Ad Value Equivalency is fundamentally flawed, but is it fixable?

I still remember holding a ruler against my magazine clippings, hoping a client’s placement took up enough space to be considered ⅓ of the page versus ¼. It was my first job out of college: a boutique public relations agency serving fashion brands. An account assistant, I was tasked with compiling Ad Value Equivalency, or AVE, reports.

Each quarter, I dutifully pulled out the ruler to determine what percent of a page in GQ my client’s sneakers took up (let’s say 33%), and multiplied that by how much a full page ad would cost to run in GQ ($143,681 at the time, I checked). The Ad Value Equivalency for getting those sneakers into the hands of a stylist, who in turn put them in the final shot: $47,415. Rinse and repeat until I had a full tally of how much my client would have paid in advertising for the coverage produced through PR.

Was it bulletproof? Of course not. Comparing advertisements to media coverage was, and still is, an apples-to-oranges comparison.

But was it really that bad? I’d argue no! Since the magazine’s ad rates were determined by its monthly circulation and audience, that ad rate was a decent proxy for the caliber of placement. If the placement took up less than a full page, my handy ruler accounted for that. We avoided subjective multipliers to account for added value of earned over paid. For print coverage, AVE gave my client a solid metric to track each quarter, and it let the agency demonstrate the millions of dollars in value we were generating. So where did it all go wrong?

AVE didn’t evolve with the rise of digital media

Let’s say I got those sneakers featured today on AVE would have me take the site’s 10 million unique monthly visitors, multiply them by a percentage of traffic I think saw that placement (let’s generously say 1%), and then multiply it by whatever GQ charges for an impression of a display ad on the page. With a hypothetical display ad rate of $50 per 1000 impressions, or $0.05 per visitor, the AVE for my hard-earned placement comes out to 10,000,000 * 1% * $0.5 = $5,000. 

Yikes. At some point over the last two decades, the sneaker placement went from being valued at $47k to a “generous” $5k. Is earned media truly less valuable in the digital age, or is something else at play?

“The greatest trick advertising ever pulled on PR was getting the industry to use its math”

I’ve heard Memo CEO Eddie Kim come back to this refrain a lot. He argues that the biggest issue with AVE in the digital age isn’t that it’s derived from inaccurate potential reach numbers or that it makes assumptions about how many people saw the content.

AVE’s fundamental flaw is taking an entire article – where a reader is actively engaging with content about a brand for 80 seconds on average – and comparing it to the rate for a small box on the page that we’re conditioned to tune out. Finding a true apples-to-apples comparison means completely rethinking the foundation of AVE in the digital age.

What if we treated an article like the destination it is: a landing page

We can think of an article as a landing page, and this opens up an entirely new way to assign a dollar value to earned media. Our full methodology for MRV (Memo Readership Value) is outlined here. In brief, MRV calculates what it would cost a marketing team to pay for the engagement that was earned by PR and uses three inputs:

  1. The article’s unique visitors (what Memo reports as readership)
  2. How each unique visitor came to that article (i.e. how many readers found the article through Google search, via Twitter, through a newsletter, etc)
  3. The cost-per-click rates associated with each of those channels, as a comp for how much a paid media team would need to pay in order to replicate the earned engagement of PR

The result is a dollar-based value for an earned placement based on relevant paid-media math. Instead of trying to fit a square peg into a round hole like AVE, MRV uses newly available, accurate data to completely reinvent a way to show ROI for PR.

TL;DR: MRV does what AVE could not

AVE is fundamentally flawed because it equates a full article with a small digital ad. We shouldn’t be calculating value based on ad space but rather how much it costs to drive traffic to the article content via equivalent cost-per-click rates. That’s what MRV does. 

For the first time, you get an accurate view of impact through readership and you can demonstrate ROI for all your work. Bonus: we do the math so you don’t have to.

3 graphs that illustrate the problem with PR impressions

“We know impressions are inaccurate, but at least they’re directionally correct.”
“We know impressions are inaccurate, but we divide them to be more realistic.”
“We know impressions are inaccurate, but no one is forcing us to change.”

“We know impressions are inaccurate, but.” It’s a common and persistent refrain in the PR industry. Years of having no alternative metrics created a status quo of measuring the potential, rather than the actual.

Unfortunately, impressions are not directionally correct at the article level: highly-trafficked outlets don’t always get higher article readership (i.e. unique visitors to an article page) than lower-traffic outlets. And dividing monthly impressions by 7 or 30 days is not a realistic assessment of how content performs: on the same day in the same publication, one article can get one million readers, another one thousand. 

You might say Memo has a refrain of its own: “Impressions are not just inaccurate, they’re misleading.” We’ve published data that shows how impressions distort share of voice and how impressions overlook important outlets. But mechanically, why is this?

Our team analyzes readership data every day. We want to illustrate exactly why impressions obscure the insights that are so glaringly obvious with readership. 

Actual readership among a publication’s articles is highly variable

We pulled an entire month’s worth of content published on an outlet that receives roughly 30 million unique monthly visitors. Each box represents an article, and the size of the box represents that article’s readership, i.e. the number of unique visitors to the article in the first 7 days of publication.

