Launching a New Testing Tool for Images and Headlines
A product launch designed to help editors make data-driven decisions, optimizing homepage performance for major news sites.
The Challenge
Editors needed a way to maximize traffic and determine which images and image-headline combinations lead to higher click-through rates. However, they were left relying on gut instinct due to a lack of tools designed for the publishing industry.
The Solution
I led a team in creating a prototype of a multivariate image testing tool for homepage editors. This solution empowered editors to test images, headlines, or both simultaneously, making data-driven decisions to optimize audience engagement.
The Outcome
Following a one-week design sprint, the project was greenlit, resulting in the launch of a new revenue-generating product. By 2020, major news sites were using the tool to improve homepage performance.
My Role
As the Lead Designer, I directed the sprint and played a key role in guiding the project from conception through to the final product release.
Project Background
For publishers, choosing the right image and headline is crucial for driving traffic to articles. While headlines are traditionally tested, images had been overlooked despite their importance. Editors had no dedicated tools for testing image performance, creating a significant gap in their ability to optimize content.
Building on the success of our headline testing tool, we received numerous requests from high-revenue customers for a similar solution for images. In response, we conducted a design sprint to rapidly explore the scope and potential design of an image testing tool.
User Research
We interviewed both internal subject matter experts and external customers, uncovering these key insights:
Editors operate in fast-paced environments, requiring an efficient testing process.
Editors needed the flexibility to test images, headlines, or both together.
High costs and contractual limitations around image use made data-driven decisions essential.
Design Sprint Approach
We began by mapping out the problem space, identifying users, actions, and goals. After aligning on the key challenges, we generated design ideas through sketching exercises, leveraging a cross-functional team for diverse input. These collaborative efforts informed our user flow and prototype, ensuring a solution that addressed real editor needs.
A map that included the actors, steps, and outcomes to guide the sprint.
Our Director of Data Science, Chris Breux, participating in a How Might We exercise.
Output of an individual sketching and dot voting exercise.
We brought it all together in a storyboard that guided our final prototype.
Results
Our design sprint helped secure funding for the Image Testing tool, which became a technical milestone for our team. By 2020, top news publishers worldwide adopted the tool to optimize their homepages, directly increasing their click-through rates and engagement.