A researcher’s account of moving into PR industry and the gap that shows up when you have spent your career reading data.
I spent more than twenty years using data to direct strategic decisions. Not to prove them afterward, but to direct them.
The programs I built answered questions like these:
- Should this product launch in this market?
- Which position in the market can this company credibly own?
- Which audience is actually ours to win?
- How should we change the communications strategy to get better results?
- What messages will land with the people we are trying to reach?
- Which competitors deserve our attention, and which ones do not?
The list goes on. But the common factor was always the same. Every one of these programs ended in a recommendation backed by data that could be defended, and that recommendation was meant to inform strategy and shape growth.
How the work looked mattered too. Nobody acts on a finding they cannot follow. But it was never just a pretty chart. It was a blueprint a company could use to take some of the risk out of a decision.
With a recent transition into the world of PR, my work changed shape. Most of it was about finding the insight in a dataset that could carry a story: the finding a journalist would run with, the number that gave a company something original to say.
Thought leadership research earns its place in a communications strategy. But it is one application of research, not the whole of it.
The profession has largely won the argument about using research to claim a leading position in its industry. It has even started the conversation about proving its value with better numbers, moving away from vanity metrics like unique visitors per month. What it has not yet worked out is how to use insight to direct strategy rather than report on it.
The short version
PR spent twenty years learning to prove its work mattered. That was necessary, and it largely worked. The harder task is using the same evidence to decide what to do next. That takes people trained to read data, working alongside people who know the discipline.
What the communications industry gets right about measurement
The industry is in the middle of a real transition, and it deserves more credit for it than it usually gets.
For decades, PR measurement meant advertising value equivalency, the practice of pricing coverage as though it were an ad buy, alongside clip counts and estimated reach. Numbers that produced a figure without producing an argument. The profession did the hard work of dismantling that, and it was not easy work.
The current writing on this is thoughtful. Raina Lazarova, who chairs AMEC, argues in a recent Muck Rack piece that vanity metrics have been misunderstood. Everyone shames coverage volume now, but coverage volume is not inherently bad.
The key is knowing which question you are trying to answer and choosing the metric that fits it. The same metric can be the right one or the wrong one depending on the objective. It is one of the more sophisticated positions I have seen on this.
Where Lazarova writes about the philosophy behind choosing metrics, Lora Thornton at Flaunt Digital writes about the metrics themselves. Her argument in Beyond Vanity Metrics: The PR Metrics That Actually Matter is that coverage volume is an outdated KPI, and that what deserves attention instead is relevancy, authority, topical and entity alignment, sentiment and salience, and share of search.
In a landscape shaped by AI systems that map relationships between brands and topics rather than counting mentions, that is directionally right.
Both are arguing for the same shift, from visibility to understanding. And I think both are correct.
There is one gap, though, and it is the kind a researcher notices. The industry has largely learned how to prove that its work matters. That was necessary, and it took years. The next step is harder, and it happens to be the one I have spent my career on: using the same evidence to decide what to do next.
What is a vanity metric, actually?
Vanity metrics are the thing everyone in communications is talking about. Taking a stand against them has become its own kind of positioning. But almost nobody has said what makes a metric vain.
The common view is that vanity metrics are the big obvious ones. Impressions, reach, followers, ad-equivalency figures. So teams retire those and replace them with something that sounds more rigorous. Engagement rate. Quality-weighted coverage score, which weights each placement by the quality of the outlet. Share of voice.
The measures get more precise, the dashboards get prettier, and everyone relaxes.
Sophistication was never the problem.
A metric is vain when no value it could take would change what anyone does.
That is the whole test. Ask whether the thing you are measuring could give you a reason to change direction. If it cannot, do not measure it.
It is the same logic a researcher applies when writing a questionnaire. If the answer will not help you make the decision, why are you asking?
What a researcher notices in PR measurement
When I read those two pieces, the researcher in me could not stop reading them as study designs. Here is what stood out.
The humans are missing. And the humans are the point.
Every metric in both articles can be produced from media data and search data alone. The audience never appears anywhere in the process.
We measure how a brand shows up in media, and where, and we are now making real progress on measuring how it shows up in AI search. All of that is worth knowing.
But what does any of it tell us about whether the people we are trying to reach think differently than they did before? That question is missing from the equation, and it is the one the whole discipline exists to answer.
Proving and directing are different jobs
Proof looks backward. It asks whether the thing we already did worked, which gives it two possible answers, and it is usually commissioned by the people who did the work. That is a large part of why it so reliably finds that the work succeeded.
Direction is a different exercise. It weighs options against each other and asks which of the things we could do next is most likely to work, for whom, and what we would need to see to change our minds.
That means designing the measurement before the program instead of after it. It means setting a starting point you cannot move later. And it means accepting, before you begin, that the answer might be disappointing.
A study that cannot come back negative cannot redirect anything.
Why PR measurement needs researchers, and not only researchers
The usual instinct is to solve measurement by buying a better platform, or by handing it to whoever is most comfortable with the dashboard. Both instincts miss what the problem actually is.
Measurement looks like an analytics job. It is a research job.
The skills it takes are the ones you build by running studies that decisions depend on:
- Knowing how much a given group of people can actually tell you
- Knowing how much the wording of a question changes the answer
- Knowing when a difference is real and when it is noise
- Knowing when to stop collecting data and make a call
That experience does not come from a PR, communications, or agency background. This is the part the industry has been slowest to absorb.
None of which means researchers should do this alone, and I want to be clear about why.
Communications professionals know things no dataset contains. Which journalist will actually run the story. What a spokesperson can credibly say. How a message will land in one market and not another. When a technically accurate claim will read as tone-deaf. I have watched methodologically sound recommendations fail because they ignored all of that.
What I have always argued for is a partnership. Research designs the measurement and interprets what comes back. The people who know the discipline, in this case communications, shape what is worth measuring in the first place and what the finding means in practice.
That partnership only works if both sides are in the room. Often only one of them is.
When measurement gets assigned to the account team, it ends up built by the people whose work it evaluates, using a tool that can only see one source. That arrangement will reliably confirm the program succeeded. What it will not do is show you where to go next.
The one question to ask before you measure anything
Before commissioning any measurement, ask one question: what result would cause us to change course?
If nothing you could plausibly find would change anything, the exercise is ceremonial. It will produce a number that survives a budget review and tells you nothing you can use.
But if you can answer it specifically, and say that we would move budget out of this channel, or retire this message, or stop chasing this audience, then you have the start of something real. You now know what the measurement has to be capable of detecting, and you have given yourself permission to be told something you did not want to hear.
That is the part I keep coming back to. Proving that the work mattered is necessary. Knowing what to do about it is the real value.
Common questions
What is a vanity metric?
A metric is vain when no value it could take would change what anyone does. Size is not the test. A sophisticated composite score that nobody has attached to a decision is exactly as vain as an impression count. It is simply harder to challenge, because it looks like work.
How should PR measurement change?
Design the measurement before the program rather than after it. Set a baseline you cannot move later. And measure whether the audience changed its mind, not only whether the coverage appeared.
Why do researchers belong in communications measurement?
Measurement looks like an analytics job and is really a research job. Knowing what a sample supports, how question wording moves a result, and when a difference is real rather than noise are skills built by running studies that decisions depend on. They are not acquired by proximity to a dashboard.