Each of the approximately 800 boxes is a single article published in August 2022 on the same publication. The size of each box represents that article’s readership.

The most-read article that month received over 2000x more visitors than the least-read article. 

There is brand coverage that completely hit it out of the park, and there is coverage that could benefit from further amplification. 

There are article topics that tend to fall on the upper left corner of that graph, and topics that tend to fall on the lower right corner.

There are takedown pieces that blew up, and takedowns that barely made a splash.

Article-level readership provides a wealth of information about earned media performance and strategy. So what about impressions?

Impressions (wrongly) report that every article performs the same

We can visualize the same ~800 articles with potential impressions instead of actual readership. This is what we see:

Each of the approximately 800 boxes is a single article published in August 2022 on the same publication. The size of each box represents that article’s potential reach (aka impressions or UVMs).

Did we get a lot of eyeballs on our product press? Does this outlet get high readership on our industry’s news? Is this negative story worth a spokesperson response? Potential reach doesn’t help us answer any of these questions, but readership does.

It’s the difference between a clippings report where every article has the same performance metric (left) versus a readership report where you know exactly how many people saw the coverage (right):

Sure, the report that tallies up to 225,000,000 potential impressions looks impressive. But with 258 million adults in the US, business leaders know it’s a bogus figure.

Lower UVM publications can get more article readership than higher UVM publications

The monthly unique visitors on a site can be a helpful proxy for publisher authority when, for example, trying to understand the landscape or build an initial media list. But impressions are a horrible proxy for article performance, even across different publications. 

Everyday we see outlets with relatively low monthly visitors publish articles that receive higher readership than content on relatively high-traffic outlets. (A Memo report further examines this trend.)

In fact, one of the first things new Memo users say is “I can’t believe how many people read our placement on [insert niche outlet].” 

To illustrate, here is the same publication visualized above next to a second publication with approximately 75 million UVMs:

Each of the approximately 800 blue boxes is an article published in August 2022 on a publication with 30 million UVMs. Each of the approximately 1,300 purple boxes is an article on a publication with 75 million UVMs. The size of each box represents that article’s readership.

The higher-UVM outlet published the most-read articles among the two publications. But there are hundreds of articles on the lower-UVM outlet that received more readership than content on the higher-UVM outlet. 

We’ve now illustrated that impressions are 1) not directionally correct, and 2) not a realistic assessment of article performance, no matter how you slice them. 

Still, if no one is forcing the issue, why change?

Comms has become more entwined with marketing and business strategy. Its measurement will be too.

One of the biggest PR measurement trends that emerged this year was that Communications teams are working more closely with Marketing and other business functions. With this seat at the table, however, comes expectations of more rigorous measurement. 

Our team has worked with some of the earliest adopters of readership data. The Comms groups that embraced this change a year or two ago are already operating at a different level. They’re more strategic with media relations. They’re better equipped to handle crisis stories. They’re giving earned media its due credit in the broader marketing mix. 

No longer misled by the false impression (pardon our pun) that content performs uniformly on a publication, they’re making better business decisions.

All about article topics, Memo’s secret weapon for readership insights

While the wealth of readership data that the Memo platform provides is certainly exciting, it is hard to extract those insights without having a way to “slice and dice” the numbers. 

This is why our app assigns each article a “topic,” a label that provides an instant understanding of that article’s content. 

Say you want to hone in on coverage about hiring and workplace benefits – perhaps to see which outlets get high readership on the subject, or how your share of readership compares to competing employers. You can filter by topic in the app, in this case Business News – Hiring, Wages, Benefits, and view readership stats specific to this theme. 

Or conversely, if a topic is creating a lot of noise in your media coverage, you can filter it out to focus on the readership data most relevant to you. Pretty handy, right?

This month, we’re excited to release a new machine learning-powered classification system that improves both the categorization process and the topic taxonomy. 

We’re calling this launch “universal topics.” And while a faster, more consistent topic schema might not seem flashy, I promise that it’s an actual game changer for surfacing deeper readership insights at scale. Here are the details:

Memo’s article topics are built for how PR & Comms teams view media coverage

Unlike tools that generalize the subject of a piece of content, Memo tags articles with topics that are relevant to the coverage categories PR & Comms teams think about every day. An article about the new iPhone wouldn’t just be “consumer electronics” or “iPhone.” Rather, Memo might label it Product – Launch – iPhone 14 so that the user knows this was product-related press about the launch of the new iPhone.

