predicted-ratings

Much of the content on the web is created by users (“user generated content,” or “UGC”), but only a small amount of that is actually interesting enough to generate substantial interest or “go viral.” A new study by OTOInsights, a division of One to One Interactive, looks at user-created videos and flash animation from a neuromarketing standpoint. Specifically, the researchers used biometric measures to gauge the emotional engagement of viewers and then compared their data to actual ratings of the content as shown in the above chart. They came up with several major findings:

1. Traditional evaluation methods are insufficient for explaining and interpreting emotional response to digital media.

2. Setting expectations prior to content viewership encourages positive ratings and engagement.

3. Viewers encourage and respond positively to emotional content.

4. Empathy and appeal are key strategies for promoting positive emotional response and engagement.

[From Design Lessons from User Generated Content: An Analysis of User Generated Internet Video and Flash Animations]

Based on these findings, the report suggests the following steps to better optimize content:

1. Measure for emotion and engagement during the media’s development to help predict viewer response on release.

2. Carefully craft metadata to promote the media while also setting accurate expectations of its content and style.

3. Provide emotionally rich content but ensure emotionally satisfying conclusions are possible.

4. Empathize with viewer’s personal histories or appeal to the interests and culture of their microcommunity to promote positive response and engagement.

Some of these may seem fairly obvious, but it’s good to see OTOI publishing their findings and methodology for all to see. Check the full report for more detail.

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