Senior Content Designer.
Google Search.
Ask me how I:
- Impacted direction for a high visibility feature release on Search
- Shipped clear, data-driven, and scalable copy that increased interaction metrics by 4x
- Increased scope for content design and UXR
- Collaborated closely, aligned XFN, and advocated for content design
- Worked fast on multiple projects across surfaces, balancing quality with speed
- Wrote and iterated on copy for A/B and multivariate testing
Case Study: Launching an AI-powered calling feature on Google Search
This feature uses AI to call multiple local businesses near you to get pricing and availability on your behalf. This means you can get the details you need to make an informed decision about who to hire, without losing all the time to make the calls yourself. This feature also benefits businesses by connecting them with potential customers.
[Note: these are screenshots of an incomplete flow. Check out the video demo of the full flow here.]
Challenge:
This technology is unprecedented, so users don’t have a mental model to help them understand what this does or how it does it. That makes user education very important, but we had several parameters limiting what we could do at this time.
For the MVP, we needed the entrypoint—a single CTA button—to do a lot of work:
- Convey the unique value of this feature (that the calling and price gathering gets done for you)
- Compel people to tap on the CTA to learn more
- Set enough of an accurate expectation for what will happen once people tap on the CTA so they’re not thrown off by what they see next, preventing confusion and abandonment
- Convey the minimal amount of what this does, and why, to achieve the bullets above
I identified:
- What is the goal at this touch point
- What is the minimal amount of info we need to convey at this touch point
- What language best resonates with users, while working within our parameters and guidelines
- What signal do we need to find the best solution, and what variables do we need to test to get that signal
- Future improvements and testing opportunities
Impact
Content design improved interaction metrics (CTR) by 4x from the original entry point design.
Solution
Much iteration and rationale went into the solution. At this time we have released an MVP of this feature, which involved multiple rounds of testing (LEs), leveraging those results (and shaping follow-up LEs), working closely with product design, UXR, and ENG, and iterating quickly. More to come as the team further develops this feature.
In the meantime, please check out some of our early press!