Universal topics follow a pattern of Primary Topic (all) – Secondary Topic (most) – Tertiary Topic (some). For many longtime Memo users, these labels will look familiar. Here’s how the taxonomy works:

First, every article is assigned one of 13 possible Primary Topics:

  • Advice: How-to, instructional, and advice-driven articles
  • Business News: Corporate news, earnings coverage, executive news, etc.
  • Celebrity: Celebrity interviews, paparazzi coverage, gossip, and partnerships
  • Content Availability: Coverage of how, when, and where to access content
  • Corporate Initiatives: ESG-related initiatives by companies
  • Deals & Promos: Sales announcements and promotional offers
  • Event: Summits, conferences, sporting events, awards ceremonies, etc.
  • Human Interest: Feature stories that portray people in an emotional way
  • Incident: Coverage of crimes, deaths, cyberattacks, etc.
  • Industry Trends: General industry news and commentary
  • Issue: Coverage of large societal issues
  • Product: News about a company’s products, including launches and reviews
  • Merchandising: Articles promoting the availability of retail goods

Content and industry nuances are captured with subtopics

Once the Primary Topic has been identified, most articles will receive a Secondary Topic, and some will receive a Tertiary Topic. 

For certain Primary Topics, there are finite lists of corresponding Secondary Topics. All of the possible Secondary Topics for Business News, for example, are the following: 

  • Business News – Earnings 
  • Business News – Expansion
  • Business News – Hiring, Wages, Benefits
  • Business News – Leadership
  • Business News – M&A & Partnerships
  • Business News – Stocks & Markets
  • Business News – Thought Leadership

For other Primary Topics, there are infinite Secondary Topics. For instance, the primary topic Event has endless possibilities. In these cases, we use machine learning to pull out named entities that identify the specific event. An article that discusses the Emmy awards will be labeled Event – Emmy Awards. An article about the Academy Awards will be labeled Event – Academy Awards.

The primary topic Product is a combination of finite and infinite: the Secondary Topics are always either News, Review, Launch, or Roundup. Then we use entity extraction to pull a custom Tertiary Topic, typically the name of the product. So an article titled “Apple Launches iPhone 14 and 14 Plus” would be categorized as Product – Launch – iPhone 14.

The new topic schema enables easier readership analysis

A major benefit to the newly launched topic conventions is that the consistent structure makes it easier for brands to hone in on the coverage they care about for a given analysis.

In the iPhone example above, a brand like Apple could zoom in on iPhone 14 launch coverage to measure the readership of that campaign; they could look at the entire product news cycle for the iPhone 14 (the launch, product reviews, product promos, etc) to track readership over time; or they could compare all product launches across different devices to find the best outlets for the next device launch.

Imagines of Memo's readership dashboard filtering by different topics
Consistent topic hierarchies and naming conventions make it easier for Memo users to filter for different types of coverage.

Universal topics balance article fidelity with industry flexibility 

Previously, topics were assigned at the brand level, meaning an article’s topic might differ across accounts. 

By acknowledging that the topic of the article is a singular entity, universal topics create more value by prescribing an identity to that article, rather than assigning a topic in the context of the account’s dashboard. 

The launch of Brand tags in our platform in 2021 (labels that indicate which brands are included in an article) removed the need to clarify the brand context in articles with topics. In the past, for instance, when an article only mentioned an account’s keywords in passing, Memo assigned it the topic Mention. While that is the context of the article in relation to the brand, it doesn’t actually tell us anything about the contents of the article! 

With universal topics, each article’s topic is a direct representation of what that article is about. As described above, Secondary and Tertiary Topics provide more detailed entity information to make the topic relevant to the industry and brand. Altogether, this structure ensures consistency in reporting and allows Memo to provide deeper insights at scale.

Universal topics are also processed faster with new AI models

An added benefit to this launch is a standardized delivery time of the topic assignments. The granular customization at the brand level was possible with our legacy keyword-based topic assignment system, but it posed a hurdle as we migrated to more advanced, scalable machine learning models. And frankly, it took a long time to process.

Now, when you log into the dashboard first thing in the morning, all of the articles for the previous day will have a topic in addition to readership, every time! No more waiting for updates at 12pm EST or later. 

We have been working hard over the past several months to revamp our topic system, and we are so excited to share these improvements with our clients. The scalability of this system paves the way for deeper and faster insights, reports, and product features – so this is just the beginning.

Why social media has broken social listening, and how to fill the gaps

Key takeaways:

  • Social platforms that once served up a silver platter of data on earned-media engagement have deprioritized news articles.
  • With often <10% of article traffic originating from social media – and little correlation between the two – social listening is a misleading proxy for article readership.
  • It’s time to rethink the role of social listening for Comms and Marketing, and find new data sources to fill the gaps.

23% of U.S. adults use Twitter.

And among them, just 10% are responsible for 92% of Tweets.

It’s a surprising finding coming from the Pew Research Center, but should I be so shocked given my own habits? I have a Twitter account that I use for some aggressive lurking, but never Tweeting. When I want to share an article I found on Facebook, I usually copy the link and fire it off in group texts or Slack channels. I might like the occasional post from a brand on Instagram, but I’m acutely aware of the activity my friends, family, and ex-boyfriends can see on the platform. While I wouldn’t go so far to call myself the norm, that Pew study suggests I’m not an exception either. 

With so much engagement on brand content happening outside of social channels – and with the engagement inside those channels driven by the vocal minority – what role does social listening serve for Comms and Marketing teams? To understand where social listening can continue to provide valuable intel, we first need to dissect where it’s no longer relevant in 2022:

The days of measuring earned media performance with social are waning.

