Customer churn prediction is difficult for many marketers. And it’s easy to see why.
There’s no crystal ball that shows you exactly when high-risk customers buyers will abandon their respective buying journeys, enter the “Lost Customers” segment of your database, and, ultimately, affect your recurring revenue numbers.
Having said that, you and your team can greatly improve your churn prediction and prevention efforts by using advanced machine learning algorithms to:
- Analyze why you lose customers: from one-time buyers to long-term subscribers
- Examine current customers’ behaviors to discern the likelihood of churn occurring
- Assess which buyers’ customer lifetime value (CLV) scores are dropping over time
One-third of subscription-based organizations have lost revenue or experienced reduced profitability due to high annual churn rates. That makes it critical to scrutinize your first-party data regularly and take the necessary actions to retain customers.
Customer churn prediction and its impact on your brand’s retention and revenue
Before you begin your customer data audit to what could cause certain individuals to stop doing business with you altogether, it’s vital to understand how proper customer churn prediction protocols impact short-term marketing goals and long-term brand profitability.
We’ll assume we don’t need to answer the obvious question: “What is customer churn?” However, it’s certainly worth outlining why it’s one of the most important marketing metrics to monitor:
- Businesses lose roughly $1.6 trillion annually from customers who churn due to poor customer service experiences in the past. — Accenture
- The cost of acquiring new customers as profitable as existing ones can be up to 16 times higher retaining current customers. — MIT
- 59% of consumers will stop buying from brands after several bad customer experiences, while 17% will do so after just one. — PricewaterhouseCoopers
The evidence continues to mount in favor of developing customer churn prediction models you can regularly refine and, concurrently, new customer retention strategies.
And yet, many executives at B2B and B2C brands alike still don’t understand the (numerous) negative ramifications — both fiscal and reputational — of ignoring these approaches that can reduce churn and help them retain customers.
- Just 15% of senior leaders at B2B organizations said their teams use customer data to routinely inform business decisions. — Forrester
- Only 30% of executives and board of directors members consider customer satisfaction a top priority for their brands today. — Deloitte
- Improving customer loyalty and retention is primary objective for just 38% of retailers and ecommerce companies. — BRP Consulting
TL;DR: Those who fail to forecast and calculate customer churn and bolster their retention rates will only continue to see their audiences flock to competitors. Both in the short term and over a long period. (Basically, as long as they fail to respond appropriately).
Calculating churn rates and analyzing past data to drive down customer attrition
“So, how can I address my company’s churn rate and keep our customers coming back?”
That’s definitely the right question to ask. And the answer is threefold:
- 1) Understand customer intent.
- 2) Track customer experience.
- 3) Identify customer trends.
As you likely suspected already, churn prevention and customer retention go hand in hand:
- Churn prevention focuses on the past. Unearth insights about from your databases to identify the potential and likely reasons behind previous buyer abandonment.
- Customer retention focuses on the future. Use those findings to inform new and revised marketing messaging to retain existing customers for the long run.
What’s essential to remember is your customer-retention and churn-reduction strategies won’t succeed if the marketing and data science teams don’t work together.
Specifically, they must work in tandem to predict and reduce customer churn. (And, in turn, keep attrition as low as possible for the longest possible time period.)
Having said hat, you can certainly use a customer data platform (CDP) like BlueConic without the aid of a data analyst to leverage easy-to-deploy customer churn prediction models.
(More on this shortly.)
If you don’t have a CDP, or simply need assistance with getting going with machine learning models, a data analyst can help you dissect your customer data from various sources.
In short, they can help you see what commonalities exist among premier buyer segments, like the:
- Total number of customers to buy your highest-priced products or services
- Volume of clients to sign a long-term contract within a given period of time
- Propensity of subscribers to sign up for paid plans after their free trials
- Frequency of engagement across channels (e.g., site, social media, email)
Once these figures have been compiled, sorted, and sent your way (or unified in a CDP after connecting with other data sources), you can support your data-based findings further.
How? By conducting qualitative research about your customers to glean more intricate and advantageous purchase and churn insights, including:
- Why they repeatedly bought specific products or services but eventually stopped
- What reasons ultimately led them to end contracts and sign with competing brands
- How they perceive the quality of your brand, products, services, and pricing model
Whether or not you decide to go the extra mile with this kind of qualitative customer data research (which can be accomplished through tactics like NPS surveys you can promote on-site and via email) is up to you.
But the next step is the all-important one: developing hypotheses and an action plan based on your unified audience insights integrated in your database ecosystem.
Customer churn prevention methods for B2B and B2C marketing professionals
At the end of the day, B2B and B2C marketers want to accomplish similar goals through similar means. For instance, nurturing top prospects and acquiring high-value customers and clients.
Having said that, it’s clear B2B marketing differs greatly from B2C marketing in many respects as well. Including and especially regarding their customer churn strategies.
B2B customer churn prevention strategies
Whether you work for a SaaS startup or an established B2B ecommerce brand, it’s likely a top goal to keep your high-cost customers long term.
At the end of the day, this once-arduous task can be accomplished with comprehensive churn prediction analysis and prevention strategies.
