Support for customers who pay to never think about a ride
I came into Uber Elite wanting to automate support. Interviews with the executive assistants who book most Elite rides changed my mind, and the future-state model became concierge support built on reaching out before something goes wrong.
- Organization
- Uber
- My role
- Program Manager MBA Intern
- When
- Summer 2026
- Result
- Set the customer profile and support expectations for the 1,100-trip NY/NJ Elite pilot
The problem
Uber Elite is an invite-only premium tier. Before we could design how support should work for it, including after the Blacklane acquisition closed, we needed to know who the customer actually was and what they expected. Coming from AI strategy, my starting hypothesis was to automate and use AI wherever we could.
What I found
Most Elite rides are booked by executive assistants on behalf of executives, so the EA was the customer to understand first. I interviewed 15 of them, went through rider reviews, and pulled both into a segmentation framework across four premium travel contexts: executive travel, the EA booking for someone else, airport transfers, and special occasions.
The surprise was how little price came up. What EAs cared about was ease and flexibility. Plans change constantly, and their whole job is making sure their executive never has to think about a ride. That broke my hypothesis. Self-serve tools and deflection push work back onto the EA, which is exactly the work these customers are paying to hand off.
To set the bar, I looked at how luxury brands already serve these same people and landed on five expectations:
- Stays ahead of issues (private aviation)
- Knows who I am (luxury hotels)
- Handles the details (chauffeur services)
- Owns the hard moments (luxury travel agencies)
- Remembers the relationship (fine dining)
Result
The target state moved from automation-first to personalized concierge support built on proactive outreach. Support contacts the EA and rider about a likely delay before they notice it, and checks on an unclear dropoff instead of waiting for a complaint. The framework became the customer profile and support expectations for the 1,100-trip NY/NJ Elite pilot.
What I took from it
How much to automate depends on who the customer is and what they’re paying for. These customers were buying the absence of effort, so a bot they didn’t ask for is the same failure as a self-serve form: it hands the work back to them. I’d use AI where the customer opts into it.