Four Criteria for Choosing a Distribution Platform (Enter and Exit)
Score a new platform on retention, monetizability, value exchange, and scale — then plan your exit before you enter.
- Difficulty
- Advanced
- Time to result
- ~months to results
- Steps
- 5
- Confidence
- 90%
A first-principles scoring rubric for deciding which emerging distribution platform to build on, plus the paired discipline of designing your exit the moment you enter. Balfour lists four entrance criteria ordered by signal strength, deliberately down-ranking vanity metrics, and insists the exit plan is inseparable from the entry decision because the platform will eventually close (Step 3 of the cycle).
Origin
Brian Balfour's distilled criteria from evaluating channels across his career at HubSpot and Reforge, grounded in the iOS-vs-Android monetization asymmetry and the recurring platform lifecycle.
Core principles
- 01Depth of engagement and retention are stronger signals than signups or MAU, which are vanity metrics.
- 02User quality and monetizability can invert raw scale — a smaller, higher-value user base can beat a larger one.
- 03Platforms are a game of arbitrage: whoever best understands and exploits the value-exchange rules gets the edge.
- 04Entry and exit are one decision — you accumulate defensibility during the open window so you survive the close.
How to run it
- 1
Weight retention and depth of engagement first
Judge a platform primarily by how deeply and durably its users engage, not by signup counts or MAU. Look for the 'smile curve' (retention that dips then climbs back up) as an early escape-velocity indicator.
Pro tip The smile curve historically preceded winners like Slack; it's usually the result of a network effect and is very elusive.
Watch out Beware inflated MAU from 'flyby users' — e.g. people who click a Gemini button by accident — which mask weak real engagement.
- 2
Check user quality and ability to monetize
Assess whether the users on the platform are the kind you can actually monetize. A smaller base of high-value users can beat a larger low-value one.
Pro tip iOS is the canonical case: ~30% of devices but ~70% of market dollars, the inverse of Android — bet on the monetizable base.
- 3
Analyze the value exchange and how to arbitrage it
Work out exactly what the platform gives you to incentivize building on it (distribution, context, memory) and how the rules can be arbitraged. The players who best understand and exploit the rules get the edge.
- 4
Then weigh pure scale
Only after the first three criteria, consider raw scale/momentum. If everything else is comparable but one platform has, say, a 200x scale advantage, choose the bigger one. Scale is a tiebreaker, not the lead signal.
Pro tip ChatGPT's ~10x MAU advantage over Claude is why a resource-constrained developer would rationally prioritize it despite loving the alternative.
- 5
Immediately design your exit
Once you're in the game, move straight to planning the exit, knowing the closing step is coming. Build defensibility the platform can't strip: own an important part of the user workflow, accumulate specialized data/context the majors don't have, or create micro network effects.
Pro tip Be early enough that you can figure out the exit strategy along the way, rather than being late and forced to react — the same logic HubSpot applies to opening its data to ChatGPT connectors.
Watch out Outcome-based agent pricing and margins get competed away unless paired with a durable moat (proprietary data/network effects); pricing power alone is temporary.
In the wild
In isolation, giving ChatGPT access to all your data and letting usage accrue there makes no sense. But HubSpot did it anyway — being early, accepting it doesn't yet know its full exit strategy, and committing to figure that out along the way rather than arriving late.
→ Balfour calls it a smart play: better to be early and design the exit in flight than to be late and forced into a weak position.
Common mistakes
Choosing a platform on vanity metrics
Optimizing for signups or MAU rather than retention and monetizable engagement leads you to bet on platforms full of flyby users that will never convert.
Relying on temporary pricing power
Outcome-based agent pricing that looks great today gets undercut as competition and falling compute costs erode margins — unless a data or network-effect moat makes the pricing durable.
Is it for you?
Best for
Growth and product leaders evaluating which emerging AI/distribution platform to invest scarce build resources in
Not ideal for
Teams choosing among mature, well-understood channels where retention/monetization data is already established and no platform-closure risk looms
From the transcript
“the better signal is retention and depth of engagement of the users on this platform than it is like pure kind of user level like…”
“there's some element of like user quality and monetiz and ability to monetize the users on this platform”
“just analyze what the value exchange is, right? So what are they giving you to incentivize you to develop on their platform”
“how are you going to own a important part of the user experience or workflow or you know how are you going to accumulate specialized…”
From the episode
Why ChatGPT will be the next big growth channel (and how to capitalize on it)
Brian Balfour (Reforge)