H1 Browser Extension

H1 was hyper-scaling after the Series B fundraise, and the Board wanted to invest in creating adjacent products. Consequently, H1's strategy team identified adjacent markets to compete in with new products Foremost, was to compete with Doximity, the 'LinkedIn for doctors.'

Specifically, the team thought to create a public-facing "Doctor Network" -- like Yelp and Zillow where public information is claimed and enriched by verified owners. This user-generated data was a big bet intended to create a data moat against our competitors.

For additional context, learn more about H1's core product & users in my H1 Doctor Profile case study ->

Getting started

As lead designer, I was excited to help spin up prototypes and validate this new product in the market -- a true zero-to-one experience.

Team goals were as follows:

1. Discover - Perform 20+ customer discovery interviews
2. Build - Rapidly design prototype and marketing landing page
3. Launch - Launch and promote via organic/inorganic channels
4. Test - Test iterative improvements/ideas to see what increases conversion

Through our initial discovery interviews, we narrowed our target user to medical school students who were nearing the end of their schooling (e.g. residents, fellows). We learned that these students knew they needed to start to own their digital presence, yet hadn't invested into this yet because it seemed daunting.

We hypothesized that we could launch a lightweight product that fit right into these student's workflows. It would easily surface all public data (that H1 had gathered) in an easy-to-claim flow, give them a huge head start on owning their digital presence, and loading their profile with all their public data (e.g. publications, clinical trials).

Based on a value x effort analysis, we decided on building a free, public browser extension that would automatically display valuable contextual network info on research sites (e.g. PubMed, medical journals). In our early concept testing, this resonated with target users.

MVP Design & Build

Admittedly, I was designing just-in-time for this project. It was fast and furious, and without little time to usability test. We built a simple MVP in a matter of 2 sprints, and I employed the "Fake Door Test" to get signal on interest via email signups. Lastly, we spun up a landing page and drove traffic via paid ads. We utilized the ~50 email signups to help source further customer discovery interviews.

Launch & Test

After launching the MVP, we saw a few hundred users start to use the product. 🎉 Woo! However, we knew that we needed to refine our acquisition funnel because it was a very leaky bucket. So, we went to work with rapid iterative tests.

Three tests are described below with the following framework:

• Goal
• Hypothesis
• Assumptions
• Design Solution
• Success Metrics
• Outcome
  

1) Top of Funnel Adoption

Goal: Educate user, & shorten time to understanding value prop

Hypothesis: By automatically opening a focused tab with instructions/FAQs, we will increase user's understanding of the extension's value, and thereby increase adoption and claimed profiles

Assumption: Users will clickthrough to test it out, users gave the extension permission to read all sites.

Success metric: Measure % of users clicking "Test it out"

Design Solution:

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Outcome: 🎉 Success! Of the cohort who clicked "Test it out", we saw a 15% lift in usage over the next month.

2) Increasing Conversion

Goal: To increase sign-ups and claimed profiles, we employed the classic rate-limit / paywall method.

Hypothesis: By rate limiting users to view 10 articles only, we will increase user sign-up conversion.

Assumption: We assume that users will be convinced of the value of the extension after 10 interactions.

Success metric: Sign-ups via clickthrough on the rate-limited CTA.

Design Solution:

Outcome: 🎉 Big success! We saw a huge spike in signups (~34%) in the following month.

3) Aligning Value Props

Goal: To align users expectations, we set a goal to refine our value proposition on our marketing landing page.

Hypothesis: By refining our hero text & main call-to-action on the landing page, we will increase signup conversion.

Success metric: Sign-ups via clickthrough on the rate-limited CTA.

Design Solution:

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Outcome: 🤷 We didn't see a noticeable change in signups on these changes. We ended up not indexing on any of these options.

Speed matters

• With zero-to-one products, let quality go for the sake of speed.
• Pixel-perfection matters less. Don't get hung up on details.
• Speed forces humility. I grew to enjoy killing ideas fast.

Navigate ambiguity

• When designing a new product, nothing is set in stone.
• Push forward on decisions. Note assumptions and revisit later.

Instrument & Isolate

• Testing too many variables messes up metrics.
• Instrument ASAP. Without it, you are direction-less.