Every content marketing case study starts after it worked. This one is from month 6: roughly 50 articles, 3 frameworks, 828 search impressions, and 14 clicks. I’m publishing the full Search Console export because the content marketing results timeline everyone quotes is built entirely from survivors, and this is more useful to anyone currently building a property from zero and quietly panicking.
14 clicks.
That’s what organic search sent this site between 27 February and 29 July 2026, across roughly fifty published articles and three frameworks. Not fourteen thousand. Fourteen.
I write about content strategy for a living, I’ve built content functions that contributed to 48% marketing-sourced pipeline, I publish an AEO/LLMO framework about making content discoverable, and yet my own domain, at month six, produced fourteen.
Every case study you’ve read in this field begins after the hockey stick, but mine starts here, because the useful information is in the part everyone deletes.
The unframed numbers
Straight from Search Console, 153 days, web search only.
| Metric | Six-month figure |
|---|---|
| Clicks | 14 |
| Impressions | 828 |
| CTR | 1.69% |
| Average position | 18.6 |
| Days with at least one click | 11 of 153 |
| Days with zero impressions | 42 |
| Distinct queries generating impressions | 58 |
| Queries that produced a click | 1 |
| Pages that produced a click | 6 of 91 |
The single query that produced a click was my own name.
What I expected, and where that expectation came from
I expected more, and the source of that expectation is the lesson.
It came from environments that don’t transfer. Every content function I’ve run has been inside a company with an existing domain: years of accumulated links, established crawl history, brand search volume, and other people’s work compounding underneath mine. At Cleanwatts I grew organic traffic 22%, at Critical Software it was 28% year on year. Those numbers arrived fast enough to report quarterly, and I carried an unexamined assumption that the mechanics were about the content.
They weren’t. Those results were the content plus a domain that already had standing.
The second source was the sheer volume of case studies that start at month twelve, or month eighteen, or whenever the curve turned. Read enough of those and you internalise a ramp curve that doesn’t exist, because you’re only shown survivors. Nobody publishes month six from a new domain, so everyone building one is calibrating against a sample that systematically excludes them.
How long a new domain takes to rank
Ahrefs tracked a million URLs first seen by their crawler and checked how many reached Google’s top 10 within a year. Only 1.74% did. Filtered to English pages that rises to 6.11%, which still means roughly 94 in every 100 pages don’t reach page one inside twelve months. The same study found 72.9% of current top-10 pages are more than three years old, and the average #1 result is five years old, up from two years in the 2017 version.
Ranking is getting harder for new pages rather than easier, with only 13.7% of current top-10 pages under a year old, down from 22%.
Separately, research across the SEO press suggests close to 85% of content from newly launched sites doesn’t break into the top 50 within six months.
Measured against that, fourteen clicks at month six looks less like underperformance and more like the modal outcome. I’d been judging myself against a curve that describes the luckiest 1.74%.
Domain authority is the strongest single predictor of how fast a page ranks, and it’s built from accumulated links, crawl history, and time. A six-month-old domain has none of those by definition.
Why impressions but no clicks is a position problem rather than a demand problem
The export gets really interesting here, and the click number turns out to be the least informative figure in it.
828 impressions means Google is showing this site, and the average position of 18.6 means it’s showing it on page two. Of the 58 queries generating impressions, 37 sit below position 20, and those account for 196 impressions that were never going to convert regardless of how good the page was.
The pattern repeats at page level, and it’s brutal in a specific way:
| Page | Impressions | Position | Clicks |
|---|---|---|---|
| Homepage | 237 | 3.8 | 9 |
| AEO/LLMO framework | 164 | 25.5 | 0 |
| 48% pipeline article | 123 | 19.3 | 0 |
| Blog index | 90 | 8.7 | 0 |
| CV | 51 | 6.4 | 1 |
| AI citation tracking | 51 | 47.4 | 0 |
My two strongest assets, the flagship framework and the pipeline methodology piece, generated 287 impressions between them and zero clicks, because they’re ranking on pages two and three. Content quality and audience demand are both fine here, while position is the constraint, and position that’s what takes years to get.
The geography confirms it: the United States produced 452 impressions and one click at an average position of 19.2, Portugal produced 12 impressions and four clicks, a 33% CTR at position 2.7, and Spain returned three clicks from eight impressions at 37.5%, which means people click at healthy rates where this site ranks.
One embarrassing finding while I’m being thorough: the query “solangerainha.com” generated 85 impressions at an average position of 8.5, with zero clicks. People are searching for my domain by name and finding it eighth. That’s a technical fix that I hadn’t noticed before running this export, which is itself an argument for pulling the data before theorising about why your traffic is flat.
The curve is bending, which I didn’t expect
I went into this export expecting a flat line but it isn’t flat.
| Month | Clicks | Impressions |
|---|---|---|
| March | 2 | 29 |
| April | 0 | 24 |
| May | 3 | 131 |
| June | 1 | 196 |
| July | 8 | 448 |
July alone produced 54% of all impressions in the period and 8 of the 14 clicks, and impressions grew roughly fifteen-fold between March and July.
