Alex Lawrence-Richards

Case Studies

About

Alex Lawrence-Richards

Case Studies

About

Alex Lawrence-Richards

Nivelo

Nivelo

Cameo

Peloton

About

Cameo

Tools for Talent Success

Role

Lead Product Designer

Responsibilities

End-to-end UX + UI for iOS and Android, design systems, prototyping, user research

Timeline

Q2 2022 – Q4 2022

Cameo enables fans to request personalized videos from their favorite talent. I redesigned the talent tools to make request management faster, more intuitive, and scalable for talent with high request volumes.

Cameo

Tools for Talent Success

Role

Lead Product Designer

Responsibilities

End-to-end UX + UI for iOS and Android, design systems, prototyping, user research

Timeline

Q2 2022 – Q4 2022

Cameo enables fans to request personalized videos from their favorite talent. I redesigned the talent tools to make request management faster, more intuitive, and scalable for talent with high request volumes.

Outcomes

10%

Increase in new talent onboarded without 1:1 rep support within the first month

7%

Increase in fulfillment rates within the first two months

20%

Decrease in unfulfilled orders, driven by improved request visibility and talent-side tooling

42%

Decrease in time between talent account creation and receiving their first order

Previous Experience

Before the redesign, the talent app was a collection of loosely connected screens. Managing requests, setting up a profile, and tracking performance all lived in separate flows, with little guidance or prioritization. This fragmentation created extra work for talent reps and left many talent unsure how to manage their Cameo presence effectively.

  • Search

  • Fan Clubs

  • Requests

  • Activity

  • Profile

  • Profile

Problem

Cameo’s legacy tools couldn’t keep up with high-volume creators. The “Tinder-style” card interface made requests slow to manage, while fragmented workflows for requests, profiles, and performance tracking left creators with no way to self-manage or improve quality. Talent reps handled most onboarding and troubleshooting, creating bottlenecks that hurt completion rates.

Goals

  • Replace the card UI with a scalable, high-density view for faster request management

  • Unify requests, profiles, and performance tracking into a single interface

  • Give creators tools to self-manage and improve quality without relying on reps

  • Streamline onboarding and support flows to reduce manual troubleshooting

Problem

Cameo’s legacy tools couldn’t keep up with high-volume creators. The “Tinder-style” card interface made requests slow to manage, while fragmented workflows for requests, profiles, and performance tracking left creators with no way to self-manage or improve quality. Talent reps handled most onboarding and troubleshooting, creating bottlenecks that hurt completion rates.

Goals

  • Replace the card UI with a scalable, high-density view for faster request management

  • Unify requests, profiles, and performance tracking into a single interface

  • Give creators tools to self-manage and improve quality without relying on reps

  • Streamline onboarding and support flows to reduce manual troubleshooting

Key Features

Request Hub

Open requests appear in a single, high-density view for quick scanning, while completed, expired, and other requests have their own sections to maintain focus.

Performance Insights

Visualization to link performance to visibility and bookings, highlighting trends, and flagged areas for improvement.

Self-Service Onboarding

A scalable, in-product setup flow that helps talent get live quickly, set the right price, build compelling profiles, and generate early demand without relying on talent reps.

Takeaways

What Worked

  • Centralizing requests into an inbox reduced decision friction and helped talent triage quickly

  • Color-coded urgency and clear request types improved prioritization and time-to-fulfillment

  • Light-touch nudges, filters, and affordances gave talent more control without overwhelming them

What Didn't

  • Some talent still preferred having a dedicated talent rep, especially high earners

  • Cameo’s priorities didn’t always align with talent motivations. Some valued speed and scale, while others often prioritized personalization and performance quality.

How we responded

  • Iterated on onboarding flows and microcopy to highlight underused features

  • Worked with Talent Reps to segment talent by behavior and needs, allowing for more tailored rollout support

  • Continued to refine request UI to balance speed and personality, without making fulfillment feel transactional

Takeaways

What Worked

  • Centralizing requests into an inbox reduced decision friction and helped talent triage quickly

  • Color-coded urgency and clear request types improved prioritization and time-to-fulfillment

  • Light-touch nudges, filters, and affordances gave talent more control without overwhelming them

What Didn't

  • Some talent still preferred having a dedicated talent rep, especially high earners

  • Cameo’s priorities didn’t always align with talent motivations. Some valued speed and scale, while others often prioritized personalization and performance quality.

How we responded

  • Iterated on onboarding flows and microcopy to highlight underused features

  • Worked with Talent Reps to segment talent by behavior and needs, allowing for more tailored rollout support

  • Continued to refine request UI to balance speed and personality, without making fulfillment feel transactional

Copyright © 2025 Alex Lawrence-Richards

Copyright © 2025 Alex Lawrence-Richards