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Stripe CRO Eileen O'Mara on her new role, enterprise demands, and AI

Oct 24, 2023
an illustration of Eileen O'Mara of Stripe surrounded by vertical stripes and digital lights

Photo Illustration: Tiffany Herring/Axios; Photo: Courtesy of Stripe

Stripe's Eileen O'Mara was promoted to chief revenue officer this year, tasked with leading the payment firm's push to serve enterprise customers.

Monday at Money20/20, she sat down with Ryan to discuss her new role, how Stripe is approaching its enterprise opportunity, and how it's experimenting with AI.

This interview has been edited for brevity.

Stripe had a bit of a management change with you moving to CRO and [former CRO] Mike Clayville becoming chief customer officer. Can you explain the change and what you each will do in your new roles?

  • I'm in my fifth year at Stripe. I joined originally to lead the EMEA business and then progressed from there to the global head of sales role. The move to the CRO role was pretty much a natural progression. That was always the intent and the plan.
  • We thought it was the right time also to have a chief customer officer role, and Mike is just an amazing executive in so many ways — but particularly with the customer at the center of everything.
  • From our users' perspective, this is great because you have Mike, who's building out our function and motion around CCO. And I will continue to focus very deeply on the revenue and growth of the organization.

We spoke with [Stripe chief product officer] Will Gaybrick earlier this year, and one of the big messages that he got across was Stripe's shift to enterprise sales and adoption. Where do things stand now?

  • One reason I was excited to join Stripe [was], here is a company that wants to serve all sizes and segments of users — from your upstarts and startups all the way up to your large enterprises.
  • We've organized ourselves and have invested to serve enterprise users in a very intentional way across the business in everything we do. From a product development perspective, from a go-to-market perspective, to how I organize my sales organization and support organization.
  • It's a journey for sure, but we're really happy with the progress that we're making. We have over 100 customers now who do more than $1 billion on the platform annually. So that's a major shift.

How is the enterprise sales process different from Stripe's early focus on startups?

  • It's super-complex, and the sales cycles obviously can be longer. You're often dealing with the architecture and sometimes dealing with big distributed decision-makers.
  • I think what's interesting, though, that we're seeing in the enterprise is that they are being super-disruptive within companies.
  • So when you get into it with these large enterprises, there's tons of urgency, and they are absolutely on a path to deliver a fast ROI and impact to the company in a way I haven't seen in my previous roles.

You're best known for payment processing, but can you talk about the growth of other parts of your business?

  • Our other pillars are revenue and financial automation, and that's really around billing, subscription management, and tax reconciliation. And I suppose we think really that the back office has been unserved.
  • 200,000 users now on that platform are customers, so it's gained a lot of momentum, and it's a big lever for our investment and our R&D strategies.
  • Our third pillar is embedded finance or Banking as a Service, and this provides our customers with the opportunity to open a bank account, to offer capital loans to their customers, and to issue cards from a B2B perspective.
  • That is very complementary to the payment stack and sits in an adjacent way to our payment platform.

The big topic at Money20/20 this year is generative AI and LLMs. How is Stripe using AI?

  • Well, Stripe has always used AI, and it's always been at the heart of our whole differentiated platform.
  • Sigma AI is a new product that users can, using an LLM, just query anything on your financial platform with Stripe. That's super-cool because, within seconds, very complex data is served back to you.
  • Also, on our developer tools, we're using LLM models and programs to provide [co-pilot like] coding tools.
  • Then, at a practical level, we're using it to be more efficient internally. A lot of how we're training our sellers and our go-to-market teams is supported through LLM learning.
  • So we're embedding it throughout everything we're doing, as well as in our customer support services. I would say we've put it in the hands of every [employee].
  • And our consumers and users are looking to us to see what they could do [with AI] and how they could leverage some of the efficiencies from the platform.
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