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1.1 // RELEVANT CONTENT, ENGAGED USERS

Challenge:

content overload

Virtually every app has more content than each user could (or cares to) consume. Whether showing videos in an entertainment app, articles in a news app, hotels in a travel app, or tickets in a productivity app, developers constantly need to filter and sort content.

Pre-AI Approach:

sort and filter by data attributes

The most common method to deal with content overload is to order and filter the content by data attributes. For instance:

While attribute-based ordering is a powerful basic tool, it completely ignores the user history and preferences, resulting in reduced user engagement and expensive content that is left undiscovered.

Better with Haro:

sort and filter based on relevance to each user

With Haro, you can order and filter almost any content by how likely each user is to engage with it. Haro empowers you to build prediction-driven features that show:

Furthermore, Haro allows your app to augment the existing attribute-based ordering with prediction-driven personalization, and show:

By providing powerful content discovery tools, Haro enables your app to have more engaged users who are able to find the content that is personally relevant to them.

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