AI can Predict Subscription Cancellation

The subscription economy is based on customer retention. The more a subscriber sticks to the subscription product or services, the more likely the merchant offering subscription product or services can have a better recurring revenue growth with the opportunities to sell, upsell, cross-sell, or re-sell the subscriptions.

To keep the customers hooked with the subscription product or services, a robust and data-driven strategy of sales, marketing, and growth is required.

Subscription businesses are the science of data. Its terms and conditions, policies, business processes management, support, and services—all are data-driven. It is mainly because once you lose the customers, it is hard to earn them back.

Envisaging the likelihood of subscription cancellation or churn can mitigate the risks of losing a source of recurring revenue. Having a forewarning on subscribers who are on the verge of canceling their subscription can be a great advantage in a modern subscription business management.

Artificial Intelligence can be used to make the subscription business processes management proactive instead of being reactive by adding the value of data-driven intelligence that can suggest appropriate action moves at the right time for the right department to act right on the right lead or customer. AI provides maximum support to stay subscribers at the platform and continue to contribute to the recurring revenue stream.

In some of our previous articles, we have learned that the Machine Learning (ML) and Deep Learning (DL) as the subsets of the Artificial Intelligence are increasingly being used in the subscription management to find, foretell, and mitigate the risks to the recurring revenue growth, brand progression, and business development.

This blog post particularly deals with the learning of how AI plays a major role in identifying the patterns and behaviors behind the subscription cancellations. Knowing the reasons that cut the cords between the subscribers and the subscription services providers allows subscription businesses to take data-driven precautionary measures that can halt or help in churn reduction.

Also Read: AI and SaaS for Revenue Growth—Follow Our 7-Steps Guide to Automate End-to-End Subscription Management for Your Business

Why Forecasting Subscription Cancellations is Important for the SaaS and Other Subscription Businesses?

The Subscription services providers need to gain insights into why Subscription pauses or cancellations are causing frictions in the subscription cycle continuity and reducing the lifetime value of users while incurring the sudden loss in recurring revenue.

Usually, SaaS, telecom, rentals, newspaper and magazine, OTT (Over-the-top) media, gated-content sites, memberships, telemedicine, education services, and many others are all the subscription services providers. It explains that these subscription merchants depend on the number of subscribers who subscribes to their daily, weekly, monthly, or annual plans and contribute to growing recurring revenue and building brand loyalty.

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Identification of all the non-performing indicators also help the subscription services providers to remove the frictions from the business processes management–from developing the product to strategizing the marketing and sales funnel to the customer support and services at each stage of customer acquisition and customer retention.

Using AI-powered data allows subscription organization to find the logic behind the subscription cancelation and the product attributes. It harnesses the productivity and efficiency of the product managers, sales, marketing, and support teams to stream success.

Once the factors greasing the churn in the subscription business are identified, it can pave the ways to increase retention and revenue.

Also Read: AI-Enabled SaaS for Subscription Management—05 Key Areas Where Using Artificial Intelligence Revolutionized the Data-Driven Services

How AI Uses Data to Foretell Churn In the Subscription Management Software?

We know AI uses data to identify the reasons behind subscription pause, cancellation, or even downgrades. This is how it can predict the churn and recurring revenue damage in its earlier stages. It leverages the subscription merchants to take all the necessary steps times ahead and reduce the chances of any losses of revenue or customer base.

But, here the question arises that how does AI forewarn the risk and what data does it require to foresee the subscription cancellations?

Artificial Intelligence through the ML and DL structures, reads, understands, and analyzes the user online behavior, subscription parameters, engagements, paywall, newsletters, and other product attributes trends to determine the subscription health of any subscriber.

In any subscription lifecycle, those who are found at the risks of churn can be targeted with measures like personalized promotions, discount perks, enhanced customer experience, better customer support, and then their actions can be monitored, measured, and managed, efficiently.

AI-led modules are trained to analyze the following key types of data to monitor, measure, and suggest management and mitigation actions that reduce the damages in a subscription cycle. Some of the most valuable datasets to stop subscription cancellations are:

Customer’s Personal Information—it includes name, contact details, email, or social media accounts, and other personal information.
Demographic Data—it encompasses the data like age, income, education, location, etc.
Product Data—this dataset covers information like the subscribed product, plan, term, and features used.
Support Services—it includes information related to customer interaction with the subscribed product’s customer care, queries, feedback, complaints, and of course, the satisfaction ratings.
Payment Data—this dataset is used to find the customer behaviors at the paywall, expenditure over the time in the form of daily, weekly, yearly, or exclusively for a particular feature, engagement due to discounted coupons and vouchers, credit score, transaction history, or, overdue balance, etc.
Device Data—AI uses the login and activity information available through the device. This is the personalized form of information that brings more accuracy in the predictive analysis of the subscription cancellations.

Also Read: Leveraging the Power of Machine Learning in Subscription Billing to Mitigate Fraud and Churn rate

The Science of the AI-Powered Predictive Analysis of the Subscription Cancellations

Artificial intelligence efficiency is directly proportional to the amount of data available. The more the volume of the data, the better the forecasting of the subscription cancellations or churn.

The more structured the data set is, the faster and the better predictions are. However, deep learning can help in establishing the structure and logic in the data for the AI to include even the unstructured data to bring more precision in the prediction.

With subscription cancellation predictions, the ML/DL algorithms interpret the complex patterns in high-dimensional data that correlate with one of two outcomes i.e. Subscription and Subscription Cancellation.

AI facilitates the subscription businesses to concentrate on the customers who show more probability of leaving the subscription. It channels customer retention to immediately impact the bottom-line.