There was a time when the only datapoint we had for quantifying article performance was potential impressions (i.e. the publication’s unique monthly visitors). So when news content exploded on Facebook and Twitter, it’s no surprise that PR & Comms teams flocked to social listening tools to report actual engagement with articles posted to feeds – finally a more tangible metric!

But news content just doesn’t have the same prominence it did a decade ago on social media. When analyzing our users’ press, Memo’s Insights team often finds that social referred less than 10% of an article’s traffic (organic search, email, aggregators, and the publication’s own website are more common traffic drivers).

Most articles about these brands received less than 10% of their traffic from social media channels over a 28-day period.

With Facebook and Instagram emphasizing creator content over posts from your followers, and with Meta further confirming it will no longer pay publications for content in the News tab, the decline in news readership from social media is likely to continue.

Social engagement on an article isn’t even directionally indicative of readership.

Measuring the performance of news content via social engagement is incredibly misleading: the number of likes/shares/comments an article receives is not directional to how many people actually read that article. 

To illustrate, take the below mapping of social engagement (vertical axis) against article readership (horizontal axis) for 600 articles about a large fast food restaurant. There is no discernible trend that defines the relationship between how much engagement an article receives on social media and how many times that article is actually read. (Technically the correlation coefficient here is 0.18, so a very weak positive relationship.)

Many highly read articles have low social engagement – not surprising given how little traffic social often refers to articles.

Conversely, some articles have high social engagement but relatively low readership – also not surprising given that users share articles without reading them (usually on hot-button issues) and the proliferation of spam bots.

This unpredictability in how users interact with news content on social media is also driven by changes to the platforms themselves – changes that have implications to marketing more broadly. 

Beyond PR, platform changes have also made social listening a less valuable signal for marketers.

The social media landscape is undergoing a seismic shift. “TikTok says it’s an ‘entertainment platform.’ Snapchat calls itself a ‘camera company.’ Meta says it’s a ‘metaverse’ company. The era in which social networking served as most users’ primary experience of the internet is moving behind us,” to quote Axios’ Sara Fischer, who was in turn summarizing Scott Rosenberg’s article “Sunset of the social network.”

Platforms that once served up a silver platter of data on consumer trends, brand relevance, and news engagement are moving away from the user experiences that facilitated this centralized measurement. Public news feeds are giving way to private groups and messaging channels; posts authored by connections are being supplanted by creator content; and short-form videos are the future.

Even Twitter, the most accessible platform to social listening tools, is in flux: it has yet to find a sustainable business model and is one acquisition away from an overhaul of its own. Until then, discourse is skewed to a minority of users (the 10% of power Tweeters), and politically biased (over two-thirds of those users identify as Democrats or Democratic-leaning independents). 

This isn’t to say social listening doesn’t have value; we just need to acknowledge its gaps.  

We need to be more judicious about what we rely on social for, and where we supplement gaps with other data. I’ve already discussed the shortcomings of using social listening to measure earned-media engagement, so let’s take another use case:

Using Twitter as a barometer for brand health, for example, can easily over-index on the negative. Among the 90% of infrequent Tweeters, how many emerge only to @ an airline for missing luggage or air some other grievance in hope of rectification? If Twitter is for complaining, it can certainly help measure threats to brand health, but it will overlook the engagement happening outside the platform with more positive brand stories.

And we need other data sources to reveal the trends that social listening can no longer surface.

There’s a trove of content about brands that people engage with everyday online: articles in the press. And unlike social platforms – where most activity is public to at least a group of followers – engagement with articles is often private. Readership is free of participation bias, virtue signaling, and algorithm manipulation. It’s an honest signal for the stories and brands that consumers are interested in and, for the first time, it’s finally measurable.

Share of Voice is a broken metric. Here’s how we fix it.

Key takeaways:

  • Traditional SOV measurement is not just inaccurate; it’s misleading 
  • Share of Readership reveals what’s actually working for your brand and the competition
  • Below we walk through a real-world example of SOV vs Share of Readership

Share of Voice (SOV) is one of the most common metrics that PR & Comms teams use to benchmark the quantity and quality of their coverage against their competitive set. 

A major goal in looking at a brand’s SOV is to figure out your company’s position in the market. By understanding which competitors are succeeding, how they’re doing it, and where, you can identify and act on gaps in strategy.

But even important calculations like SOV aren’t immune to “garbage in, garbage out.” Inputs need to be accurate and transparent to in turn ensure an accurate representation of the competitive landscape.

And regarding that representation of the competitive landscape: What does it mean for a competitor to win? Are they getting written about in more publications? In publications with a higher potential reach? Or is there something else?

