How to Use Braze Predictive Analytics for Customer Retention

Customer relationships are no longer measured by one-time interactions; they are measured by long-term engagement and loyalty. Today, to retain customers, brands need more than just promotions — they need data-driven strategies. This is exactly where Braze Predictive Analytics comes into play.
Braze’s powerful AI infrastructure enables brands to anticipate customer behavior, reduce churn risk, and intervene with the right message at the right time.
In this article, we’ll explore step by step how Braze Predictive Analytics works, how it contributes to customer retention, and how Omtera, as a Braze partner, helps brands leverage this power in the most effective way.

Fundamentals of Predictive Analytics

Predictive Analytics is an analytical method that learns from past data to predict future behaviors. Braze applies this approach by analyzing user data within its platform (for example: interaction frequency, campaign response rate, last session date, purchase history).
As a result, the system generates a likelihood score for each user.
Example:

• A user has an 85% chance of returning to the app within the next 7 days.
• Another user has a 60% chance of canceling their subscription.

This information allows marketing teams to prioritize customer segments and develop personalized intervention plans.

Understanding Customer Behavior with Braze Predictive Analytics

Braze supports its predictive models with machine learning (ML). These models continuously update user data and produce increasingly accurate results.
Some of the main models include:

• Churn Prediction Model: Predicts the risk that a user will leave the app.
• Purchase Prediction Model: Determines the probability that a user will make a purchase within a certain timeframe.
• Engagement Prediction Model: Measures the likelihood that a user will respond to campaigns.

These models enable brands to develop strategies for each stage of the customer lifecycle.
For example:
If a user has a high churn probability, Braze can automatically trigger a personalized re-engagement campaign.

Steps to Increase Customer Retention

Integrating Braze Predictive Analytics into your customer retention strategy follows specific steps:

Step 1: Clean the Data and Feed the Model

Accurate predictions require clean, organized, and meaningful data.
Braze unifies data from CRM, mobile app, web, email, and API sources to offer a 360° view of each user.
Omtera manages this integration process, optimizing data flows and seamlessly connecting Braze with systems like Snowflake, Segment, or Mixpanel.

Step 2: Create a Predictive Model

You can build a Predictive Model in just a few clicks through the Braze Dashboard.
For example, with a “Conversion Prediction” model that targets user behavior, you can identify users with a high purchase probability and group them into a dedicated segment.

Step 3: Automate Segmentation

Predictive results are automatically reflected in segmentation processes.
Examples:

• Send a discount email to users with High Retention Risk.
• Send a premium offer notification to the High Purchase Likelihood segment.
  These segments can be targeted through omnichannel campaigns in Braze Canvas.

Step 4: Monitor and Optimize Results

Braze allows you to measure the results of Predictive Analytics campaigns in real time.
With metrics like Engagement Rate, Churn Reduction, and Revenue Uplift, you can identify which strategies are effective and optimize them continuously.

Omtera’s Role: Strategic Execution and Continuous Optimization

Braze is a powerful platform, but using it effectively requires expertise.
As an official Braze partner, Omtera provides support to brands in the following areas:

• Predictive Model Setup: Configures models according to your data quality and business goals.
• Data Integrations: Connects Braze with your existing data ecosystem (CRM, BI, customer data platform).
• Campaign Strategy and Orchestration: Converts predictive model results into actionable marketing automation.
• Continuous Monitoring and Optimization: Analyzes campaign performance and dynamically updates segments.

Thus, brands not only access data but also gain a structure that transforms data into action.
Omtera’s unique value lies in adapting Braze’s full potential to the brand’s strategic objectives, ensuring long-term success.

Tangible Benefits of Predictive Analytics

A Real Example: Segmentation + Predictive Power

Imagine an e-commerce brand.
Twenty percent of users have reduced their purchase frequency, and churn risk has increased.
Braze Predictive Analytics labels these users as High Churn Probability.
For this segment, the Omtera team designs the following strategy:

• Push notification: “Exclusive discount on the products you viewed last time.”
• Email campaign: “Today only — 10% off in your favorite category.”
• In-app message: “Welcome back! Your bonus reward is ready.”

Result?

• 18% decrease in churn
• 25% reactivation rate
• 12% revenue growth

All achieved automatically and sustainably.

Best Practice Tips

• Avoid overcomplicating your model: Simple models with smaller datasets often yield better results.
• Update segments regularly: Customer behavior changes over time — your model should adapt accordingly.
• Ensure consistency across channels: Predictive campaigns should maintain the same tone across all touchpoints.
• Leverage Omtera’s expertise: Misconfigured predictive analytics setups can produce misleading results.

Do you want to increase customer retention and strengthen your data-driven marketing strategies?
Contact Omtera today and integrate Braze Predictive Analytics into your business.

Frequently Asked Questions (FAQ)

How accurate is Braze Predictive Analytics?
Accuracy depends on data quality and sample size. Braze’s ML engine improves over time, achieving accuracy rates of 80–90%.

Can I create automated campaigns with Predictive Analytics?
Yes. You can set up automated triggers in Braze Canvas based on predictive model results.

What kind of support does Omtera provide?
Omtera offers end-to-end services, including model setup, integration, campaign strategy, A/B testing, and continuous optimization.