Last week we talked a great deal about PR measurement. During that discussion, I mentioned the tool—CoverageImpact—that the creators of CoverageBook have created. Right now, because it’s in beta, it’s a free tool you can use to begin to understand how your efforts translate to outcomes instead of outputs.

With a spreadsheet of activities and some analytics information, you can correlate your efforts to increased qualified leads, stock price increases, sales, website visitors, and more. And better yet, it automates some of the analysis and reporting for you, so you don’t have to do the dreaded math—or even create visuals from spreadsheets. 

Let’s walk through how to use this tool to report on the success of your work, correlate your efforts to the organization’s goals, and finally begin to measure outcomes. 

Moving from Outputs to Outcomes

First, let me say I get nothing from them for showing you how this tool works. I’m simply super impressed with its potential, and I want to tell the world. I also created a tutorial for the PESO Model© Certification, and, as I was building it, I thought, “Eureka! I should repurpose this content!” 

They describe their work as follows, “Visualize how your PR coverage affects real-world outcomes. Turn your tracker spreadsheet into a coverage-over-time graph in a flash. Layer on data like sales, web traffic, or search trends—and connect PR activity to organizational goals.”

Sounds pretty amazing, doesn’t it?

One of the biggest challenges in the PR industry is that we tend to measure outputs versus outcomes—tactics instead of goals. But this tool claims to take one of your tactics—media placements—and correlate those efforts with something the organization cares about, such as sales, stock price, search trends, donations, website visitors, and more.

Let’s see if it delivers.

Using CoverageImpact

First, I download a CSV file containing a year’s data. I’ll use it to analyze all the media placements we received in 2023 for one client. The file should include the date and the link. It can contain more, but it needs at least those two things.

I upload that CSV file to the software. 

Next, I upload a second CSV file with data based on the organization’s goals. For this example, I’m going to use website traffic. Going into Google Analytics, I can export a file of all website visitors for this client by day in 2023.

Once both of those files are uploaded, the software does its job. You don’t have to work in spreadsheets or create your own charts and graphs. It does it in seconds. It outputs a graphic showing two things: a coverage timeline for all of 2023 and, in this case, it overlays the website traffic for the same time period.

I will ideally see an increase in website visitors on the day of and the few days following a media placement or placements. That way, I can correlate our media relations efforts to more people visiting the website. I know that more website visitors result in more qualified leads, which results in more sales for this particular client. 

The PR Measurement Conundrum

When you watch the video below, you’ll see that there was, indeed, a spike in traffic on days that we had stories run. But something else cool happened…while traffic returned to normal a day or two after a story ran for the first half of the month, it spiked in the second half with more placed stories—and maintained that spike and then some for the rest of the month.


The story tells itself when you show that to your client or executive team. Now imagine if you overlay sales, stock price, or donations. Suddenly the correlation between your media relations efforts and what really matters to a CEO is clear.


It also gives you a really good reason to ask for that data. You can do it by day, week, month, or quarter, making it easy to demonstrate success.

It only does this for placements right now, but I’m working with them to figure out how to include paid, shared, and owned media, too. 

Dissect the Data Points

While this tool isn’t the end-all, be-all, it does mark the beginning of a pivotal shift from measuring outputs to measuring outcomes. Now your job moves beyond observing the correlation between media placements and the organization’s goals. What you should work on is how to dissect these data points to uncover deeper insights that can drive strategic adjustments.

For instance, analyzing the coverage timeline alongside website traffic may reveal that certain types of media placements—feature articles, interviews, trade articles, or product reviews—have a more significant effect on driving traffic or conversions. 

This nuanced understanding will enable you to refine your pitching strategies and focus your efforts on securing the types of coverage that align most closely with the goals.

Then, you can look for patterns in how different content types influence outcomes and tailor your owned media efforts to combine with the earned media results.

While this level of analysis requires a keen eye for detail and a willingness to delve into the data, in this case, AI can help you out. 

Use AI to Uncover Deeper Insights

If I upload the media coverage, Google Analytics CSV files, and the graphic from CoverageImpact to ChatGPT, I can ask it to do a correlation analysis. 

By doing this, it tells me that there is a strong positive correlation between website visitors and coverage presence. The correlation coefficient is approximately 0.894, which indicates a very strong relationship.

Now we can prove our hypothesis correct: media coverage positively affects website traffic. 

I can also ask AI to provide qualitative insights and determine the longer-term effect as we increase website traffic with media coverage.

The best part is that if you can access sales or conversion data, you can begin to correlate your efforts to the all-mighty dollar. Once you do that, the “what have you done for me lately” conversation disappears. 

PR Becomes a Business Necessity

Harnessing the full potential of tools like CoverageImpact propels PR into a strategic role that directly correlates with achieving business objectives. This advancement will enable us to make data-driven decisions before launching a campaign.

Imagine the advantage of predicting how a specific story placement could influence market perception or customer behavior weeks or even months in advance.

Now put that on steroids as we integrate the other media types to provide a full look at all facets of the PESO Model. This integration will enhance our PR measurement capabilities and clarify how our work affects the organization’s growth. It’s about building a cohesive narrative across all channels that amplifies our message and drives measurable outcomes.

This evolution will also open the door to more sophisticated stakeholder engagement strategies, where we tailor our communications to address their specific interests and needs, resulting in higher loyalty and trust.

As Long As You Stay Curious

The journey toward advanced PR measurement is an ongoing process that requires curiosity, innovation, and a willingness to embrace new technologies. Our role is to continuously explore these tools, adapt our strategies, and contribute to the conversation around PR measurement. 

By doing so, we prove the value of our work and drive forward the success of our organizations.

Gini Dietrich

Gini Dietrich is the founder, CEO, and author of Spin Sucks, host of the Spin Sucks podcast, and author of Spin Sucks (the book). She is the creator of the PESO Model and has crafted a certification for it in partnership with Syracuse University. She has run and grown an agency for the past 15 years. She is co-author of Marketing in the Round, co-host of Inside PR, and co-host of The Agency Leadership podcast.

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