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 will abandon their respective buying journeys and enter the “Lost Customers” segment of your database.
Having said that, you and your growth-focused teams 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
- Employ personalized and individualized engagement activities to keep customers
One-third of subscription-based organizations have lost revenue or experienced reduced profitability due to high annual churn rates, Forrester research shows.
That makes it critical to leverage your first-party data to better understand and interact with customers and, in turn, deliver bespoke experiences that help you maintain their business.
And there’s no better technology to help you tap into your first-party data and aid your customer churn prediction and prevention efforts than a customer data platform (CDP).
Customer churn prediction and its impact on your retention rate and revenue
Before you begin your database audit to identify what facets of your business lead to a high risk of churning, it’s vital to understand how proper customer churn prediction protocols impact short-term marketing goals and long-term business profitability.
We obviously don’t need to answer “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 than retaining current customers. — MIT
- 59% of consumers will stop buying from businesses after several bad customer experiences, while 17% will do so after just one. — PricewaterhouseCoopers
And yet, many C-suites still don’t understand the (many) negative ramifications (fiscal and reputational) of ignoring approaches that can reduce churn and retain customers:
- Just 15% of senior organizational leaders 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 companies 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 customer churn and take action on their first-party data insights bolster their retention rates will only continue to see their buyers and/or subscribers exit their funnel. (And, in all likelihood, flock to competitors.)
The good news? Analyzing individuals’ churn likelihood and activating (a.k.a. liberating) data across channels in real time to prevent churn is streamlined with a CDP like BlueConic.
How BlueConic customers forecast and prevent churn with our pure-play CDP
What’s essential to remember is your customer retention and churn prevention strategies won’t succeed without the aid of advanced technology that enables all technology users — not just data scientists — to utilize predictive models and act on data insights.
No longer do marketing, ecommerce, customer experience, and other teams have to rely on data science to build and deploy machine learning models to glean audience insights that can assist their churn reduction efforts.
Now, they can use a CDP like BlueConic, which offers out-of-the-box models — including a propensity-to-churn model — to engage the customers deemed most likely to stop purchasing from them or subscribing to their products or services.
With BlueConic, you can sync all first-party data across systems and sources and create unified, persistent profiles for each individual in your data ecosystem.
And when you launch a churn-propensity model, the customer score that indicates an individual’s likelihood to churn updates dynamically (i.e., in actual, not near, real time).
In short, with unified profiles accessible to you and all other growth teams, you can collectively see all activity, behaviors, and other attributes for likely-to-churn segments, like:
- Recency and and momentum of site visits and page engagement for buyers/subscribers
- Propensity of subscribers to renew/fail to renew and what renewal messaging resonates
- Repeat customers whose purchase frequency declined in recent days, weeks, or months
Simply put, with AI Workbench and customer profiles that automatically update as individuals’ engagement levels and other attributes change, you can capably (and efficiently) develop and execute plans to reengage those segments/audiences and prevent churn.
Specific churn prevention methods for consumer-centric companies
Companies across industries and niches want to accomplish the same goals but often go about achieving them differently. For instance, they both want to nurture top prospects and acquire and retain high-value customers. But their tactics will differ.
That said, there are common traits in all successful customer churn prevention programs today. And one common solution — a CDP — leading businesses use to lower attrition.
One prominent, proactive approach to customer churn prevention (and technically for customer acquisition as well) comes from a privately held media company and BlueConic customer:
- The company sent personalized messages to prospective and existing subscribers it ID’d in BlueConic to sign up for or update subscriptions instantly on the website.
- 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 big portion of its subscriber base.
- In turn, the publishing business kept recurring revenue for current subscriptions coming in the digital door — a big win for the media company, to say the least.
Unified first-party data access in a single source of truth like a CDP allows you to determine which products and services are bought/subscribed to often, which channels lead to purchases, and other details about your audience’s’ customer journeys.
All of which can help you effectively drive down your churn rate, keep your business’s bottom line moving in the right direction, and enhance efficiency in your day-to-day.
Download our eBook to learn about the engagement model companies needs to today to not just improve their customer churn rates, but also accelerate business growth.