Audience Segmentation for Media Optimization
A Digital Platform company shifted its focus from revenue to user engagement on a digital content platform using a proprietary machine learning model. Combined with A/B testing and targeted video campaigns, this strategy drove increased pageviews among previously low-engagement users.
By The Numbers
- 75%lift in average pageviews per user for targeted low engagement segments
Challenge
This Digital Reading Platform company recognized the need to enhance user segmentation and engagement scoring for their reading platform for libraries and schools. Their primary challenge was to evaluate and quantify non-monetary effects to improve and emphasize the user experience, rather than relying on revenue as the primary motivator for the reading platform.
Solutions & Impact
To tackle the user engagement challenges within the reading platform, we developed an integrated and advanced proprietary ML algorithm. This algorithm leveraged over 12 data sources and examined more than 100 customer behavioral signals, allowing us to accurately calculate a brand engagement score to effectively segment the audience into high or low engagement groups.
- Implemented a proprietary algorithm to calculate user engagement.
- Launched a Google Display video campaign to boost online brand interaction.
- Conducted an A/B testing strategy to assess the non-monetary effects across various engagement factors.
These efforts lead to a 75% increase in average pageviews per user for targeted low engagement segments. This approach improved overall user interaction and successfully redirected focus towards enriching the user experience, aligning with the client’s goal of prioritizing user satisfaction over revenue generation.
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