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Know your guest

Hospitality is central to restaurants, so lacking those features can be a nonstarter for sales. We believe restaurants will increase their level of hospitality if Yelp provides robust guest details.

Role

Product designer

Timeline

3 months

Goals

Inform to improve hospitality

Provide hosts with details about their guests, when they most need it.

Center workflow efficiency

Reducing the number of clicks to complete an action is key for hosts’ workflows.

The experience

I designed the experience in three stages. This allowed our team to ship and then test results between each release.

Search for guests

Autofill guest phone number as host adds them to the waitlist.

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Surfacing guest details

For the v2 experience, I designed how guest details are surfaced to hosts and the corresponding editing interactions.

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Download Guest Directory

For the v3 experience, I designed a directory of guest details, allowing owners to analyze data for marketing campaigns.

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Process

1) Reviewed business needs

Guest details is a required feature from a customer POV -> P0 urgency on the team

2) Initial user conversations

Informed the mental model powering the design + what info to show hosts & when.

3) Scoping with PM & eng

Used the research to draw out a vision for this product & used this to scope the work.

4) Design & prototype

Designed, prototyped, and speced out the logic of this experience.

5) Showed prototypes to users

Finalized the logic by reviewing prototypes with key users.

6) Finalizing & handoff

Documented newly-created components & wrote out the details of implementation.

Business & user needs

A business need identified the problem area, and user needs informed how to tackle and design the solution.

Business considerations

The team reviewed product feedback: Not having guest details was a frequent non-starter for customers when considering joining Yelp. This feedback identified a major need.

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User conversations

Created a discussion guide and led interviews with owners and hosts. This informed what guest details hosts want to see & when + how to display these details in a way that matched their mental models.

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Scope of project

I worked with my PM to scope the work to maximize the cost/benefit tradeoffs. This stage gave constraints & boundaries to work within.

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Immersion

Understand the business

By this stage, I understood the business need to increase sales via introducing this new feature.

Understand the hosts (users)

I additionally went to restaurants to see hosts in action and talked with them about their needs.

Designing & prototyping

From the previous steps, I had immersed myself in the business & user needs. This allowed me to now make informed design decisions. But, because this experience was a major lift, I needed to further derisk it by creating a prototype to validate further.

Refined the designs

The designs needed to be ready to show to our users for testing, so they needed to feel as real as the final product would, despite being limited due to prototyping constraints.

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Intense saving logic

Explored various logics for saving a guest's detailed. Took detailed notes for presentations & specs.

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User testing with prototypes

Presented prototypes to restaurant managers for feedback. Most importantly, this informed our saving logic choices.

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Derisked critical open questions

With competitive analysis

Compared our designs to our competitors to ensure that we weren't missing major concepts that our competitors already had.

With user testing

Shared prototypes with our users for feedback in moderated sessions. Getting feedback early further derisked our decisions.

Refinement & engineering handoff

Now that I had a derisked direction and a base-line of designs, I refined the designs further by designing and contributing new components back to our designs system. I also detailed specs for handoff to our eng team.

New and rethought components

Updated components to better utilize limited vertical space and introduced brand new components

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Details that work for users

Leveraged competitive analysis, Yelp's component library, and user interviews to optimize interactions to meet hosts' needs