1Weather is one of the top-rated weather apps for Android on Google Play Store that provides real-time local weather predictions. This mobile app offers weather information and forecasts for locations worldwide along with severe weather alerts and reports for specific locations in the U.S.
There are more than 8 million active users, of which 95% are from the U.S. and use the app to get daily weather predictions even when they are on the move.
As a utility app, 1Weather followed the primary best practices of user engagement through regular weather updates and predictions on their app. While this engagement plan worked well in bringing users back to the mobile app, it did not cover re-engagement of users in a regular manner. As a result, the brand observed lower page sessions within the app. They wanted to ensure that users are able to benefit from 1Weather’s accurate weather information and forecasts in a regular manner through the mobile apps.
We had a unique challenge of providing real-time, hyper-local and personalized weather alerts to our users and MoEngage has proved to be an asset in automating our efforts at scale. The analytics piece has helped us analyze, understand and uncover valuable insights to improve our retention.
1Weather’s marketing team wanted to send regular notifications on their users’ mobile phones, eventually bringing them to the app. However, with the majority user base from the U.S. this regular engagement strategy came with certain limitations/restrictions:
Being a utility app, 1Weather could not access a user’s PII (Personal Identification Information) such as email, phone number, and more. However, they did have access to the user’s location and weather search history based on approvals provided by the user. The user location data was the default location added by the user on their mobile phones but user events data captured all the additional location data that was either searched or added by the user on the app. The brand’s marketing team already had this humongous amount of location data from almost 8 million users. This data was ingested into the MoEngage platform and was analyzed using MoEngage Analytics and the insights derived were used to create niche user segments.
Using Behavior Trends Analytics: The brand’s marketing team was able to analyze past users’ behavior and their mobile app activity. Now the team knew who the active and inactive users were, and their weather search history. Once this logic was set, the team utilized MoEngage Segmentation to segment these users into different groups:
Using MoEngage Analytics, the team analyzed past customers’ behavior and mobile app activity. It showed them who the active and inactive customers were, as well as their weather search history. The team then utilized MoEngage to segment these customers.
• 25 million incremental app opens
• 10% increase in CTRs on push notifications
• 20% boost in depth of session calculated using CES
• 15% higher session duration
The team utilized the newly segmented groups to dynamically map personalized customer communication campaigns using MoEngage’s Push Notifications and Dynamic Product Messaging. The objective was to send the right weather notifications to the customers at the right moment with the right messaging.
1Weather’s strategy of offering relevant, bite-sized customer communications helped them achieve higher incremental mobile app opens and higher engagement. This eventually improved mobile app sessions too. Adding relevant content to every notification boosted their content engagement score as well.
