ExpertsFMTom Digan & Greg Stewart - Building the World’s Best Fitness App - [Invest Like the Best, EP.454]
Invest Like the Best with Patrick O'Shaughnessy · January 13, 2026
5 Selected Lessons:
framework · 2 case · 1 heuristic · 1 reasoning_pattern · 1
Workout-completion as the single North Star metric for prioritization
Source
Invest Like the Best with Patrick O'Shaughnessy — Tom Digan & Greg Stewart - Building the World’s Best Fitness App - [Invest Like the Best, EP.454] (January 13, 2026) · at 29:19 ▸
When this applies
when a team has many plausible feature ideas and limited capacity to build them all
The takeaway
Anchor all prioritization decisions to a single north-star metric tied directly to the core value delivered, and require every proposed addition to have a clear thesis for moving that metric before building it.
Why it works
Defining one outcome metric that is causally tied to customer value and retention gives a clear, objective filter for every proposed addition, preventing scope creep driven by novelty or internal interest.
One level up
Clarity of a singular success metric is what makes ruthless prioritization possible; without it, prioritization becomes subjective and political.
Where it stops holding
This stops working when the chosen north-star metric is a poor proxy for actual value delivered, leading the team to optimize the metric rather than the customer's real outcome.
Detail
procedure:
- Define one north-star metric tied to actual customer value (workout completions, not payment)
- Require a thesis that any new feature will increase that metric before building
- Don't guess — absorb all member information and look for patterns that reveal what moves the needle
- Build one thing fully rather than many things partially
- Repeat the cycle
benchmarks: {}
rationale: Solving for actual usage/completion, not just payment, captures true retention-driving value.
In their words
We're solving, not forgetting you to pay one. We're solving for you to actually complete workouts with Ladder. And what can we go build to go improve the odds of you doing that and staying with us?
Dissect winning content down to granular variables, build in-house creative capability
Source
Invest Like the Best with Patrick O'Shaughnessy — Tom Digan & Greg Stewart - Building the World’s Best Fitness App - [Invest Like the Best, EP.454] (January 13, 2026) · at 43:58 ▸ · at 48:44 ▸
When this applies
when trying to systematically improve the performance of any creative/content-driven channel
The takeaway
Decompose every successful outcome into its granular, controllable variables and own the iteration loop in-house rather than outsourcing to an agency with slower feedback cycles.
Why it works
Granular post-mortems on what specifically worked (wording, wardrobe, setting, hook structure) convert tacit, lucky wins into a repeatable, improvable system, and in-house ownership keeps the iteration loop fast enough to compound.
One level up
Speed of the learning loop is itself a competitive advantage, and outsourcing a fast-iterating function to an external party breaks that loop.
Where it stops holding
This stops working when the function requires specialized expertise/scale that can't realistically be built in-house, or when the iteration cycle is naturally slow regardless of ownership.
Detail
procedure:
- Start test accounts from scratch with no existing following
- Create content with people who know the customer intimately (coaches), not generic marketers
- Analyze every granular variable in winning posts (wording, hooks, setting, wardrobe)
- Hire full-time in-house creators rather than agencies to keep iteration speed high
benchmarks: {"growth_example":"one account went from zero to 250,000 followers in 45 days organically"}
rationale: Deep customer insight (from app store review analysis) combined with fast internal iteration outperformed agency-mediated content creation.
In their words
And all of the insights of that come from knowing your customer. It's not, hey, we magically figured out TikTok. We did. But our edge was we knew our customer insight and out.
Identify the real competitor by watching actual substitute behavior, not category labels
Source
Invest Like the Best with Patrick O'Shaughnessy — Tom Digan & Greg Stewart - Building the World’s Best Fitness App - [Invest Like the Best, EP.454] (January 13, 2026) · at 1:05:01 ▸
When this applies
when stakeholders assume the obvious same-category player is the real competitive threat
The takeaway
Determine your real competitor by observing what customers actually do as a substitute, not by assuming it's the most visible same-category brand.
Why it works
The true competitive alternative is whatever behavior customers actually substitute toward when your product doesn't exist or doesn't satisfy them, which may be a completely different category (free content on YouTube) rather than the nearest branded competitor.
One level up
Competitive analysis should be behaviorally grounded in customer alternatives, not structurally grounded in industry taxonomy.
Where it stops holding
This stops working when customer substitute behavior is fragmented across many small alternatives, making no single 'real competitor' identifiable.
Detail
approach: Ask what customers actually do when seeking the same outcome outside your product.
signals:
- Investors reflexively name the most visible same-category brand as 'the competitor'
- Actual customer behavior (typing into YouTube search) reveals the real substitute
rationale: YouTube, not Peloton, is Ladder's real competitor because that's where customers go for free workout content.
In their words
We learn, you know, investors come in and say, Who's your biggest competitor? Is it Peloton? It's like, no, it's YouTube by far. It's not even close.
Don't let one investor's product opinion override member data
Source
Invest Like the Best with Patrick O'Shaughnessy — Tom Digan & Greg Stewart - Building the World’s Best Fitness App - [Invest Like the Best, EP.454] (January 13, 2026) · at 29:19 ▸ · at 36:16 ▸
When this applies
when any single stakeholder — investor, advisor, loud customer — pushes a specific product decision
The takeaway
Treat any single piece of feedback, regardless of the source's authority, as one data point to be tested against the full customer base, never as a directive.
Why it works
Any single person's feedback reflects their own narrow use case and bias; only aggregated, empirically tested signal across many customers reveals what actually moves the core metric.
One level up
Authority of the source should never substitute for empirical validation of a decision.
Where it stops holding
This stops working when there is no mechanism to cheaply test ideas with real customers before committing resources, making empirical validation too slow or costly.
Detail
rule: Don't listen to any one person — investor or otherwise — on product; test every suggestion against your member base before acting.
threshold: A single piece of feedback counts as one data point, not a mandate.
rationale: No one person is the source of truth; empirical testing with the broader customer base reveals true priorities.
In their words
Well, I can tell you number one is don't listen to investors on product feedback. That is by far number one. But for us, it's just two things. It's prioritization, ruthlessly prioritize.
Selling conviction with no product when raising emergency capital in a crash
Source
Invest Like the Best with Patrick O'Shaughnessy — Tom Digan & Greg Stewart - Building the World’s Best Fitness App - [Invest Like the Best, EP.454] (January 13, 2026) · at 23:20 ▸
When this applies
when fundraising during a crisis with no finished product or proof points to show investors
The takeaway
In the absence of evidence, sell your own skin-in-the-game and conviction as the proxy for the thesis; a trusted referral chain can substitute for due diligence entirely.
Why it works
When there is no product or data to evaluate, investors substitute trust in the founder's personal conviction and willingness to put personal capital at risk as the signal of quality.
One level up
Relationships and demonstrated personal commitment can temporarily substitute for data when data doesn't yet exist, but this is a scarce, personal-trust-dependent resource, not a repeatable system.
Where it stops holding
This stops working when the founder lacks a credible trust network or when investors require independent evidence regardless of relationship.
Detail
situation: Needed cash immediately with no new product to show; existing product was being shut down.
decision: Wrote a personal check into the company himself and used a referral through investor Brent to reach 'Bill,' who invested based purely on Deegan's personal involvement and urgency.
outcome: Bill matched Deegan's own check without seeing a deck or knowing what the new product was, funding was wired next day.
lesson: Personal skin-in-the-game and trusted referrals can unlock funding when there is literally nothing else to sell.
In their words
The point there is, in particularly those early days, it's important to have skin in the game in whatever way you can. For us, it was about being able to show that level of conviction and urgency.