I want to be careful here, because this is exactly the point where a transparency piece starts becoming a success story. One month isn’t a trend, 448 impressions is still a small number, and I’ve written before about not confusing a nice-looking metric with a working one. July could be a fluke, or an artefact of publishing more that month.
But it’s consistent with the mechanism the research describes: impressions come first, positions improve slowly after that, and clicks are the last thing to move. Impressions but no clicks is what that sequence looks like from the inside, and a site at month six with rising impressions and a position average of 18.6 is somewhere in the middle of the curve rather than at the bottom of it.
What’s working, measured properly
Transparency pieces usually cheat here by going for a flattering secondary metric, so let me separate measuring properly from measuring optimistically.
Optimistic would be celebrating those 828 impressions as reach. Measuring properly means asking what this site was built to do, and whether it’s doing it. The distinction is important because impressions are the classic vanity substitute in exactly this situation, and fewer than 5% of sites hold first-page rankings across a year even once they get there.
Organic traffic was never the point. This site exists to convince a small, specific audience: hiring managers deciding whether to interview me, and people evaluating whether the frameworks hold up. That audience doesn’t arrive by searching content strategy topics; either someone sends them a link, or they read my name somewhere and type it in.
On that measure it has worked. The strongest opportunities I’ve had in this period came as inbound approaches from people who had read the work before making contact, and that’s the owned-audience argument doing exactly what it claims.
The caveat applies to my own good news too: those are small numbers as well. What I can say is that the metric matching this site’s purpose is moving, while the metric that looks most embarrassing measures a job the site was never optimised for.
What I’d sequence differently
- I’d have started the domain earlier and published less at the start. The binding constraint is calendar time rather than volume, meaning that ten articles published eighteen months ago would outperform fifty published six months ago.
- The navigational query should have been the first fix. Ranking 8.5 for my own domain name is the cheapest win and I only found it by exporting the data. Check your branded and navigational queries before you write anything new.
- I’d have front-loaded the pages built to be linked to rather than the pages built to be found. The frameworks are what people reference and share, and they drive the authority everything else depends on.
- I’d have written my expectations down at the start. An unwritten expectation can’t be tested, and I’d have caught the domain-authority assumption in week one instead of month five.
Why publishing this beats waiting for a better number
The obvious move is to sit on this until the number improves, then write the version with the hockey stick in it, but the small-number version is worth more, for three reasons:
- It’s more useful. Someone at month four with forty articles and single-digit clicks is currently deciding whether they’re failing, but the data says they probably aren’t, and almost nobody publishes the evidence. The survivorship problem is self-reinforcing: only the wins get written up, so the published picture of what a normal ramp looks like drifts further from the median every year.
- It’s harder to fake. Anyone can publish a good number, but publishing fourteen clicks next to a framework about discoverability, with my name on both, is a bet that being checkable beats being impressive. I applied the same logic when I scored my own site against my own audit framework and published the failures.
- And it makes any eventual good number mean more. If this site is performing in eighteen months, the case study will be stronger for having a documented month six with an unflattering figure attached.
Publishing a good number proves you had a good quarter, but publish a bad one with the export attached and you’ve proved something more useful: that you’ll tell the truth when the number goes the other way. Only one of those is worth anything to someone deciding whether to trust your work.
Figures are the complete Google Search Console export for solangerainha.com, web search, 27 February to 29 July 2026. I’ll publish the next reading regardless of what it says.
Frequently asked questions
Longer than most case studies suggest, because those are written by survivors. Ahrefs found only 1.74% of newly published pages reach Google’s top 10 within a year, 72.9% of current top-10 pages are over three years old, and the average #1 result is five years old. On a new domain with no accumulated links or crawl history, single-digit or low double-digit organic clicks at six months is a normal outcome rather than a sign of failure.
Because impressions arrive before position does. Google will show a new site for relevant queries while ranking it on page two or three, where clickthrough is close to zero regardless of content quality. On this site, 828 impressions at an average position of 18.6 produced 14 clicks, with 37 of 58 queries sitting below position 20. Rising impressions with flat clicks is the expected middle stage rather than a sign the content is wrong.
Measure impressions and average position, because those move first and tell you whether you have a demand problem or a position problem. Then measure against what the property was built to do: for a site whose purpose is credibility with a small audience, direct visits, referral traffic, and inbound approaches matter more than search clicks. Pick the metric matching your goal before you see the numbers, rather than after.
It’s a stronger credibility signal than publishing good ones, because good numbers are easy to select for and hard to verify. Publishing the unflattering figure alongside the reasoning demonstrates the methodology is real, gives people building a comparable property an honest benchmark against the actual content marketing results timeline, and makes any future success case more believable because the baseline was documented before the result was known.
