Backed by Y CombinatorTwo documents and three sheets that rank onboarding steps by the accounts who stalled and never asked for help, not by ticket volume.
Free download · No account needed
What you get
Pack of 5 files: 2 documents, 3 spreadsheets
Customer Onboarding Content Plan TemplateDrop-off by Onboarding Step
Every step in the funnel, ready for your own reached counts and your own ticket tags.
| Step | Reached | Drop | Tickets | Silent Stall |
|---|---|---|---|---|
| — | — | — | — | — |
| — | — | — | — | — |
| — | — | — | — | — |
| — | — | — | — | — |
Silent stall is the drop count minus accounts that opened a ticket and still didn't get there, the number a ticket-volume ranking cannot see.
Page one for onboarding content planning is almost entirely a product-analytics problem: build a funnel, watch session replays, interview the accounts who dropped off, then ship a UX fix. That is real work, and none of it is content planning. Zendesk's own research puts self-service preference at 73%, yet the standard content backlog for onboarding still gets built off whichever step generates the most tickets, counting only the accounts who ask, not the ones who quietly stop trying.
Loomwell, a fictional workflow-automation company, activated 240 accounts last quarter, and 161 of them, 67.1%, never reached a first production run inside 30 days. Ranking the four onboarding steps by raw ticket volume puts Connect a Data Source first: 92 tickets, more than any other step. But joining that same ticket data to the usage funnel at the account level tells a different story. Build First Automation has only 61 tickets, yet 35 accounts stall there and never open one at all, a higher silent-stall count than Connect a Data Source's 28.
Silent stall is the number a ticket-driven backlog cannot see, which is why Guide Drafts targets Build First Automation and First Production Run first, both uncovered until now. Connect a Data Source already had a guide, and Ticket Deflection shows what it actually did: a 52.4% drop in weekly ticket rate after it published. This pack covers the content half of adoption; a feature that already shipped correct launch messaging still needs someone new to get through it, and every pack installs beside the template library.
The Funnel240 accounts activated in Q2 2026. Each measured over its own first 30 days.
| Step | Reached | Drop | Tickets | Silent Stall |
|---|---|---|---|---|
| 1. Workspace created | 240 (100.0%) | — | 0 | — |
| 2. Connect a data source | 204 (85.0%) | 36 | 92 | 28 |
| 3. Build first automation | 158 (65.8%) | 46 | 61 | 35 |
| 4. Invite a teammate | 130 (54.2%) | 28 | 9 | 26 |
| 5. First production run | 79 (32.9%) | 51 | 34 | 29 |
161 of 240 accounts, 67.1%, never reach step 5. Silent stall is drop minus accounts that opened a ticket for that step and still stalled.
The RankingsSame four steps, ranked two ways. Rank 1 is the step written first.
| Rank | By ticket volume (naive) | By silent stall (actual) |
|---|---|---|
| 1 | Connect a data source — 92 | Build first automation — 35 |
| 2 | Build first automation — 61 | First production run — 29 |
| 3 | First production run — 34 | Connect a data source — 28 |
| 4 | Invite a teammate — 9 | Invite a teammate — 26 |
Connect a Data Source ranks first by ticket volume and third by silent stall. Build First Automation ranks second by tickets and first by silent stall, and it is the one with no guide.
The full funnel, both rankings side by side, naive by ticket volume and actual by silent stall, and the priority order the gap between them produces.
Two guides written for the two uncovered steps, in the voice of someone talking a stuck account through the exact screen and the exact mistake.
Every step's reached count, drop count, ticket count and silent-stall count, joined account by account rather than compared as two separate totals.
Which steps already have a guide, in what format, and which of the highest-priority steps by silent stall still have nothing at all.
The weekly ticket rate before and after a guide actually published, converted to a real rate rather than a raw count, so deflection is a number.
Open the pack in River and send a usage export plus a first-30-day support-ticket export, or download the Word documents and CSV sheets and build the funnel yourself.
River joins the ticket export to the usage funnel at the account level, so each stalled account splits into asked-and-still-stalled or never-asked-at-all.
Drop-off by Onboarding Step carries both rankings, so whichever step the naive ranking would have written for first is checked against the one silent stall actually flags.
River drafts the guide for the highest-ranked uncovered step, then Ticket Deflection tracks whether its weekly ticket rate actually drops once it has run a full quarter.
Yes, with no account, no card and no email gate on the download. Edit with AI is the optional half: send River your own usage and ticket exports, and it ranks your own steps by silent stall. Every pack sits in the template library.
Two Word documents and three CSV sheets, in a zip. The documents open in Word, Pages and Google Docs. The sheets open in Excel, Numbers and Sheets, as real spreadsheets rather than tables flattened into a page.
Because ticket volume only counts accounts that ask. On this pack's own worked cohort, Connect a Data Source gets the most tickets, 92, but Build First Automation has the higher silent-stall count, 35 accounts who stalled there and never asked anything at all.
No, and the two are not competing for the same budget. A UX fix changes the product; a guide helps someone get through the product as it is today. This pack finds which step needs a guide first, using the same drop-off data a UX team already has.
No. Win-loss interviews explain why a specific deal was lost before it ever became a customer. This pack is for accounts that already bought and are stalling somewhere in their first 30 days, a different population and a different fix.
That's a signal for Commitment Guidance, not a content gap. A guide cannot accurately document a feature that has not shipped, and if a draft ever gets ahead of what exists, the mismatch is exactly what Commitment Register is built to catch before a customer notices it first.
It installs this pack as a private workspace and asks for your usage export and your first-30-day ticket export. It rebuilds Drop-off by Onboarding Step from your own accounts, ranks your steps by silent stall, and drafts a guide for the top uncovered one.
Written by
Co-founder & CEO, River
Chandler has spent the last six years working in AI, building tools for millions of users and Fortune 100 companies. In 2025, he co-founded River to build a new kind of operating system for AI agents.
Send your usage export and your first-30-day ticket export. River joins them at the account level and ranks every step by silent stall, not by ticket volume.
Edit with AI