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A few years ago, “big data” was the buzzword in the business press. You couldn’t read anything on the web without running into it.
Today, it’s a fact of business life, affecting processes at every level of complexity and allowing more and more companies to make data-driven decisions.
One area that benefits greatly from harnessing its power is customer retention. In fact, we’ll take it even further and say data science and its comrades artificial intelligence (AI) and machine learning (ML) are the secret sauce in effective retention strategies.
There are many boons that AI and ML offer to a marketing function. Below we present you with several ways that this cutting edge technology can become the differentiator in your retention strategy.
Just a decade ago, segmentation was considered a meticulous, odious task involving spreadsheets and purchased lists — typically assigned to the most junior person on the marketing team. It involved the eye-straining work of matching demographic and personal data to the ideal buyer persona in order to pull together a prospect list worth reaching out to.
Even with today’s innovative marketing tools, segmenting users properly is a challenge to marketers who have to look at multiple dimensions to segment on (e.g. not just location but also age, gender, and whether they’ve purchased before).
But data science tools have transformed the segmentation process from an Excel exercise into a futuristic prediction machine.
Today, manual analysis can be done almost instantly with the right AI engine in place, and can even predict customer behavior before it happens based on criteria that you predefine.
For example, our data science engine can analyze your customer base using intent. This Intent Based Segmentation tool groups users based on the actions they will perform in the future, predicting a user’s propensity toward achieving a specified goal (e.g., will uninstall by end of the month, or will likely purchase in the next 15 days).
This allows marketers to engage the user with an appropriate campaign designed to move them toward conversion and ultimately, meet your KPIs.
Classify Frequent Users
But perhaps the greatest way AI and ML come to the rescue in retention efforts is by automating the segmentation process and pointing out:
Our RFM Analysis tool does this. RFM stands for Recency and Frequency (of app usage) plus the Monetary value (that a user has already given your app).
What happens here is that the AI looks at how often and how recently a user has used your app along with how much that user has already purchased from you. Then it classifies each user into one of 10 segments ranging from champions to at-risk users. This gives you a group of well-defined segments as well as an action plan.
And because the process is automated, marketers can use that extra time to think up campaigns to reach those at risk of churn, or new users with the potential to become repeat purchasers.
If there’s something that Amazon has trained us to do, it’s to expect newly purchased items to appear on our door steps in two days or less. Instant gratification is the name of the game. And if you do not have the capability to satisfy customers instantly, you potentially lose out on prospects who are ready to purchase right now.
The right data science tools can instantly connect the dots between critical customer interactions and purchase intent.
Nudge Users in Real Time
If one of your ecommerce app users bookmarked two products and created a wishlist of items they intend to purchase, your AI and ML should see this as a sign that they’re close to conversion.
At this point, marketing automation should kick in to segment these users based on intent and send them a pre-written push notification or email containing an offer that they won’t be able to resist. The idea is to persuade them to convert and take action just as they reach the point where they’re ready to buy.
Personalize Down to Likes, Dislikes
Remember that consumers won’t be delighted by general, one-size-fits-all messaging. You have to know what they like and talk to them as if they were the only ones you’re contacting.
A powerful customer data platform will catalog a user’s interests, values, likes, and dislikes so that marketing messages can be tailored to each user.
With a powerful enough machine learning application, you can process millions of data points across an entire user base to quickly send out personalized messages for opportunities that arise. And influence the users who appear to be ready to make the jump.
Find Opportunities to Improve CX
Does it look like your new app users aren’t spending that much time in your app? Are formerly active users beginning to fade away after that latest UI update?
Analytics tools such as Funnels can help you identify how users navigate the app and where they drop off before reaching a conversion step. Then our Flows tool allows you to look at all the possible conversion paths customers could take so you know how to engage with them.
All this data will point to areas that need improvement within your overall customer experience.
Throwing data at a problem won’t solve every challenge you come across as you market your mobile app. But it is a powerful ingredient in your customer retention strategies.
Among other details, data science will tell you:
Because we now work in an era where data-driven decisions are the only way to go, the combined might of AI, ML, and analytics give us tools that make retention easier and more effective.
See how today’s top brands use CleverTap to drive long-term growth and retention