The fundamental issue with the traditional methodology for SOV is that teams are still relying on PR estimates like potential reach and volume of mentions as the determining factors to analyze success and their positions in the market. But as I see day-in, and day-out at Memo, not all press is created equally, and content can perform drastically differently within the same publication. Let’s take a look:

How Share of Voice in the press is traditionally calculated

Legacy media monitoring tools like Meltwater and Cision typically allow you to calculate Share of Voice in two ways:

1) Volume of press = ([# of mentions for your brand] / [# of mentions for your brand + competitors]) x 100

2) Potential Reach = ([your brand’s total potential reach] / [aggregate potential reach of your brand + competitors]) x 100

While method #1 gives your team a general understanding as to how often your brand is written about versus your competitors and method #2 gives your team a sense as to the average prominence of the pubs writing about you versus your competitors, both are missing a critically important aspect of coverage performance: what’s working for my competitors? How many people are actually reading these articles? 

Rethinking Share of Voice for 2022 (and beyond)

To accurately assess how you stack up against your competitors, look at Share of Readership (SOR), which gives you a competitive benchmark grounded in reality, and better identifies opportunities to insert your brand in the conversations that resonate most in your industry.  

Let’s look at a real-world example comparing SOV to SOR between two major brands during June 2022: Hulu and Netflix. (Full disclosure: While this is actual data exported directly from a competitive report in Memo’s dashboard, I’ve changed the time period and names of the companies for this article to respect customer privacy.)

Tracking from a media list of the top 400 publications in the US, here is the breakdown in coverage:

  • Hulu mentions: 708 articles, 10.54 billion impressions
  • Netflix mentions: 694 articles, 10.13 billion impressions

Using method #1, Hulu and Netflix have a share of 50.5% and 49.5% of the coverage respectively – about a 50/50 split.

Using method #2, Hulu and Netflix’s share of impressions come out to 51% and 49% – again, about a 50/50 split.

So if I’m Hulu or Netflix, there’s not a whole lot to take away from SOV analyses based on clip counts or impressions, other than to keep chipping away at the competition by doing more of what we’re doing already. This is where treating all press equally, even if from the same publication, can mask critical indicators of competitive performance.

Here’s why: The combined 708 articles Hulu was mentioned in had a total of 6,221,717 readers. Netflix’s 694 articles, however, were read a total number of 12,019,205 times:

Netflix has a Share of Readership of about 66% whereas Hulu has a SOR of about 34%, a much different outcome for the month of June, and a jumping-off point to deeper insights: what press led Netflix to capture more interest from readers? How can Netflix reinforce its dominance? Where are the relevant topics for Hulu to insert itself next month? 

Impressions and clip counts don’t just miss; they mislead

Based on traditional SOV analyses, Hulu and Netflix would have both come to incorrect conclusions about where they sit in the competitive landscape.

And it’s easy to see why traditional SOV would mislead them: they’re fairly similar competitors who get written about with similar frequency in similar publications. Treating each article equally (method #1), or treating each article within a publication equally (method #2) completely ignores the variation in how readers respond to different content. (We published an entire report on readership vs UVMs here.)

If your goal is measuring how consumers are engaging with you versus the competition, shouldn’t success and SOV be defined by the number of people that are actually being reached?

Understanding your competitors’ success can no longer just involve understanding where and how many times they are getting mentioned in the press. Readership finally allows brands to dig deeper and see what’s truly working in the competitive landscape. Will you seize the opportunity?

To learn more about how accurate readership can uncover how you’re really measuring up against the competition, check out Memo’s approach to comms measurement.

How to roll out readership in your Comms org: 9 tactics from Memo customers

“Data like readership is for the Comms team of the future. A change not for the unambitious – and a challenge to the status quo that has eclipsed PR for decades.” –CCO, Fortune 500 company

How can I convince the data skeptics in our group to track readership? How do we send campaign reports with thousands of readers when executives are used to millions of impressions? How have other customers introduced this new metric?

You’re not alone. We’ve heard it all. From the most data-hungry communications teams to groups just getting their measurement practice off the ground, all Memo customers share the same challenge: adopting a metric of earned-media measurement for which there is no organizational precedent or historical context.

But change is the only constant in life, as the adage goes, and PR measurement is definitely changing. It would be disingenuous to pretend that widely adopting readership is as easy as flipping a switch; most of our customers are global corporations with a complex network of Comms groups and stakeholders to navigate. 

Yet time and time again, we’ve seen our users grow from a core group of early adopters at a brand to an organization-wide audience. Here are 9 ways we’ve seen these customers successfully introduce and report out readership, often in combination with each other. 

The takeaway: Rolling readership out incrementally, leading with insights, and reporting in a way that is aligned with but enhances existing practices is the best way to garner buy-in and adoption.

Introduce readership incrementally (#1-3)

Instead of overhauling their PR reporting from the outset, most teams find success rolling out readership incrementally. This means a select group of people have access to Memo’s platform, and they selectively loop in new team members through various reports. Over time, stakeholders get accustomed to seeing readership regularly and begin to proactively request readership in additional reporting.

