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Overview

Heat-map Case study

This case study examines CarambolaAI's contextual social units versus traditional ad banners on mobile devices, tracking user interactions and analyzing scroll and engagement patterns. Our goal was to show how CarambolaAI's social units boost engagement, extend user sessions, and improve the mobile user experience.

The Findings

Scrolling patterns Group A scrolled 27% further down the pages in average, compared to Group B.

Image 1: Group A scroll-map demonstration

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Image 2: Group B scroll-map demonstration.

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Click Patterns Group A showed significantly more frequent interactions within CarambolaAI's units compared to the traditional ad banners, indicating higher user engagement.

Image 3: Group A heat-map demonstration

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Image 4: Group B heat-map demonstration

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The CarambolaAI unit- Boosting engagement and session durations

The experiment showed that CarambolaAI's contextual social units vastly outperform traditional ad banners in mobile settings by promoting further scrolling and increased interaction. This led to longer user sessions and a more engaging experience, boosting overall impressions by 20%. This enhancement not only improves ad monetization for pages with CarambolaAI units but also significantly improves user experience. Our results highlight the value of innovative ad solutions in boosting engagement and optimizing mobile traffic monetization.

The Conclusion

The CarambolaAI unit-
Boosting engagement and session durations

The Methodology

We conducted a controlled experiment with 5000 Android mobile device users, divided into two equal groups:

Group

Interacted with Mobile-Web pages of US news site, featuring the CarambolaAI's contextual social units.

Group

Engaged with the same pages, but was expansed to classic ad banners instead.

Both ad formats had the same size, 300X600 px, and were placed in identical positions on the sites to ensure a fair comparison. All users' interactions were monitored and collected using viewport tracking tools over equal viewing durations for both groups. After analyzing the raw data that was collected, we converted it into heat-maps (Scroll-maps and Click-maps), providing a visual demonstration of our findings.  

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