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2024 In-App Messaging Best Practices

2024 In-App Messaging Best Practices

A user has your app open and then receives an in-app message that your mobile marketers sent as part of a campaign. What prompts the user to click through? And how do you construct your in-app messaging to be so irresistible that the user looks forward to it?

Take a look at the following strategic tips for building in-app messages we’ve compiled into a best practices guide for 2024 and beyond.

The Effectiveness of In-App Messaging

At CleverTap, we’ve seen that in-app messages can increase click-through rates by over 100% in comparison to push notifications. That’s because they’re effective at reaching your audience.

  • First, they’re a captive audience who already opted in by installing your app. While users must opt-in to push notifications, there’s no such requirement for in-app messaging.
  • Second, the timing is right. Remember that in-app messages are delivered to customers while they’re currently using your app. This is the essential difference between them and push notifications: you’re interacting with users in real time while they’re active.
  • Third, it provides direct and instant communication with your users. This makes it easy to provide updates, promote new features, send offers, or simply gather feedback.

In-App Messaging Best Practices: Updated

We previously covered 10 timeless best practices for in-app messages, so we don’t want to rehash the same old content. Instead, we want to focus on what’s changed since we first published that post and why you need to review how you’re currently sending your in-app messages.

So what are these new and updated in-app messaging best practices?

Use AI to Personalize In-App Messages

Artificial Intelligence (AI) and Large Language Models (LLM) are ubiquitous in marketing right now, enabling everything from human-free chatbots to visualizing images and rendering videos. It’s because AI answers every marketer’s age-old challenge of, “How do I do more with far fewer resources?”

One thing that AI does well is turning meticulous manual tasks into easy automated ones. Which is what makes it a powerful tool for personalizing in-app messaging. Remember that personalized messages aren’t an option, they’re what today’s customers demand.

To create your personalized in-app campaigns, you’ll need to leverage AI to analyze the customer data points in your system to:

  • Create user microsegments grouped by in-app behavior
  • Predict a user’s actions
  • Recommend specific content to each microsegment

Create User Microsegments Grouped by In-App Behavior

Behavioral patterns — that’s where the money’s at. Use AI to analyze those patterns of your users — everything from the web pages they visit, to the time spent in your app, to the offers they click on. Use preferences, demographics, and technographics only to supplement the behavioral analysis.

Then group your users by what they do (or don’t do). Your microsegments will be much more suitable for personalized content since these users now share similar actions and not just demographic data.

Some microsegments that you should be able to create:

  • Past Behavior Segments: This is the simplest one. Here, you simply create an action-based segment — i.e. users who’ve previously performed a specific action. For example: users who have liked a product at least one time in the past 30 days.
  • Live User Segments: Using CleverTap, you can create live segments based on the real-time actions of a user. For example: a segment of users who get added as soon as they add a product to the cart but fail to purchase within 10 minutes.

Use AI to Predict a User’s Actions

Here’s where AI shines. AI is well suited to predictive analysis, using patterns to establish potential or probable action. Used properly, an AI-enabled engagement platform can predict what a segment may do based on the previous behavior of similar users within the segment.

Some examples of how this works:

Intent-Based Segments: This is a unique CleverTap feature that enables you to define future goals and predict a user’s likelihood of achieving them. Is the goal for New York City-based users to buy a Beastie Boys boxed set DVD by December 1st? The system will look at the NYC user base and see how many of them match the required behavior and preferences that may lead to that DVD purchase.

Even better, intent-based segments allow further grouping of those results into three micro-segments:

  • Those most likely to achieve the goal: no further in-app messaging needed
  • Those moderately likely to achieve the goal: here’s where you should invest your marketing resources. Get these fence-sitters to commit to the purchase via your in-app messaging!
  • Those least likely to achieve the goal: any marketing sent to these users may lead to uninstalls, or churn.


Illustration of 3 micro-segments: least likely to convert, moderately likely to convert, and least likely to convert. Intent-based segments

Intent-based segments create user micro-segments based on their predicted actions.

Get AI to Recommend Specific Content

AI can comb through every user profile and match a user with just the right offer based on their segment and their customer life cycle stage. It can then personalize the user experience by recommending relevant offers, providing contextual support when stuck, or suggesting actions that fit the user’s interest.

Thus, a travel app can create in-app campaigns that promote the latest tours to Thailand, Philippines, and China to those active users who’ve indicated an interest in traveling to Asia.

Ready to Update Your In-App Messaging Campaigns?

Now it’s time to apply these new and updated best practices and send out compelling in-app messaging to engage your users. Get creative with the power of AI, experiment with your options, and remember to analyze the results to refine and improve your messaging strategies. With a strategic and thoughtful approach, you can create in-app messages that truly resonate with your users and contribute to the success of your app.

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Posted on October 5, 2023