Here are the Memo tools we’ve seen leveraged to slowly but steadily disseminate readership: 

#1: Circulate top-read press via daily Readership Emails 

These daily reports of the three top-read headline and non-headline mentions are an easy way to start distributing readership data throughout an organization. There’s no limit on the number of recipients, and we’ve seen these emails balloon from a group of four people in a measurement team to dozens of Comms employees, all the way up to the CCO.

#2: Isolate readership with campaign-specific Flash Reports

Many customers use Flash Reports, which are on-demand readership summaries of specific campaigns or news cycles, as a stepping stone to reporting out readership more broadly.

Flash Reports answer questions that are top-of-mind for a team running a campaign – e.g. How many people did we reach? Which outlets had the biggest impact? How did interest in this news cycle play out over time? – without making them sift through data on coverage that’s not relevant to them.

#3: Dazzle executives with MRV summaries

To combat the common fear that “trading millions of impressions for thousands of readers” will make communicators look worse (it won’t, we promise!), presenting MRV (Memo Readership Value) alongside readership to executives is a great entry point to reframing the value of a reader.

We write more about MRV here, but in brief, it’s a methodology to assign a dollar value to earned readership using paid-media rates in a way made possible with accurate article readership and traffic source data.

Lead with insights (#4-6)

Many customers generate buy-in for readership by showing how easily it lifts the veil on long-held questions and takes the guesswork out of campaign planning. Leading with insights over metrics will help connect the dots between readership and how it can be actioned. Here are some ways to surface these insights:

#4: Report aggregate readership at the outlet level

Definitively answering which outlets and reporters perform best for your campaigns is nothing short of a superpower – and fortunately this intel is readily available in your Memo dashboard. 

Next time you’re tasked with providing strategic guidance on media outreach, filter your coverage for topics related to that campaign and you’ll have a clear view into the most impactful sources:

#5: Share findings and takeaways from Insights Reports

Insights Reports are custom analyses designed to answer key questions on earned-media performance and strategy, and readership has taken these insights to a whole new level (see 10 PR strategy questions finally answered with Insights Reports). 

We’ve witnessed multiple customers get Comms groups hooked on readership by introducing it through insights reporting. Typically, our primary contacts monitor for opportune moments to support analyses and planning with readership. They’ll tell their Memo rep the questions they’re hoping to answer with readership, and our Insights team gets to work. 

#6: Introduce readership within a Reporter Database

Memo’s Reporter Database isn’t just a list of names with the coverage they’ve authored; it’s an entirely new way of helping Media Relations teams prioritize relationship building and outreach. It includes readership on reporters’ articles, tags for frequently covered topics, and summary stats for easy comparison.

Enhance existing reporting (#7-9)

Finally, customers often treat readership as additive in the early days, using it to enhance existing measurement while they allow time to understand the best way to phase out legacy practices.  

#7: Report readership alongside other metrics

One large corporation was not ready to eliminate UVMs from their global reporting, but still wanted to include readership in campaign summaries. So in a global campaign recap, they reported their usual metrics – clip counts, UVMs, social engagement – and introduced a new metric: “verified readers from our new partner, Memo.” 

#8: Report relative performance instead of absolute values

For groups that are anchored on massive impression numbers, it can take time to make readership palatable, especially if those audiences aren’t privy to the insights and context of longtime Memo users. Ways we’ve seen customers report out readership results without readership itself include:

  • % of your brand’s readership driven by a specific article/publication/topic (e.g. “this placement is responsible for 58% of our announcement’s readership”)
  • An article’s readership percentile (e.g. “this placement’s performance is in the 90th percentile for our historical coverage”) 
  • The % of readership your brand received on an outlet relative to competitors (e.g. “Acme Corp had over 2x more readership on Fortune last month than competitors”)

#9: Add “share of readership” to SOV reports

Related to the above, monitoring share of readership amongst competitors, especially when contrasted with share of coverage volume, reveals who is generating meaningful engagement with their press – and is a powerful way to demonstrate why readership provides a more accurate view of media performance.

There’s no silver bullet to transforming a measurement practice overnight, but Memo provides multiple tools (and some wonderful customer success reps) to help you steadily introduce readership and prove the value of more accurate measurement.

How 4 customers showed ROI on their switch to readership

Return on investment. It’s a phrase used relentlessly in all aspects of business, and a particularly difficult metric for Comms teams to measure. Put another way, “being asked for ROI is the perennial thorn in my side,” per one Memo customer.

Determining a hard ROI from earned programs – that is, a quantifiable bottom-line outcome resulting directly from money invested – is in practice impossible. Not because earned press isn’t valuable, but because it is part of a larger customer journey and should be evaluated more holistically with an integrated marketing program.

For example, any traffic or sales you can directly attribute to an editorial product review only represent a fraction of that article’s wider impact. That press also drove brand awareness, product consideration, and purchase intent – even if that purchase happened several months after the fact. 

(That’s not to say there aren’t better ways to report the value of earned media. Memo’s goal has always been to help our customers prove with data what we already know: earned media is extremely valuable, we just need better measurement for it. Whether it’s providing metric parity with paid media, or even helping calculate the paid media cost of your earned engagement, readership is making the results PR delivers more tangible and moving us closer to isolating its ROI within the greater marketing mix.)

