What this result means

Your app communicates with users, but not in a structured or predictable way.
Most messages reach users through push notifications, app updates, or static UI elements. This setup works at an early stage, but it does not scale. As the product grows, users receive too many pushes, miss important updates, or fail to understand new features. Teams react to problems instead of preventing them.

The main risk at this level is silence inside the app. Users are inside your product, but the product does not actively guide, explain, or support them.

Worth reading

When Push Notifications Stop Working in Banking

As banking communication becomes more complex, push notifications reach their limits. Explore how in-app communication helps explain, guide, and reduce risk.

Mobile App Onboarding

Learn what mobile app onboarding is, why it matters, and how different types — from introductory to gamified onboarding — improve engagement, activation, and retention.

What to improve first

At this stage, the goal is to create a basic, reliable in-app communication layer that works without releases:

1. Add a basic in-app messaging foundation

Start with simple, controlled formats:

• Static banners
• Pop-ups or bottom sheets
• Full-screen messages for important updates

These formats should be used for:

• Announcing new features or marketing campaigns
• Explaining changes that affect user behavior
• Communicating important operational updates

The key improvement here is the location of the message. Messages should appear inside the app, at the moment users can act, not outside the product via push or email.

I would avoid sending informational pushes that force users to open the app just to understand what changed and relying only on UI redesigns to explain product updates.

2. Introduce Stories for explanation

Stories should not be used as ads at this stage. Their first role is education.

Use Stories to:

• Explain how a feature works step by step
• Show what value the user gets, not what the feature is called
• Replace long text screens or help articles that users never open

Stories work well because they are visual, easy to consume, and most importantly — optional, not forcing the user to see it. This reduces user confusion and support load without adding pressure.

3. Track only the metrics that matter now

You do not need advanced dashboards yet. Start with a small set of metrics:

• View rate of in-app messages
• Interaction or click-through rate
• Feature adoption after communication
• Push opt-out trend (as a risk signal)

These metrics help you answer one question:
Does in-app communication reduce confusion and push dependency?

At this point I wouldn’t try tracking vanity metrics without linking them to user actions. Or comparing in-app metrics to email or paid ads directly.

4. Run one simple campaign type repeatedly

Instead of many experiments, run one repeatable campaign:

• Feature announcement → explanation → reminder
• Onboarding guidance → follow-up tip
• Important update → short Story → banner reminder

Repetition builds internal confidence and shows where in-app communication actually helps. That way you can understand which format works best for which communication type.

Summary

At this level, your success is about presence and consistency. Once this foundation exists, you can move toward more structured and interactive communication without increasing complexity.

Your next step is to ensure that гsers receive explanations inside the app, teams can post in-app content without waiting for developers, and push notifications are no longer the default solution for your app.

Tools

How Leading Apps Onboard Customers

This case study is based on 300+ screenshots collected from 35 leading apps across e-commerce, banking, travel, health, and other industries. It examines how top teams design and optimize the very first steps of meeting a new user.

200 LLM Prompts for CMOs to Boost CR

This case study is based on 200 battle-proven LLM prompts designed for CMOs and e-commerce marketing teams. It explores how structured prompt frameworks improve key conversion metrics, including CR, CTR, ER, and Churn Rate.