Ensure smooth onboarding, and follow up often.
Let’s say you offer supply chain software for manufacturers to help them better track all aspects of their business: from marketing and sales to packaging and fulfillment.
This can be a complicated solution for any manufacturing executive to learn and master.
According to Vendasta research, clients who engage weekly with the B2B businesses from which they buy have a 26% greater retention rate than those who don’t.
Develop a successful onboarding program that carefully guides clients through the process of getting set up and acclimated with your software. Then, follow up with them over time to ensure they’re engaged, happy, and making the most from the software.
Build a customer consent management strategy.
Consent management strategies help brands show they care about customers and their privacy by allowing them to opt out of messaging and gain control over their data.
To state the obvious: The more a customer trusts you, the more loyal they’re likely to be.
Therefore, crafting a consent management strategy — one that takes advantage of martech with consent management functionality to help comply with data laws like GDPR and the CCPA — is how you can win over one-time and recurring customers.
What’s more, this kind of emerging technology offers an ideal means for marketers like you to appeal to prospects who’ve yet to buy from you but express interest in your brand.
In the age of consumer data privacy, transparency wins. Consider how you can incorporate consent management to reduce your churn rate and maintain existing customers.
Offer custom discounts to ensure contract renewal.
A couple common trends B2B marketers discover during customer churn prediction analysis and prevention strategy development is clients who cease communications with them tend stop using the product altogether or fail to renew subscriptions or re-sign contracts.
(In short, their silence and lack of engagement speak volumes.)
That’s not to say all these customers or subscribers will churn and worsen your company’s attrition rate. Rather, it could simply mean they need a little nudge to re-up their deals.
If you notice one or both of these trends with your customer base, schedule additional check-ins with or offer discounts to the buyers question to see if that’s enough to get them (and, specifically, their decision-makers at those clients) over the proverbial hump.
Given the considerable cost of acquiring new customers and the relatively inexpensive cost of keeping existing customers, approaches like these are worth it for your marketing team.
B2C customer churn prevention strategies
On the flip side of the customer churn coin is the B2C approach. These churn prevention methods are akin to those for B2B brands above, but with a more individualized focus.
Research your competitors’ digital presence.
Price isn’t the only factor in consumers’ purchasing decisions. Personalized deals, social proof (testimonials, reviews, etc.), and digital customer experience all affect whether consumers buy from your brand or not.
Thus, it’s wise to invest some resources to investigate just how your competition is perceived online, what their website and other channels look like and entail, and the overall user experience (UX) customers have with those digital properties.
Sure, you’ll want to price your products and services accordingly to properly compete with brands in your space. But don’t underestimate the quality of a good CX.
Individualize offers to potential churn risks.
Another proactive approach to churn prevention (not to mention new customer acquisition) comes from BlueConic customer WEHCO Media.
The brand sent personalized messages to prospective and existing subscribers it identified in its BlueConic tenant to sign up for or update subscriptions instantly within the product.
By messaging the latter group of subscribers right before they could possibly churn on-site or via mobile, the publisher was able to retain a sizable portion of its subscriber base.
In turn, the publishing brand kept recurring revenue for current subscriptions coming in the digital door — a big marketing win for the media brand, to say the least.
Modify existing offerings and add new ones.
Unified first-party data access in a single source of truth like a CDP allows you to determine which products and services sell most often, which channels and mediums customers purchase them, and other details about your audience’s’ customer journeys.
With this info, you can see which offerings should remain (top sellers and those trending “up”), which should be fixed (products declining sales-wise), and which should be eliminated (not selling at all) — modifications that can decrease customer churn and increase retention.
There are certainly other customer churn reduction measures you could test:
- Donating to charities and nonprofits your buyers and subscribers care about
- Producing products in more eco-friendly, environmentally conscious manners
- Conducting feedback surveys to better learn about customers’ wants and needs.
The list goes on. But start with these tried-and-true churn prevention tactics first.
Customer churn prediction and reduction possible with the right martech
Consistent customer churn prediction and analysis allows you to gradually see what helps you maintain existing customers (and drive others away) over time.
Thanks to out-of-the-box predictive models, like those offered in BlueConic, you can forecast churn with ease and modify your marketing accordingly to gradually lower your attrition rate and, simultaneously, grow lifetime value for your customer base.
The machine learning algorithms behind our AI Workbench models allow digital marketers who use BlueConic’s pure-play CDP in their day-to-day efforts get insights into potential customer attrition based on buyers’ and subscribers’ profile changes (e.g., lack of website or app engagement, increase in abandoned carts).
By tracking this predictive model performance regularly, these marketing professionals have the ability to analyze data points regarding their contacts and, in turn, easily calculate customer churn likelihood for different buyers (and buyer buckets).
In case it hasn’t been made clear already, your customer churn rate won’t go down with a laid-back, assume-everything-will-work-out attitude and half-hearted efforts.
It will, however, go down with an analytical approach, a concerted customer engagement strategy across your marketing team, and the ideal martech (see: CDP) in place.
Download our eBook to learn about the new customer engagement model marketing needs to adopt and implement today to lower churn and boost retention.