The Customer Churn Prediction Guide

Customer Lifecycle Marketing|6 Minute Read

The Customer Churn Prediction Guide

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 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

Customer churn prediction and its impact on your retention rate and revenue

Before you begin your customer data 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 brand profitability.

We’ll assume we don’t need to answer to, “What is customer churn?” However, it’s certainly worth outlining why it’s one of the most important marketing metrics to monitor:

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:

TL;DR: Those who fail to forecast customer churn and bolster their retention rates will only continue to see their audiences flock to competitors. Both in the short and long term.

customer churn prediction

Calculating churn rates and analyzing past data to drive down customer attrition

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.)

However, 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 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 identified, 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 employ this qualitative data research (which can be accomplished through 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 attrition rate

Customer 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 high-value customers. But their tactics will differ.

There are, however, common traits in all successful customer churn prevention programs today. And one common solution — a CDP — leading businesses use to lower attrition.

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.

That is to say, find out what their website and other channels look like and entail and analyze 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 company sent personalized messages to prospective and existing subscribers it identified in BlueConic 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 big 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.

customer retention strategies

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.

You can then see which offerings should remain (top sellers and items trending “up”), which should be fixed (products declining sales-wise), and which should be eliminated (not selling at all) — modifications that can lower customer churn and boost 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 tech

Consistent customer churn prediction and analysis allows you to gradually see what helps you maintain existing customers (and drive others away) over time. And a CDP is the tech you need to streamline your churn evaluation and reduction.

Thanks to out-of-the-box predictive models, like those in BlueConic, you can forecast churn with ease, modify your marketing, gradually lower attrition, and retain your customer base.

By deploying predictive models and analyzing their performance regularly, you can easily and efficiently calculate customer churn likelihood for different buyers and segments.

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.

customer engagement model

See what BlueConic can do for you.

Whether you’re looking for operational efficiencies or improved marketing effectiveness through data activation, our customer data platform can help.