But given all the intangible outcomes that earned ROI fails to capture, proving out ROI on the tools you need to get the job done is even more difficult.

Fortunately, four Memo customers have paved the way, sharing how Memo’s data and team of experts helped them demonstrate a return on their platform investment. In brief, it comes down to showing how readership helped them move faster, plan better, and respond smarter.

#1: Time is money (return on media research)

A home-goods company was launching physical stores in a new location. They wanted to get the word out, but having no relationships or prior experience in this new region, they needed help determining which local outlets and journalists to pitch. 

To ensure they were spending their time and resources wisely, they leaned on Memo readership data to quickly identify the most-read local outlets and journalists to create a go-to-market strategy with assured success.  

#2: Don’t make a small problem a big problem (return on crisis response) 

A global fast food brand was in crisis, but didn’t know just how deep. Was their most recent crisis a national or maybe even global dilemma? Or was this actually only capturing attention in local markets where the incident occurred? 

Enter readership. Memo was able to confirm that while readers were somewhat engaged on local outlets, the story was generating very low readership on national news outlets. Based on this finding, the brand was able to minimize harm by not bringing more attention to the crisis with a national response, and instead developed a response strategy that was targeted locally.

#3: Turning good data into great data (return on business analytics)

An American automotive brand already had an impressive media quality scoring algorithm that they used to inform their communications strategy. It included inputs like sentiment, tonality, message pull-through, and potential reach. However, this last metric was inflating and skewing their dataset, creating a less valuable scoring output.

By replacing outlet-level potential reach with article-level readership in their algorithm, the brand was able to uncover a whole slew of insights by identifying varying performance at the article level and adjusting their strategy accordingly. (More on UVMs vs Readership here.)

#4: Timing is everything (return on campaign planning) 

A Comms team for a global streaming service was trying to understand why some competitors were more successful than others when promoting new content. 

Utilizing Memo insights reporting and our team of analysts, they found that while there were many similarities in the publications and even journalists writing about these launches, the clear indicator for success came down to timing. Memo analysts ran a timing analysis that pointed to higher readership on shorter campaigns. Specifically, campaigns that launched closer to the content release date were getting more engagement, with the sweet spot being 14-20 days prior to release.

The brand was able to use this insight to alter their launch strategy to minimize promotion and spending too soon, and ramp up efforts when they were 20 days out from release. This adjustment not only resulted in higher readership, but also time and cost savings leading up to the launch.

How to compare owned channels with earned press on Memo

How does readership on owned content from our corporate press center/blog/news site compare to readership on earned press?

It’s a question we receive a lot, and fortunately, it’s a question that’s incredibly easy to answer for two reasons: first, readership on earned coverage provides an apples-to-apples comparison to unique visitors on your owned site (it’s the same metric!). And second, Memo offers an integration.

Below we outline the steps to add your owned-and-operated content to your Memo dashboard, and we highlight some of the major insights this capability offers customers.

Tracking owned channels on Memo: benefits & use cases

Some customers are merely curious about owned versus earned readership, while others have specific goals in mind:

Secure more budget for earned campaigns. Readership removes any questions on how many people your campaigns reached. Showing how earned performance stacks up to owned can strengthen the business case for investing in PR.

Place the right content in the right place. Over time, you may start to surface patterns in the type of content that does best on your owned sites versus through the press.

Contextualize earned readership. When seeing article readership for the first time, people often ask “is this good?” Owned readership provides an immediately accessible benchmark. 

How to track readership from owned channels on Memo

Step 1: Give Memo read-only API access to your channel’s Google Analytics. We can use the Google Analytics API to fetch a URL’s unique visitor count. Go to and navigate to the property associated with content you want to track on Memo:

Then go to Admin > Account Access Management > Add users. Enter the email address provided by your Customer Success Manager at Memo, and select “Viewer” under roles (this ensures Memo can pull readership with the Google Analytics API but cannot make any changes to your Google Analytics reporting or account settings).

Step 2: Email a list of owned URLs to your Memo rep We need to know the specific content you want to pull into your Memo dashboard. So once per week (or less frequently, if preferable), we’ll ask you to email us a list of URLs to track. 

…and that’s it It’s that easy. Some important implications though: adding your owned content to Memo dashboard will automatically include that readership data in your reporting. You can use filters to exclude owned channels:

Frequently asked questions about tracking owned channels

Is there an additional charge for tracking owned content with Memo? No, the generous Customer Success team at Memo is happy to facilitate this add-on free of charge.

Can I track owned content if we don’t use Google Analytics? Yes, Memo has additional implementation options. Contact your Memo rep to find the best solution for your configuration.

Will my owned readership be available to other Memo customers? No, your owned channel can only be tracked on Memo accounts that you have authorized.

Have a question we didn’t answer? Get in touch at

Finding value where others have not: PR’s Moneyball moment

“If we try to play like the Yankees in here, we’re going to lose to ‘em out there.” – Moneyball

What’s the goal? In chess, it’s to checkmate your opponent. In baseball, it’s to win games. In Public Relations, the goals vary – to build awareness, earn trust, drive sales, etc. – but every PR campaign does start with a goal. 

