Broadcasting and Content Providers2022Machine Learning (classification)Predictive AnalyticsRecommendation SystemsB2C
OneRoof (NZME)

OneRoof boosts email click-to-open rate 23% and property listing clicks 218% with AI-personalized email timing

New Zealand property platform OneRoof used Braze Intelligent Timing's machine-learning send time optimization alongside behavioral segmentation and localized listing recommendations to increase click-to-open rates by 23%, drive a 218% uplift in total clicks to property listings, and achieve a 57% increase in unique clicks.

Click-to-open rate lift23%
Total clicks to listings lift218%
Unique clicks lift57%
4 min read

Background

OneRoof's email program was delivering generic, non-personalized content to all subscribers regardless of their location or property preferences. The marketing team lacked tools to segment, test, or personalize communications — all customization required developer involvement via API. Users were disengaged because the content was not relevant to their specific property search.

What Was Implemented

  • Deployed the Braze customer engagement platform (Intelligence Suite, Liquid Personalization, email)
  • Created a Profile Builder for users to declare property market status, buyer/seller orientation, and preferred suburbs
  • Integrated declared and inferred behavioral data from Braze into newsletter segmentation
  • Launched Local Insights (localized listings newsletter), Recommended Listings (ML-driven weekly wrap-up), Property News (editorial + personalized listings), and a regionalized Property Report
  • Activated Braze Intelligent Timing ML to calculate and deliver emails at each user's personal peak engagement window
  • Applied suburb-sequence Liquid Personalization logic to serve dynamic versions of emails and in-app messages

Results

Moving from generic to localized listings content: 218% uplift in total clicks to property listings and 57% uplift in unique clicks . Braze Intelligent Timing send time optimization: 23% increase in email click-to-open rate . Profile Builder: 77% completion rate converting prospects to registered customers with declared preferences.

Lessons

  • Declared preference data (Profile Builder) is highly effective at closing the personalization gap when behavioral signals alone are insufficient — a 77% completion rate suggests users are willing to share data when the value exchange (better listing recommendations) is clear
  • The shift from generic to localized content can drive step-change engagement improvements (218% click lift) that dwarf what send time optimization alone provides
  • ML-powered send time optimization works best as one layer within a broader personalization strategy, not as a standalone fix
  • Marketing teams need direct control over segmentation and campaign management (without developer dependency) to iterate quickly enough to learn and optimize

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