About this book
Most growth books are written backwards. Someone succeeds, then constructs a framework that explains the success, then presents the framework as the cause. The reader gets a theory that has never been tested against a case where it didn't work, because those cases were edited out.
This book is written from a single complete dataset: every day of search data from the first day a product was indexed to the day it reached 100,000 users, plus the behavioural analytics for the same period, plus the version-control history showing exactly what was built and when.
That lets me do something unusual: check the advice against the numbers, including where the numbers contradict the advice. They do, in three important places, and those three chapters are the most useful in the book.
The evidence base
The case is a browser-based document tool called ihatepdf, built alone, launched 24 December 2025, at 100,542 unique users on 5 August 2026 and passing 100,000 shortly after. Every figure quoted comes from one of three sources:
- Google Search Console, 25 Dec 2025 – 28 Jul 2026: 224 days, 42,320 clicks, 1,228,913 impressions, 1,000 queries, 160 pages.
- Microsoft Clarity, same period: 132,748 sessions, 100,542 unique users, plus performance and interaction data.
- The git history: 181 commits, dated.
Acquisition spend across that period: zero. No ads on any platform, no paid links, no sponsorships, no agency, no paid directory placements.
What this book is not
It is not a promise that you will get the same result. It is one case. A single case can prove that something is possible and can show you mechanisms, but it cannot tell you how often those mechanisms work. Where I am generalising beyond what one dataset supports, I say so.
It is also not a monetisation book. This case reached 100,000 users and very little revenue, and Chapter 30 is honest about why those are different problems and how the choices in this book make the second one harder.
How to read it
Part I is about what to build. Part II is about how to make it findable. Part III is about reading your own numbers, and is the part most people get wrong. Part IV is about the ceiling you will hit. Part V is the bill.
If you only read three chapters, read 3, 4 and 12. They are the ones where the data disagreed with what I believed.
Every chart in this book is drawn from the exports listed in Appendix A. Where a chart would have been prettier than the truth, you get the truth. There is a chapter whose central number is nine sessions, and a chapter that declines to draw its own obvious conclusion because the data does not support it.
Three ways to read this
The book is ordered as an argument, front to back. But most people arrive with a specific problem, so here are three shorter routes. Each is self-contained.
"I have no traffic at all."
Chapters 1 → 2 → 6 → 7 → 10 → 12. Is there demand you can reach; what the first ninety days actually look like; how to decompose your product into entry points; the page specification field by field; why your pages may be invisible; and why you must not judge any of it for a quarter. Then Appendix B, and start.
"I have traffic but I'm stuck."
Chapters 17 → 20 → 21 → 22 → 24. What high impressions with no clicks really means; the diagnostic that separates an on-page problem from an authority problem; why you get linked; what actually earns links versus what only moves a vanity score; and the outreach mechanics. Run the audit tool first. It will tell you which of these applies to you.
"I have traffic that doesn't convert."
Chapters 18 → 17 → 18 → 14. The half of the funnel search data cannot see; the dead-click finding; the device split; and why your falling click-through rate is probably arithmetic rather than a problem.
And three chapters worth reading whatever brought you here: 3, 4 and 12. They are the ones where the data contradicted what I believed, and they are the reason the rest of the book is shaped the way it is.
About this book
About this book is part of How to Grow Your SaaS to 100K Users Without Spending on Ads, a playbook on taking one product from zero to 100K+ users on search alone, with nothing spent on advertising. Every claim in it is checked against the real data, including the three findings that contradicted the author.
Continue reading
Free tools that implement this book
- Search Console Analyzer: Drop your export, get a verdict
- SERP Audit: Paste a URL, get the fix list in priority order
- Schema Generator: Valid JSON-LD, with the guard rails on
- SERP Preview: Pixel-accurate, not character-counted
- Position Value Calculator: What is rank 4 actually worth?
- Schema Inventory: Which structured data is on which page
- Internal Link Graph: Which pages nothing points at
- OG Image Generator: And what it looks like once each platform crops it
- Noise or Signal: Did that actually do anything?
- Programmatic Set Analyzer: How many of those pages actually work?
- Crawler View: What lands in the HTML, before anything runs
- Log File Analyzer: What Googlebot actually crawled