Everyone optimizes the first one. We engineer all six — click to closed-won.
Every point below moves by 20% — nothing heroic, no new spend, no new traffic.
Illustrative model using typical mid-market B2B stage rates. Your real numbers come out of scoring your own chain — and in our experience they're usually worse at Route than this model assumes.
You don't sell e-commerce.
In e-commerce the conversion happens on the page, in the session, by the buyer. In B2B it happens 90 days later, inside a CRM, executed by a human, after 14 touches and 4 internal handoffs. Optimizing the page and calling that conversion optimization is optimizing one-sixth of the problem and reporting on it like it's the whole thing.
It isn't. It's the closed-won. A form-fill lift that doesn't move revenue is a metric you optimized because it was easy to measure.
Four of the six conversion points sit downstream of marketing — routing, sequences, stage discipline, onboarding. Nobody owns them, so nobody optimizes them.
You can't optimize what you can't trace. If spend isn't tied to revenue by stage, every win is a story. We instrument first, then optimize. That order is not optional.
Not six services — six points in one chain. You find out which one costs you the most, and we fix that one first.
Why it leaks: Offer/intent mismatch, form friction, mobile drop-off, traffic buying the wrong intent.
What we do: Page and offer architecture, progressive forms, intent-matched landing paths, budget reallocated against downstream conversion — not CPL.
Why it leaks: No enrichment, duplicate records, scoring nobody trusts, good-fit leads misclassified as junk.
What we do: Real-time enrichment, dedupe, fit + intent scoring, explicit MQL/SQL definitions both teams sign off on.
Why it leaks: A qualified lead sits in a queue for four hours. The SLA exists in a doc, not in the system. Largest and cheapest-to-fix leak in most B2B funnels.
What we do: Sub-5-minute routing, ownership rules, enforced SLAs with escalation, capacity-aware round robin, alerting that fires at the rep.
Why it leaks: Booked meetings that never happen. No-shows treated as bad luck instead of a fixable system output.
What we do: Multi-touch confirmation sequences, reschedule automation, no-show recovery plays, pre-call context delivered to the rep.
Why it leaks: Stages defined by feeling instead of exit criteria. Deals parked in Stage 3 forever. Forecast is a negotiation, not a calculation.
What we do: Stage realignment with hard exit criteria, deal hygiene automation, stall detection, next-step enforcement, forecast built from behavior.
Why it leaks: The most expensive conversion failure in the business — you already paid to acquire them and they never activate. CAC stays high, NRR flatlines.
What we do: Onboarding conversion instrumentation, activation triggers, upsell signals wired to usage, early churn detection.
Every conversion point instrumented, every stage visible, spend tied to revenue by source. This is what separates conversion optimization from conversion opinion — and it's why our results survive a CFO reading them.
Conversion optimization isn't a project with an end date. It's an operating cadence.
An 18-metric scoring pass across all six points. Every leak sized in dollars. Output: a ranked leak list and a 90-day roadmap naming the plays that fix each one.
Before we change anything, we make it measurable. Tracking at every stage, attribution wired end to end, reporting live — so week-8 lift is a number finance can reproduce.
The pod runs the highest-dollar plays in one-week sprints. Not a strategy deck — routing rules deployed, stages rebuilt, sequences live, dashboards shipped.
Weekly re-scoring. Next-highest leak, next play. The chain gets measurably better every sprint, and the compounding math starts working for you instead of against you.
The question is where they stop, and what they can prove.
| Who | What they optimize | Where they stop | What they can actually prove |
|---|---|---|---|
| CRO / web agencies | The page | The form fill | Form conversion rate. Rarely a revenue number. |
| Demand gen agencies | The click | The MQL handoff | CPL and MQL volume. Both can rise while revenue falls. |
| Sales consultants | The rep | The conversation | Anecdote. No stage-level data to isolate the lift. |
| RevOps consultants | The tool | The configuration | That the system works. Not that conversion improved. |
| An internal hire | What already exists | Their own bandwidth | Whatever one person can hold in their head — and it leaves when they do. |
| JayOh | All six conversion points | Attributed closed-won revenue | Conversion rate by stage, pipeline created, sales cycle, CAC — traced to source. |
100+ engagements since 2016. The plays exist because we've run them, counted them, and measured what they returned.
Paid, lifecycle, routing, CRM, attribution, analytics — one team. Nobody hands your conversion problem across a vendor boundary.
Same team designs, builds and runs it. Conversion optimization dies in the handoff between the deck and the deployment. We removed the handoff.
The RevOps Brain maps your GTM architecture so change is safe and the knowledge doesn't walk out the door. It compounds.
Hold any conversion firm to this. Most can show you a lift at one point.
| Conversion point | What we've measured |
|---|---|
| Click → Form | 25% improvement in landing page conversion · 35% reduction in cost per lead · 7:1 ROAS on a launch with CAC under $10 |
| Form → Qualified | 90% reduction in data errors · 45% increase in MQLs from enhanced targeting · MQL→SQL conversion doubled from paid |
| Qualified → Contacted | 60% increase in a lead's likelihood to convert into a paying customer · sub-5-minute routing as standard |
| Contacted → Meeting | 93% demo attendance rate · 80+ SQLs from a single 30-day ABM program |
| Meeting → Opportunity → Won | 3.5× demo-to-proposal lift · sales outcome conversion 46% → 50.5% · 35% shorter sales cycle · 20% faster cycle from defined MQL/SQL criteria |
| Won → Onboarded → Expanded | 21-percentage-point increase in form-to-completed-onboarding conversion · $100K MRR added from PLG initiatives in under 3 months |
| Measure (all points) | 28% improvement in forecast accuracy · 5.8 hours/week/FTE recovered · 33% faster optimization cycles |
| End-to-end | 35% lift in ad-click-to-customer conversion · $2.2M pipeline in the first 90 days · ARR doubled $8M → $16M after GTM rebuild · 20% lower CAC |
Anonymized results across B2B SaaS and PE-backed portfolio engagements. Named references available under NDA.
Then you're optimizing step one, and that's real work — 3% to 3.6% is money. But if 35% of the leads that page generates aren't contacted inside your SLA, you paid to fill a leakier bucket faster. We'd keep your CRO program and fix the five points behind it.
At 7 deals per 10,000 visitors, doubling traffic costs you double. Tripling conversion costs a fraction of that and improves every future dollar of spend forever. More leads is the most expensive way to fix a conversion problem.
Are they architecting all six conversion points, or maintaining the system that already exists? One person can't cover paid, lifecycle, routing, CRM and attribution at depth. We work alongside internal teams — they keep ownership, they get a pod behind them.
Because we instrument before we optimize. Baseline conversion rates at every stage are captured in the first 30 days, and every play is measured against that baseline. If we can't prove it, we don't claim it.
Usually it broke in the gap between the recommendation and the deployment. Someone delivered a conversion audit and left your team to implement it. We don't do strategy-only work — if we can't build and operate it, we're the wrong firm.
Scorecard and roadmap on day 14. First play live in week one of the install. First measurable conversion movement by week four. Guaranteed in writing at day 60 and day 120.
We onboard a limited number of clients at a time.
Bring the numbers you have. We'll score all six conversion points against 18 metrics, size every leak in dollars, and name the plays that fix them — highest-dollar leak first.
First call is a conversation about your chain, not a pitch. If the fix isn't ours, we'll tell you that too.
From click to close — we own the system.
We engineer growth systems. JayOh builds the RevOps architecture, GTM execution and data infrastructure that turn messy revenue operations into predictable pipeline for B2B SaaS and PE-backed teams.
