Why Trust Is FinTech's Most Underrated Growth Lever with Michael Goodbody

Brand investment without demand capture can end up growing your competitors. Michael Goodbody points to a lesson Robinhood learned the hard way before he joined: the company created enormous demand for free trading, and competitors that “just got the last mile right” captured much of the search and demand Robinhood generated. That’s why he builds marketing from the bottom up. He starts by understanding the business, then builds (or diagnoses) the growth and performance marketing engine before layering brand on top, because brand works as a multiplier on what sits beneath it. And it isn’t only about paid spend. Organic and earned media can fill someone else’s funnel just as easily if the capture mechanisms aren’t there.

Brand gets buy-in from technical leaders when it’s presented in the language they already trust: measurement and testing. Michael frames marketing as a complex algorithm with brand as one component of it. A strong brand favorability score means every interaction converts at a better rate, which makes brand a multiplier on performance spend rather than a separate bet. His sequence is to measure the bottom of the funnel first, to a level that builds confidence in you as a leader, then introduce brand layers as components you can test in isolated ways. He also calls the CFO a marketer’s most important partner, since a CEO who loves the campaign won’t help much if the CFO still can’t see the ROI.

A match-market test can isolate a sponsorship’s effect. At Robinhood, the team became the Washington Wizards’ jersey partner in part because the Wizards had the fewest nationally televised games, which kept exposure concentrated enough for a clean test-and-control read. Washington was also one of Robinhood’s top markets, and a rebuilding team kept the cost relatively low. The team oversampled that market in its national brand studies and worked with its data science team on a synthetic control. The results showed a cascade on a lag: awareness of the partnership rose first, then trust (or a closely related metric Michael recalls mapping to trust), then conversion on Robinhood’s subscription product. That proof helped justify more sports sponsorships afterward.

Financial decisions have to win over two sides of the brain. Michael calls them the “monkey brain,” the cognitive side that needs to believe your product is the best option, and the “lizard brain,” which has to actually take the action. That second step is especially hard in finance because so many tasks feel like chores. From his time launching Credit Karma Tax, he compares filing taxes to being told to tidy your room or do your homework. Inertia compounds the problem: most people change banks maybe once or twice in their lifetime, which is why banks historically grew by acquiring each other or spending heavily on top-of-funnel awareness. His approach is to isolate the rational case and the “why now,” then solve them independently and in a connected way.

AI gets work to “okay” quickly but rarely to great. Michael describes it as the wisdom of crowds, so its output tends to revert to the mean. Okay is fine for plenty of work, like the transactional email someone gets after linking an account, but not for the headline copy on your website. His estimate is that a business probably only needs an A-plus on about 10% of what it does, and the leadership skill is knowing where that 10% lives and protecting the time for it. He also flags a growing risk: people are good at recognizing AI patterns and tuning them out, so over-relying on AI-sounding content may make marketing less effective. He’s clear this is a snapshot in time, since the tools keep improving.