Case Study: Bolt OU

New Demand for Ridehailing

Overview of my work at Bolt:

I was the researcher for Bolt’s most business-critical vertical: ride-hailing. Operating within a high-velocity, low-margin, global mobility ecosystem and two-sided marketplace, my scope covered a roadmap for millions of users across diverse international markets. I lead research that bridged the gap between digital interface, the real-world operational service quality, and our customer’s lives.

This case study:

This case-study outlines a project with Bolt’s New Demand team wherein we introduced and expanded our standard service offering (rides), to become a courier-like service where customers could send packages (without actually traveling with it).

What I did:

  • Identified opportunities for both service and product improvement after our initial release.

  • Evaluated pre/post launch sentiments shifts from app releases.

  • Evaluated product-market-fit and identified the top-needs for creating a business-focused service model to capture market.

  • Sized the opportunity/risks and go-to-market strategies for new service add-ons such as “door to door delivery”.

My work was integral in identifying the service and app pitfalls in our initial release, prioritizing fixes, and discovering/prioritizing our roadmap for expanding our service beyond consumers, to segments like businesses looking to send supplies, samples, products, etc.

Bolt Send: Expanding courier services to ride-hailing.

  • Identifying areas for improvement in general (qualitative interviews)

  • Evaluating pre/post launch sentiment shifts in the first UX update

  • Evaluating PMF, Identifying and prioritizing opportunities for top-users; identifying who these users are, their unique use-cases (e.g. why are they using Bolt Send multiple times a day?), and what they need to make Bolt Send really work for them and to improve PMF.

    • Interviews

    • Survey

      • MaxDiff

      • Willingness to Pay for door-to-door

      • “Satisfaction” and PMF/reliance

      • Identifying use-cases (what they are sending and why)

  • Sizing the opportunity and functional requirements for offering door-to-door service from both a supply (driver/courier) and demand (customer) perspective to find an optimal balance per market.

    • AI-moderated interviews

    • Surveys

    • Why we started with Drivers/Couriers on this one, instead of customers… Drivers have a more hollistic view of the landscape (they can actually tell us about 100 orders they’ve done, instead of just 3). They can tell us about what they experience in terms of expectations of D2D and what that all means (what is “the door” in each market?) Without supply, the demand gets killed anyway — it doesn’t matter if we release “door to door” if drivers don’t accept those orders or refuse to do it…

What do you do when the product/service is clearly lacking… there are lots of ideas on how to improve it (based on user interviews and competitor analysis) but which ones do you do first? How do you know which ones to prioritize?

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