Beton + Stripe
Revenue events as first-class signals
Stripe billing events as a signal source. Trial-to-paid conversions, plan upgrades, payment failures, churn — joined with product behavior for sharper signals.
Stripe events as direct revenue signals
Most of Beton's signals work through behavioral inference — user did X, X correlates with conversion, route a signal. Stripe is different. Stripe events are direct revenue evidence: the customer paid, the customer downgraded, the customer's payment failed. There's no inference layer to backtest because the event itself is the outcome. What Beton adds is the pattern detection across many Stripe events over time, and the routing of those events into the CRM with enough context that the AE or CSM can act on them.
Beton connects to your Stripe account via a restricted-permission API key (read access to customers, subscriptions, invoices, and events). The agent watches the event stream and surfaces patterns that matter for revenue ops: customers approaching usage limits, customers with rising MRR, customers who just had a failed payment, customers who downgraded after a sustained period of growth.
Patterns Beton typically surfaces in Stripe data
- Usage approaching plan limits — for usage-based pricing, the moment a customer crosses 70%, 80%, or 90% of their tier allotment is the most leverageable expansion moment of the quarter. The customer's decision window is narrow; if no one reaches out, they downgrade or work around.
- MRR growth trajectory — customers whose monthly spend is trending up consistently for 60+ days are usually in business-growth mode, and that's the population most receptive to enterprise-tier conversations.
- Payment failure patterns — a single failed payment is noise; a pattern of failed payments is a churn precursor. Beton flags the pattern so collections or CS can intervene before the subscription cancels.
- Plan downgrades — the downgrade is usually the announcement of churn arriving in 60–90 days. Catching the downgrade in the CRM, with context about what the customer's usage looked like before, gives the CSM a chance to intervene.
- New subscription patterns — first-purchase customers segmented by which plan they entered on, time-to-first-payment after trial, and which entry path correlates with retention.
Why Stripe pairs especially well with PostHog
The two most useful signal pairs Beton routes are PostHog × Stripe combinations. PostHog tells you the customer is hitting feature gates on the next plan tier; Stripe confirms they haven't yet upgraded. PostHog tells you the customer's usage is accelerating; Stripe confirms they're still on the starter plan. PostHog tells you a power user has dropped engagement; Stripe confirms the subscription is approaching renewal. None of these signals are useful in isolation — together they're the actual leading indicators of expansion or churn.
When Beton routes a Stripe-derived signal to the CRM, the payload includes the relevant Stripe metadata — current plan, MRR trajectory, recent invoice history, payment health — so the AE or CSM doesn't have to context-switch to Stripe to understand what they're looking at. The signal arrives self-contained, in the workflow they already use.
What stays out
Beton never stores card numbers, never accesses payment method details beyond what's required to identify a payment failure, and never modifies anything in your Stripe account. The connection is read-only against the standard Stripe API, and the API key can be revoked at any time without affecting any other system.
Connect with a restricted Stripe API key, point it at your CRM, and the first set of plan-ceiling-approaching signals usually flows in within a few minutes.
How It Works
Add a Stripe restricted key
Generate a restricted API key (read-only on customers, subscriptions, invoices, charges, events). Paste it into Beton — no webhook setup required.
Beton joins billing with product behavior
Subscription state changes, plan switches, failed charges, and trial conversions are joined with PostHog/Postgres events on email or domain. Signals carry both contexts.
Backtest revenue-grade hypotheses
Hypotheses like "trialists who hit feature X within 3 days convert at Y%" are validated against actual paid conversions in your Stripe history.
What Stripe sees
{
"signal_type": "trial_about_to_convert",
"confidence": 0.88,
"sources": ["stripe", "posthog"],
"account": { "email": "jane@acme.com", "domain": "acme.com" },
"stripe": {
"subscription_status": "trialing",
"trial_end": "2026-05-04",
"plan_amount": 4900
},
"product_events": ["workspace_invited_teammate", "api_key_created", "workflow_published"]
}Features
- Restricted-key OAuth — read-only, scoped, revocable
- Subscription, invoice, charge, and customer events ingested
- Auto-joined with product analytics on email and domain
- Trial-conversion and expansion hypotheses validated on real revenue outcomes
- Failed-payment and downgrade signals route to CRM as churn-risk
- Works with Stripe test mode for staging environments
Use Cases
- Detect trial users likely to convert before the trial ends
- Spot accounts about to upgrade based on usage + billing trajectory
- Catch payment-failure churn signals and route to CS
- Validate "feature X drives expansion" claims against actual MRR data
Ready to connect Stripe?
Start detecting revenue signals and routing them to Stripe in minutes.
Pairs well with
Stripe is the data source — pair it with a destination to actually route the signals Beton finds.
Stripe + Attio
Tie billing events to Attio accounts so RevOps sees expansion and downgrade risk in the same pane.
Attio integration →
Stripe + Apollo
Use revenue-side signals (upsell ready, churn risk) to prioritise Apollo outbound and renewals.
Apollo integration →
Stripe + Webhooks
Forward billing-derived signals to your billing analytics, finance ops, or alerting stack.
Webhooks integration →