Publication and PR links: measuring what SEO teams can't

The coverage that everybody celebrated and nobody could value

The piece ran on a Tuesday. Founder profile, product photos, a link in the third paragraph, and a group chat full of screenshots.

Two weeks later somebody asked the finance question. What did it produce.

The analytics said four orders. Four, from a publication with a real readership, against a retainer that costs more per month than the four orders were worth combined.

So the PR agency was put under review, and the honest answer was that the coverage had probably worked and the measurement had not. Nothing in the reporting stack was built to see what that article actually did.

The failure is specific and it repeats everywhere. Publications introduce people who buy later, and every default tool credits whoever was standing nearest at the moment of purchase.

Why publications introduce rather than close

The reading context is the whole explanation.

Somebody reads an article about a founder over breakfast. They are not shopping. They may be at work, on a train, half attending.

They register the brand. Some of them tap through and look. A few of those buy in that session, and they are the exception rather than the pattern.

The rest do what people do with a brand they liked the sound of. They come back a week later, or they search for it by name, or they see a retargeting ad and finally click.

Every one of those later paths sets a new last touch. The article that started the process leaves no mark on the order it produced.

Compare that to a performance ad, where the click and the purchase usually sit in the same session. The measurement systems most brands run were built around that pattern and work poorly outside it.

What last-touch actually sees

Model a single piece of coverage and follow the readers.

Stage	People
Read the article	1,000
Click through	60
Buy on that first visit	4
Return later and buy	15
Total orders from clickers	19

Last-touch credits four of nineteen, which is 21%. The undercount is 4.75 times.

Those proportions are assumptions and yours will differ by publication and category. The direction does not change, because the underlying behaviour is about reading context rather than about any specific outlet.

Now consider what that does to a decision. A PR retainer judged on four orders gets cancelled. Judged on nineteen it might be the cheapest acquisition in the mix.

Same coverage, same readers, same money. The decision flips entirely on which number somebody looked at.

This is also why SEO teams struggle with it. Referral traffic shows the sixty clicks and says nothing about orders.

Last-touch conversion shows the four and says nothing about the introduction. Neither tool answers the question being asked.

The readers who never click

The nineteen is not the whole contribution either, and the remainder is genuinely invisible.

Of the 940 readers who did not click, some remembered the brand and searched for it later. Model that at 25 orders.

Those people carry no cookie, because they never touched the publication’s link. They arrive as organic search or direct traffic and get credited to your brand, which is both technically correct and analytically useless.

Add them in and the publication’s real contribution is 44 orders against the 4 that last-touch reports. That is an undercount of 11 times.

Nothing available will capture those 25 cleanly. A post-purchase survey asking how somebody heard about you catches a fraction at low completion rates, and it is worth running as a directional signal rather than a measurement.

The honest position is that a portion of earned media value is unmeasurable, and the right response is to say so rather than to let a system that sees 4 out of 44 make the budget decision.

Giving publications their own slug

The first and cheapest fix is to stop treating publications differently from creators.

Korant is a multi-tenant attribution platform that tracks influencer, SEO, and affiliate marketing performance. Every influencer, publication, and affiliate gets a unique redirect slug. Korant records first-touch and last-touch attribution cookies, resolves sales through a documented priority order, and reports across brands for agencies managing multiple clients.

A slug per publication does two things. It separates outlets from each other, so a retainer can be judged on which coverage produced results rather than on coverage in aggregate. And it sets a first-touch cookie, which is the surface that captures the fifteen delayed buyers a last-touch read discards.

Read first-touch for PR and last-touch for performance channels. They answer different questions and running one number for both is how earned media gets defunded.

Set a longer window than you use elsewhere. Thirty to ninety days, fixed in advance, because the gap between reading and buying is longer than for any performance channel. A seven day window applied to PR will reliably confirm that PR does not work.

Ask for a code where the outlet will carry one. Many editorial publications will not, which is a real limitation rather than evidence that the channel is weak.

Why publication sits last in the resolution order

Korant resolves a sale through five checks in a fixed order: discount code to influencer, discount code to affiliate, last-touch cookie to influencer, last-touch cookie to affiliate, then cookie to publication.

Publication is fifth and last, and that is the correct place for it.

A publication that introduced someone months ago should not outrank a creator whose code the buyer typed today. Coverage builds the consideration and something else usually closes, and the resolution order should reflect that rather than flatter the channel.

The value of the slug is not that it wins ties. It is that first-touch gets recorded at all, so the assisted path becomes visible even when the credit goes elsewhere.

Report those two separately. Publication-resolved orders is a small number and publication-first-touch is a much larger one, and the second is the one that should inform whether the retainer continues.

Anyone reading the report needs to know which is which, because presenting the larger number without the resolution order behind it is the mirror image of the mistake this article is about.

What this measurement still misses

Korant is not for stores with a single paid channel, and it is not for brands that only need Shopify’s native reports. A brand running one PR push a year can answer this with a traffic spike and a judgement call.

Three things sit outside the model entirely.

Backlink value. A link from a high-authority publication has organic search value accruing over months, attributable to no session. Measure it separately and never fold it into the sales figure.

Credibility. Coverage changes how every other channel performs, because a shopper who has seen you in a publication converts differently on an ad. That effect is real and shows up as improved performance elsewhere.

Syndication and pickup. One article becomes six, and the derivative versions carry no link at all.

The limitation worth sitting with is that PR measurement improves from terrible to partial, and partial measurement invites false precision. A report showing 19 first-touch orders looks authoritative next to one showing 4, and both are incomplete in the same direction.

Brands that fix their PR attribution often conclude they have solved the problem and go back to optimising against a number that still misses more than half of what is happening.

Hold PR budget against a slower measure such as branded search volume, treat the attributed figure as a floor, and resist ranking publications on a number this noisy. The same first-touch logic applies to creators who build consideration rather than clicks, covered in finding creators whose audience overlaps yours. How to instrument before a campaign is in the influencer brief that gets you usable content, and the pay implications are in paying influencers on performance.