Ster advertising

Ster advertising

Ster advertising

AdScan: Enhancing ad performance insights

AdScan: Enhancing ad performance insights

AdScan: Enhancing ad performance insights

AdScan, a product by Ster, uses advanced machine learning to predict how a panel of a hundred people would assess a TV commercial. It is not just a tool. It's an interaction between AI algorithms and advertisers.

The challenge

Advertisers were facing difficulty interpreting the complex results from current AdScan. My objective was to redesign AdScan's interface to deliver clear, understandable advice on commercial performance.

A multidisciplinary team

Our team was a mix of developers, marketers, and data scientists - individuals familiar with AdScan and who could understand advertisers' perspectives. As the facilitator, UX Designer, UI Designer and Interviewer/ UX Researcher, my role was to steer the project. Yes, I was wearing many hats. It has pros and cons. For the next time, I might consider bringing in another designer and/or a dedicated facilitator.

Approach: comprehensive understanding

Our first step was to thoroughly understand the problem. A 4-hour workshop highlighted the strengths and weaknesses of the current version of AdScan. We also constructed an empathy map to gain insights into the mindset of an advertiser, our target group. Lastly, we mapped out a user flow. We found out we wanted to include the landing page, before going directly to the AdScan interface.

Generating ideas

Inspiration is everywhere. Each team member contributed ideas from various sources like apps, websites, or advice tools. Based on these ideas, every person from the team created their solution. We sketched, shared, and voted for the most promising ideas. The selected ideas were then transformed into a clickable prototype made in Figma, by me.

Outcome: user-friendly interface

Our prototype was intuitive for the users. It presented advice in an easy-to-understand format. First, we give an overall score, together with an industry benchmark. Then we provide the advice: What elements should you keep, what elements could be eliminated and which elements could improve the ad performance. We interviewed five different advertisers. Based on feedback from them, we further refined our prototype.

In conclusion

AdScan has transformed into a tool that advertisers can easily understand and utilize. Our focus was not only on designing an interface but also on creating a user-friendly link between complex AI and advertisers. The redesigned AdScan has become a clear interface for advertisers, offering actionable advice and clear commercial performance insights.

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Let's get in touch

I'm just a message away. Let's talk!

Let's get in touch

I'm just a message away. Let's talk!