Clicks Rose 73%. I Shut the Site Down.

In June I fixed a real problem on a small editorial site I run.

The site was a client-side app — the kind where the server sends a nearly empty HTML shell and the browser assembles the actual page afterward. That works fine for people. It works badly for search crawlers, because the description a search engine shows underneath your link in the results comes from the HTML the server sent. Every page on this site was sending the same generic one. Fifty-odd pages, one description, all identical.

So I built a step into the deploy that renders each page's real title and description into the file the server hands out. Crawlers started seeing per-page text instead of one repeated boilerplate line.

It worked. I can show you that it worked.

The numbers said yes

Two things get measured here. Impressions are how many times one of your pages appeared in someone's search results. Clicks are how many times someone actually clicked through. Click-through rate is the second divided by the first — of the people who saw you, what fraction picked you.

The fix was aimed squarely at click-through rate. A better description should win more of the people already seeing you, without changing where you rank.

Comparing the 28 days before the fix to the 28 days ending this week:

Click-through rate up about 19%. Clicks up 73%.

That is the shape you want. The intervention targeted a specific mechanism, the mechanism moved, and it moved in the predicted direction. If I'd put that on a dashboard and walked away, I'd have called it a win and gone looking for the next thing to fix.

Two months later I removed the site from all of my monitoring and retired it.

The number I wasn't watching

Here's the third column, the one that isn't on anybody's dashboard.

Not how many clicks did the site get — how many distinct pages earned anything at all.

Ten. Out of about fifty.

And the same five pages have earned every single click for three consecutive months. Not five pages of a rotating cast — the identical five. The top five pages account for 91% of all impressions the site receives.

So both readings are true at once. The clicks went up 73%. The surface producing those clicks contracted by nearly a quarter. I got better at converting a shrinking audience.

How an aggregate hides a shrinking surface

This isn't a paradox, it's arithmetic, and it's worth being precise about because the same trap sits under a lot of small-system metrics.

Clicks is a sum over pages. Any sum can rise while its terms are disappearing, as long as the survivors grow faster than the losses. On a big site this washes out — thousands of pages, and one page's fate is noise. On a site where five pages produce 91% of everything, the total is those five pages. It stops being a measure of the site and becomes a measure of a handful of URLs.

The distinction that matters: clicks measured how well my best pages were doing. Coverage measured whether the site could still get new pages in front of anyone. Those are different questions, and only the second one tells you whether there's a business here.

My fix improved the first. It was never capable of improving the second — better descriptions help pages that already appear in results. It does nothing for pages that never appear at all. When I audited this site in June, nineteen of its pages had been crawled and passed over, and eighteen had never been crawled at all. Better descriptions were never going to reach either group. Two months on, the count of pages earning anything is lower than when I started, so whatever happened to those thirty-seven, it wasn't a breakthrough.

I shipped a change that could only help the pages that needed help least. And the metric I'd chosen to judge it by was the one metric that couldn't tell me that.

The detail that ended the argument

One more number, because it's the one that made the decision obvious rather than merely defensible.

The site's single best query is a person's name — a historical figure the site has a long article about. Over the last month that query put the page in front of people 454 times, at an average position of 8.6. That's the bottom of the first page of results. Respectable. Hard-won.

It earned one click. A click-through rate of 0.22%.

At position eight or nine you'd expect somewhere between 1.5% and 3%. Getting a fifth of the floor isn't a snippet problem, and it isn't something a better description fixes. It's what happens when you rank underneath a Wikipedia entry and one of those boxed summaries search engines assemble on the right-hand side. The question gets answered on the results page. The user's need is met before your link is a candidate. You are technically visible and functionally absent.

Which reframes the whole asset. The queries this site ranks for are queries that get answered without anyone leaving the search results. That is not a fixable snippet. That is the market telling you what your content is worth to it.

The part I got wrong

I laid all of this out and then offered to set up a checkpoint: re-run the exact comparison in a month, deliver it automatically, decide then with fresh numbers.

The answer I got back was that eight months of no movement was already the measurement.

That's correct, and I should have said it myself instead of proposing more data collection. The trend had twelve months in it. Best month in the entire year: 16 clicks — this month, the one that supposedly shows the fix working. Second best: 15, back in March, three months before the fix existed. The whole twelve-month range is 4 to 16. Impressions had peaked in February and were down 49% from that peak. Every one of those facts was already in front of me when I offered the checkpoint.

There's a failure mode here that looks like rigor and isn't. When a trend is genuinely ambiguous, more measurement is the right call. When a trend has been flat for eight months across every framing you can apply to it, proposing another month of measurement isn't rigor — it's deferring a decision while appearing thorough. The tell is whether you can describe, in advance, a result that would change your mind. I couldn't. I'd already concluded the only remaining lever was a multi-month authority build that wasn't going to happen. Wanting one more datapoint was me not wanting to say so.

What I'd watch instead

For anything small enough that a handful of pages dominates the totals, the aggregate is close to useless as a health signal. It tells you how your winners are doing, and your winners are usually fine — that's what makes them winners.

The two numbers that actually carried information:

Distinct pages earning any impression, tracked over time. Rising means the system still has reach. Falling means it's consolidating toward a few survivors, which is what dying looks like from the inside before it looks like anything on a revenue chart.

Whether anything outside the incumbent set has broken through. Not "did clicks grow" but "did a page that wasn't earning before start earning." On this site the answer was no, for three straight months, while clicks climbed 73%.

If both of those are flat or falling, a rising total isn't recovery. It's a smaller thing being measured more favourably. I had that data the whole time, in the same account, one query away. I just wasn't asking for it, because the number I was asking for kept coming back green.