Braze Launches Machine Learning-Powered Predictive Suite to Bolster Cross-Channel Capabilities and Boost Customer Loyalty

Braze Launches Machine Learning-Powered Predictive Suite to Bolster Cross-Channel Capabilities and Boost Customer Loyalty

Customer Engagement Platform Also Announces Updates to AI-Powered Intelligence Suite, New Tools and Three New Partnerships

Braze, the comprehensive customer engagement platform, announced new features and product expansions to bolster cross-channel capabilities, increase retention and amplify customer loyalty. These include updates to Braze’s automated decision making Intelligence Suite as well the introduction of Braze Predictive Suite, a new lineup of tools which will help brands increase retention using machine learning.

New AI and Machine Learning Features to Support Personalized Actions

The introduction of the Braze Predictive Suite and updates to the Braze Intelligence Suite help marketers gain insight and prompt easier and quicker personalized actions. With Braze Predictive Suite powered by machine learning, marketers will be able to easily build and analyze predictive models and segments to understand churn, behaviors, and purchases, and ultimately better inform customer engagement strategies. The first model designed to predict customer churn is set to become available in February 2020.

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Further, in an effort to create greater cohesion and pave the way for new AI and machine learning feature sets, Braze has refreshed its Intelligence Suite, which leverages automated decision making. Namely, Intelligent Timing, which enables marketers to send messages to customers when they’re most likely to engage, has been reconfigured to provide more ease and greater control over campaigns. This includes the ability to choose a fallback time, classify specific times of day as off-limits to send messages, and more. With Intelligent Timing, marketers are able to achieve a 12 percent lift in email open rates and a 28 percent lift in push open rates.

“We’re already in the age of automation, but AI and machine learning can still be perceived as cumbersome and difficult to figure out,” said Kevin Wang, vice president of product at Braze. “With Braze’s new Predictive Suite and streamlined Intelligence Suite, we’re aiming to provide brands a platform that is both effective and easy to use, and in turn, brands will add more value with each customer interaction and campaign they create in their regular workflow.”

“We’re excited to work with Braze on a customer churn prediction feature that allows us to re-engage users that are likely to fall off,” said Hector Bragado Fernandez, lifecycle marketing manager at Lumos Lab. “The results of our first round of testing have shown that we can boost retention, and we are eager to roll this out more broadly to realize the feature’s full potential.”

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Expansion of Partnership Integrations to Enhance Existing Loyalty Programs

After expanding its popular Alloys partner program this fall to include more than 40 solutions partners worldwide, Braze continues to expand partnership initiatives with new integrations with Amazon Moments, Talon.One, and Voucherify. These partnerships focus on providing holistic, customizable integrations so that brands have more options to send the perfect content at the perfect moment, without disrupting their current marketing stack.

Additional updates include:

  • Canvas components: Braze’s customer journey tool, Canvas, gets three new components designed to give marketers greater flexibility. Delay, Decision Split, and Message Steps allow marketers to unlock new capabilities and opens up a simpler and more intuitive process for the whole team.
  • Promotions: Braze now makes uploading and managing promotion codes for use in campaigns simpler and faster. This new feature can process larger volumes of promotion codes, allow upload via CSV and set expirations for lists.
  • Dark Mode for In-App Messages: Provides an alternate color theme for users who use Dark Mode on their devices, a simple yet powerful form of personalization.

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