1Weather: Scaling Mobile User Engagement with Personalized Notifications
Technology Category
- Robots - Wheeled Robots
- Sensors - GPS
Applicable Industries
- Cities & Municipalities
- Telecommunications
Applicable Functions
- Sales & Marketing
Use Cases
- Leakage & Flood Monitoring
- Smart City Operations
About The Customer
1Weather is a top-rated weather app on the Google Play Store, providing real-time local weather predictions. The mobile app offers weather information and forecasts for locations worldwide, as well as severe weather alerts and reports for specific locations in the U.S. 1Weather has more than 8 million active users, of which 5% are from the U.S. These users rely on the app for daily weather predictions, even when they are on the move.
The Challenge
1Weather, a top-rated weather app, faced a challenge in maintaining user engagement and re-engagement. Despite providing regular weather updates and predictions, the app was experiencing lower page sessions. The company wanted to ensure that users could consistently benefit from its accurate weather information and forecasts. The primary goals were to increase app opens and engagement, improve click-through rates (CTRs) using relevant push notifications, and boost the depth of each session using a content engagement score (CES). However, the company faced limitations due to the majority of its user base being in the U.S., where stringent data and user privacy laws required all engagement communications to be related to weather conditions only.
The Solution
To overcome these challenges, 1Weather adopted a more segmented engagement approach, ensuring that delivered messages were relevant to each user and optimizing the number of messages sent. The company partnered with MoEngage to deploy its customer engagement platform. They leveraged the massive amount of location data from nearly 8 million users, which was analyzed using MoEngage Analytics to create niche user segments. The brand’s marketing team was also able to analyze past users’ behavior and their mobile app activity. They then segmented users into active and inactive groups, further segmented based on their default location preferences. The team utilized these newly segmented groups to dynamically map personalized user communication campaigns using Periodically Scheduled Push Notifications and Dynamic Product Messaging (DPM). They also implemented strategies to improve mobile app stickiness, moving users from the inactive segment group to the active segment group, and adding more location data to a user’s current profile.
Operational Impact
Quantitative Benefit
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