.
That means tactful, thoughtful marketing communication — primarily through relevant, personalized and individualized messaging at the most applicable times and places (both online and offline) — must be a top priority for your organization. Always.
Before you put these proven tactics into play for existing customers, though, you must:
- Calculate the attrition rate for all segments of your customer base to better understand the types and traits of the buyers and subscribers who exit your funnel
- Examine your business model and marketing from top to bottom to determine any and all elements that may be contributing to your high attrition rate
- Implement advanced predictive churn models to forecast which customers are likely to “leave” next so your brand can adjust your marketing strategy accordingly
With the right data (and database), you can implement customer attrition rate-reducing best practices that help you diminish churn, bolster retention, and grow your bottom line.
How to calculate your attrition rate — and determine what’s causing customer churn
After you’ve gone through the hard work of acquiring new customers, it’s time to get and keep them engaged to prevent customer attrition and increase your retention rate.
So, how you can preserve business from existing customers — particularly high-value ones?
First and foremost, you need to calculate your company’s customer attrition rate.
There are many ways to calculate customer lifetime value and retention rates. (Not all companies will even agree on the definition of a customer, due to varying business models).
But the below formula — which can be used to calculate monthly and annual attrition rates — is the one widely used by marketing professionals today to identify their churn velocity:
Just as your leadership team regularly tracks the employee attrition rate (i.e., calculate the average number of employees to leave the company over a given period of time), this customer version of the formula is equally as vital to both monitor and address.
(Of course, how you and your marketing team address it will differ considerably than when your CEO tries to ease your employee turnover rate. But you get the point.)
Once you’ve divided the number of customers lost against those you had at the start of a month plus new ones added, you can gauge which customers churn most.
More specifically, you can (and should) run this formula for various segments (e.g., customers with average order values of $100 or more, clients with annual contracts of $50K-plus) to get a clear sense of which kinds of customers are churning.
This, in turn, can denote which segments (and even individuals) deserve your attention first and foremost when it comes to conducting bespoke lifecycle marketing activities that can mitigate the customer churn rate for those buckets and specific buyers.
Moreover, you can learn why your customer attrition rate increased by regularly reviewing your customer journey analytics across your marketing systems:
- Customer service records to see how quickly, efficiently, and successfully internal reps have handled tickets, complaints, requests, and issues for buyers
- The Net Promoter Score (NPS) for your customer base and in which direction the average overall score (and score for each segment) is trending over time
- Level of customer engagement your audience has with your digital presence and product (e.g., frequency of website visits, duration of page views, software usage rate)
- Purchase behaviors for existing customers (e.g., previously high-volume shoppers abruptly or gradually stop buying from you entirely, change in frequency of purchases)
- Types and frequency of messaging shared with your customers (e.g., if certain segments tend to churn most after receiving specific types of emails)
- Volume of customers who opt out of receiving marketing messaging (partially and wholly) and request your business cease communicating with them
The deeper you dive into your database to detect what outright causes (or, at least, contributes to) your customer attrition rate, the more aware you’ll be of what does and doesn’t aid your marketing and what you’ll need to alter to alleviate your high churn.
High attrition rate often the result of poor customer experience across channels
A common area of companies’ marketing efforts that tends to lead to a high attrition rate (along with declining bottom lines and a worsening brand reputation) is the lack of a concerted, consent-oriented, front-end customer experience strategy.
As we’ve discussed (quite often), customer identity needs to be the nucleus of your marketing program. In other words, all marketing activities should revolve around and take into account everything you know about customers— and inform your CX efforts.
Your CX strategy and efforts to lower your customer attrition rate go hand in hand.
For instance, how you manage and leverage customer data across channels — ads, emails, social media — impacts both the way your customers and prospects perceive your brand, especially compared to competitors, and purchasing decisions your buyer audience makes.
Regarding existing customers, they buy based on a variety of factors. But the experiences they have with your brand is arguably one of the most significant factors.
In very basic terms:
- A high-quality CX can compel customers to buy repeatedly and extend subscriptions.
- A low-quality CX can deter them from purchasing again and renewing subscriptions.
Back in 2018, the majority of marketers (81%) who own the customer experience initiatives for their companies told Gartner they “expect competing mostly or completely on the basis of CX” by 2020. Many also noted their CX budgets would continue to grow annually.
Even if don’t you own or contribute to your brand’s CX program, every interaction a customer has with your brand is considered part of their customer experience.
That means — in some way, shape, or form — you have some role to play in delighting them, boosting their engagement, and maintaining their business.
So, ensure you deliver a fair value exchange (not exactly a new concept for marketers) to customers to keep them satisfied and help steadily grow their lifetime value.
Customer experience specialist Blake Morgan outlined 20 distinct CX metrics for marketers that, when tracked regularly, can help them accurately gauge their strategies’ effectiveness.
Some of these metrics may be more applicable to your business than others:
- Customer effort scores likely help mostly retail, ecommerce, and direct-to-consumer brands that want to enhance the user experiences, buying paths, and general level of service for their shoppers.
- Meanwhile, securing feedback a client’s primary decision-maker regarding the quality of one’s products or services is probably more beneficial for B2B manufacturers, SaaS companies, and the like.
The point is constant analysis of these engagement and satisfaction metrics can inform upgrades to your lifecycle marketing orchestration program, help you craft a world-class CX, and, ultimately, impact your efforts to better resonate with and retain customers.
Preventing churn and tracking attrition rate easier and more efficient with a CDP
As McKinsey partners Pallav Jain and Kushan Surana noted in recent churn analysis research, companies that “excel” at reducing their customer attrition rate do so through this regular (see: weekly, biweekly, or monthly) calculation and by following other best practices:
- Achieving a complete, unified, single customer view that compiles every last data point (well, at least the pertinent ones related to their buying journeys) into one database
- Breaking down their customer base into “microsegments” so their marketing team can “personalize the treatment of a precisely targeted group of customers”
- Developing “agile testing” processes to utilize the insights gleaned in your martech ecosystem to better connect with and retain likely-to-churn customers
In conjunction with calculating your attrition rate, evaluating all customer insights from across channels — ideally, by pulling all data into a single source of truth like a customer data platform (CDP) — and modifying your marketing accordingly is how you can capably and progressively minimize churn.
You can also advance your attrition-rate reduction efforts by using predictive models.
For example, our CDP offers an out-of-the-box, propensity-to-churn notebook for marketers. (Among other easy-to-deploy, OOTB predictive models.)
This machine learning model enables brands that use BlueConic to calculate attrition risk per customer based on previous customers who have already churned.
Since this notebook comes out-of-the-box, zero hard coding skills are needed to set this up.
Having said that, if there is a specific model your company is already using to predict churn, you can import that model into BlueConic using AI Workbench.
Our customers have the ability to model churn for an entire population or particular segments and store propensity-to-churn scores in individual profile properties.
For instance, you can reduce ad waste by only targeting those with a high likelihood to churn with special discount offers or offer premium experiences to prevent churn.
Add one part comprehensive customer data (i.e., all your first-party data) with one part AI (advanced machine learning notebooks you can easily train and run), and you have the recipe to enhance your CX, increase customer satisfaction, and improve your attrition rate.
Watch our on-demand webinar to discover advanced AI marketing use cases, including propensity-to-churn models that can lower your customer attrition rate.