That’s the thing about the goal: it’s the easy part. Once established, the next steps get interesting. What’s the best strategy to achieve the goal? What tools give us the best chance of success? How do we get there? 

In the almost two centuries since the first ball players started playing baseball, the goal has remained the same but the game has changed drastically. What once began as a backyard game with a yarn-and-leather ball and a bat made from excess lumber, is now a multibillion-dollar industry with 100 MPH fastballs, acrobatic catches, and more data generated from a single pitch than could be stored on the computer that took us to the moon.

But one simple truth that hasn’t changed is that there are big-market teams and small-market teams, each with a corresponding budget to manage its roster. Every team has the same access to the MLB draft, but as players perform better and win, they command a bigger payday. As is often the case, All-Stars and MVP’s sign big contracts with large market teams, leaving the small market teams to go back to the drawing board and rebuild.

So what can the small-market teams do? There’s a famous line in the based-on-a-true-story movie Moneyball, where the Oakland A’s are trying to figure out how to replace their All-Star first baseman Jason Giambi, who they just lost to the deep-pocketed Yankees. As the coaches review their options, it becomes clear that there isn’t another Giambi out there. Even if there were, the A’s couldn’t afford him. Over the chatter of disappointment, General Manager Billy Beane remarks, “if we try to play like the Yankees in here, we’re going to lose to ‘em out there,” pointing to the empty ballpark. 

Billy wanted to win. That was his goal. Billy (along with assistant Paul DePodesta) figured out that in order to win, his strategy couldn’t be to buy players; he needed to buy wins. In order to buy wins, he needed to buy runs. 

Billy knew the A’s weren’t the Yankees. But if they could use sophisticated statistics to put together a roster of players that consistently got on base and put runs on the scoreboard, the A’s could be a contender. By looking at draft picks through this lens and bringing in players that the rest of the league had undervalued, the A’s might actually make the playoffs. That’s exactly what they did, and the advanced data analysis whose usage they pioneered still drives strategy in the MLB today.

I think about Moneyball a lot when I think about what we’re doing at Memo. There will always be opportunities to buy a big splashy ad or hire a top-tier influencer if your wallets are deep enough. But does that always achieve the goal? Even so, is that a sustainable approach? 

The good thing is, it doesn’t matter. Whether you’re a Fortune 100 or a nimble startup, new data means the PR playbook is changing – you just have to start thinking like Billy Beane. Instead of aiming for volume of press hits, aim for volume of readership. Instead of optimizing for potential reach, optimize for real reach. Instead of monitoring passing likes on social, monitor true engagement with an article. Memo’s publisher-direct readership data enables all of this.

No matter the goal of your PR campaign, readership provides the north star to what’s resonating, what’s not, and how to build a roster of tactics that others in your field have overlooked. 

Baseball isn’t played with scrap yarn and lumber anymore, and the PR function of tomorrow won’t look like the PR function of today. Memo is here to help you change the game.

The future of PR, part 3: The future belongs to storytellers. How will we empower them?

This piece was adapted from “Earned Media’s Value: The True Story,” a compilation of conversations held between PRWeek, Memo, and industry leaders from brands like Mastercard, Walgreens, and Goldman Sachs on the new era of PR measurement.

Stories are essential to our culture: from fables to parables to novels to Netflix, stories are how we learn and how we connect with others. Everyday we see the tremendous importance of narrative. To rally action. To move markets. To open minds.

For brands, storytelling is a crucial tool for connecting with their customers. As the famed Simon Sinek said, “people don’t buy what you do, they buy why you do it.” Put another way – people buy your story. 

If a story falls in a forest though? Good storytelling is only effective if someone hears it. Despite the rise of social media, news publications remain one of the most important channels for brands to tell and reinforce their stories. Social posts are often a flash in the pan, but a well-placed article can boost a brand’s SEO for years to come. 

I would argue there is no other medium that exists today where you can consistently get someone to spend the same amount of engaged time learning about your company’s messaging, values and products. Earned media offers companies the institutional trust that media publishers have spent decades building. 

Yet with all this value being created, I’m astounded by the gaps I see in how earned media – and by extension the PR and Comms function – has been measured and quantified. It’s my belief that our industry has a data problem. 

For too long, PR has been anchored on metrics that attempt to capture its worth with potential numbers or estimates. While marketing and brand measurement has become increasingly precise, communicators have been left to create a patchwork of flawed data that fall short in showing the true value of their work. PR professionals deserve a more accurate and complete picture – and that’s what we’re working to give them. 

I founded Memo with a mission to move the industry closer to measurement befitting the value PR delivers. As data becomes more essential to fueling effective comms strategies and guiding the C-suite, it will also be the key to ensuring earned media gets the credit and recognition it deserves.

In a world driven by stories, the future will belong to storytellers. Let’s give them the right data to prove it.

Read the full series of roundtables on PRWeek: