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Content Marketing Measurement Guide: 23 Definitions To Know

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Content Marketing Measurement Guide: 23 Definitions To Know

Every time I use the words “analytics,” “metrics,” or “KPIs” in a discussion about the impact of content, a little voice goes off in my head. It’s the voice of Inigo Montoya from the movie, The Princess Bride: “You keep using that word. I don’t think it means what you think it means.”

While content marketers may recognize these terms relate to content measurement, it’s easy to confuse their distinctions. Read on for explanations of 23 common measurement terms and how they fit into your content’s performance strategy.

Content measurement definitions

Analytics

Marketo defines analytics as the practice of managing and studying metrics data to determine the ROI of marketing efforts like calls to action, blog posts, channel performance, and thought leadership pieces, and to identify opportunities for improvement.

Bounce rate

According to Google Analytics, a bounce rate is a single-page session divided by all sessions on your site. A bounce is a session that triggers a single request to the analytics server, such as when a user visits a page on your site and exits without taking further action. While a site exit doesn’t tell you much about your content (everyone leaves your site at some point), a page with both high exit and bounce rates may need changes to the content.

The bounce rate is a single-page session divided by all sessions on your site, says @joderama via @CMIContent @Acrolinx. Click To Tweet

Click-through rate (CTR)

A click-through rate is the percent of total viewers or recipients who clicked a link in a content asset (clicks divided by total recipients). It’s commonly used to gauge success for email campaigns, newsletter-driven website visits, and content promotions (e.g., display ads, native advertising), where the total number of recipients can be quantified (rather than estimated).

Conversion/conversion rate

A conversion happens when a consumer takes an action after engaging with your content. The action is what your organization designates as meaningful – purchasing a product, registering for an event or a gated asset, subscribing to a blog or newsletter, or joining a social media community. Calculate the conversion rate by dividing the number of visitors to the content who converted by the total interactions with that piece of content.

Customer acquisition cost

A customer acquisition cost is how much the company spent to obtain that customer. Take all the expenses – product research, development, manufacturing, marketing, advertising, etc. Divide that total by the number of customers within a designated time frame.

Calculate the customer acquisition cost by adding up all expenses and divide by number of customers in the time frame, says @joderama via @CMIContent @Acrolinx. Click To Tweet

Downloads

The download metric is commonly used to gauge performance for lead-magnet content assets like white papers, e-books, and infographics. It indicates a deeper level of engagement and interest than a view or visit because the user found the content valuable enough to save a copy to explore in more detail or share with others in their networks.

Engagement

Engagement is considered both a fundamental content metric and a content marketing goal. As a metric, it’s broadly defined as an act of content consumption –opening an email newsletter, reading a blog article, clicking on an ad or an interactive asset, or liking/commenting on a social media post. While engagement indicates at least a passing interest in your content, it’s not a particularly informative indicator of why the content captured audience interest. It’s often best used to contextualize other metrics rather than as a definitive decision-making tool.


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Entrances/exits

Entrances are the number of times visitors enter your site through a specific page or set of pages. Likewise, exits indicate how often visitors end their site visit on that page. A page with a high entrance rate could indicate it’s well-optimized for search. However, neither entrance nor exit rates are clear indicators of content success (or failure) on their own. It’s a good idea to correlate this data with other insights – bounce rates, time on site, user flow, and referral traffic sources – to get a clearer picture of what it indicates about your content performance.

Goals

Goals are the desired business outcomes to be achieved through your content marketing strategy. While the stated goal of content marketing is to drive a profitable action, your goals should be more specific and quantifiable, such as increasing sales conversions, saving the company money, building (or growing) a subscribed audience, or driving greater customer loyalty and brand satisfaction.

#ContentMarketing goals should be specific and quantifiable, says @joderama via @CMIContent @Acrolinx. Click To Tweet

KPI

KPI stands for key performance indicators. They are standard, agreed-on measurements for assessing progress against your content marketing goals. Potential KPIs might be average conversion rates, number of leads, quality of leads, or revenue per new customer.

Marketing-qualified lead (MQL)

MQLs are leads generated by the marketing team that satisfy the criteria to pass along to the sales team for further outreach.

Metrics

In contrast to KPIs, metrics are the business-as-usual measurements for things that add value to your organization but aren’t focused on the most critical goals. They might include website page views or likes on social media posts. Think of these as the “what-needs-to-be-true” numbers that can help you achieve or optimize your KPIs.

Objectives and key results (OKR)

OKR is a method to determine which metrics best gauge performance against your goals. It starts with designing a measurement pyramid that includes goals, key performance indicators, and metrics. CMI’s chief strategy advisor Robert Rose details the OKR process here. The end result should be your business mission segmented into strategic objectives. Each segment should connect to the OKR pyramid and be a source tool for each metric that goes into it.

An example of OKR architecture results, mapped out.

Click to enlarge

Open rate

An open rate is a metric related to content delivered via email. It measures the percentage of subscribers who opened the email regardless if they clicked on any of the links in that content. Already limited in value due to its narrow focus, its reliability has come into question even further with the advent of Apple’s iOS email tracking changes.

Page views vs. unique page views

Commonly used to gauge website traffic, page views are the total number of times a site page is loaded by all visitors over a set time called a session, usually lasting 30 minutes. If a visitor views the same page three times during a session, total page views increase by three.

In contrast, a unique page view tracks views based on the visitor’s unique IP address, device, and browser. In the example above, the visitor who viewed the same page three times in a session would count as one unique page view. However, let’s say the visitor viewed the page two times in a Google Chrome browser and one time in a Microsoft Edge browser from the same URL. That would count as two unique page views.

If your website content is configured for Google’s Universal Analytics, look for page views and unique page views for each of your site page URLs under Behavior > Site Content > All Pages. If you’re working with Google Analytics 4, you’ll find the pages report under Engagement > Pages and screens, but will need to do some additional configuration to view data by page URL instead of the page title.

Referral traffic/rates

When a visitor reaches your domain through a third-party link (other than a search engine), it’s tracked by Google as referral traffic. In Universal Analytics, you can find referral data under Attribution > All Traffic > Referrals. For GA4, click on the Reports link in the left-side menu, navigate to Acquisition > Traffic acquisition, then type “referral” in the search box and hit enter.

You can see the sources that led visitors to your site, how many visits were referred from each source, and additional data on their behaviors after arriving on your site. As a metric, it’s a useful indicator of brand awareness and thought leadership. The more sources that send traffic your way, the more highly regarded your domain likely is – an outcome that leads to better domain authority and better rankings of your content on search.

The more sources that send traffic your way, the better domain authority and ranking of your #content on search, says @joderama via @CMIContent @Acrolinx. Click To Tweet

Registrations/subscription numbers

While gaining subscribers is among the top goals for content marketing (particularly for content brands and entrepreneurs), it’s also a metric tracked to gauge progress toward other achievements in the marketing funnel.

It refers to the total number of people who completed a form or other action to gain access to your content – attend an event, download a lead-magnet asset, receive email newsletters, join your brand community, etc.

When registrants or subscribers renew, that renewal rate is a metric that can be used to gauge brand loyalty.

Return on investment (ROI)

Return on investment is a broad term to describe how a company’s marketing initiatives drive profitable actions and business growth. Knowing ROI for content campaigns enables marketers to determine appropriate budget allocations, maximize the efficiency of each marketing expense, and demonstrate the impact of their efforts to their executive stakeholders.

Though it’s (arguably) the most critical measurement of a marketing technique’s effectiveness, the complex nature of attributing conversions to a particular asset can make content ROI difficult to calculate precisely, let alone prove definitively.

Sales-qualified lead (SQL)

An SQL is lead qualified by the sales team as active in the market. These leads are more likely to become a customer than an MQL.

Subscriber count

Subscribers are defined as audience members who have taken an action around your content (and provided some personal data to do so) in exchange for an expectation of receiving ongoing value. It is a core metric for measuring content marketing value.

Time on site/time on page

These metrics indicate how long a visitor spends on the site or a page. Visits that exceed the average time on page (or site) are a positive indication of interest and engagement with that content. However, it’s impossible to tell using this metric alone whether the user actively engaged with the content all that time or simply left it open on their browser.

Video views/duration

Video views measure how many times a video asset is watched. Duration indicates the time the average viewer plays that video. Just because a video was viewed in its entirety does not mean the viewer actively engaged with all of it.

Visits/unique visitors

A visitor is any internet user who arrives on your website (or mobile website). Seems simple, right? But what’s involved in characterizing that visit and how it gets factored into content measurement is more complicated.

In Google Analytics, to track site visits, the user needs to have enabled tracking cookies. (This is why the end of third-party cookies was likened, at least at first, to the end of digital marketing.)

There also is a distinction between visits and unique visitors. Visits encompass any time a user visits your site. Unique visitors refers to the number of people who browsed your site during a session. A unique visitor who visited several times during that session would count as one unique visitor. If they returned after the session, that would count as another unique visit.

Know what’s in the measurement name

Every content marketing program requires a solid measurement strategy. By knowing the terms and understanding how they fit in your brand’s content marketing, you’re at the start of a successful evaluation of your content’s effectiveness.

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Cover image by Joseph Kalinowski/Content Marketing Institute

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The Biggest Ad Fraud Cases and What We Can Learn From Them

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The Biggest Ad Fraud Cases and What We Can Learn From Them

Ad fraud is showing no signs of slowing down. In fact, the latest data indicates that it will cost businesses a colossal €120 billion by 2023. But even more worrying is that fraudsters’ tactics are becoming so sophisticated that even big-name companies such as Uber, Procter & Gamble, and Verizon have been victims of ad fraud in recent years. 

So what does this mean for the rest of the industry? The answer is simple: every ad company, no matter their size or budget is just as at risk as the big guns – if not more. 

In this article, I summarize some of the biggest and most shocking cases of ad fraud we’ve witnessed over recent years and notably, what vital lessons marketers and advertisers can learn from them to avoid wasting their own budgets. 

The biggest ad fraud cases in recent years 

From fake clicks and click flooding to bad bots and fake ad impressions, fraudsters have and will go to any lengths to siphon critical dollars from your ad budgets.

Let’s take a look at some of the most high-profile and harmful ad fraud cases of recent years that have impacted some of the most well-known brands around the world. 

Methbot: $5 million a day lost through fake video views 

In 2016, Aleksandr Zhukov, the self-proclaimed “King of Fraud”, and his group of fraudsters were discovered to have been making between $3 and $5 million a day by executing fake clicks on video advertisements. 

Oft-cited as the biggest digital ad fraud operation ever uncovered, “Methbot” was a sophisticated botnet scheme that involved defrauding brands by enabling countless bots to watch 300 million video ads per day on over 6000 spoofed websites. 

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Due to the relatively high cost-per-mille (CPM) for video ads, Aleksandr and his group were able to steal millions of dollars a day by targeting high-value marketplaces. Some of the victims of the Methbot fraud ring include The New York Times, The New York Post, Comcast, and Nestle.

In late 2021, Aleksandr Zhukov was sentenced to 10 years in prison and ordered to pay over $3.8 million in restitution. 

Uber: $100 million wasted in ad spend 

In another high-profile case, transportation giant Uber filed a lawsuit against five ad networks in 2019 – Fetch, BidMotion, Taptica, YouAppi, and AdAction Interactive – and won. 

Uber claimed that its ads were not converting, and ultimately discovered that roughly two-thirds of its ad budget ($100 million) wasn’t needed. This was on account of ad retargeting companies that were abusing the system by creating fraudulent traffic. 

The extent of the ad fraud was discovered when the company cut $100 million in ad spend and saw no change in the number of rider app installs. 

In 2020, Uber also won another lawsuit against Phunware Inc. when they discovered that the majority of Uber app installations that the company claimed to have delivered were produced by the act of click flooding. 

Criteo: Claims sues competitor for allegedly running a damaging counterfeit click fraud scheme 

In 2016, Criteo, a retargeting and display advertising network, claimed that competitor Steelhouse (now known as MNTM) ran a click fraud scheme against Criteo in a bid to damage the company’s reputation and to fraudulently take credit for user visits to retailers’ web pages. 

Criteo filed a lawsuit claiming that due to Steelhouse’s alleged actions — the use of bots and other automated methods to generate fake clicks on shoe retailer TOMS’ ads — Criteo ultimately lost TOMS as a client. Criteo has accused Steelhouse of carrying out this type of ad fraud in a bid to prove that Steelhouse provided a more effective service than its own. 

Twitter: Elon Musk claims that the platform hosts a high number of inauthentic accounts 

In one of the biggest and most tangled tech deals in recent history, the Elon Musk and Twitter saga doesn’t end with Twitter taking Musk to court for backing out of an agreement to buy the social media giant for $44 billion.

In yet another twist, Musk has also claimed that Twitter hid the real number of bots and fake accounts on its platform. He has also accused the company of fraud by alleging that these accounts make up around 10% of Twitter’s daily active users who see ads, essentially meaning that 65 million of Twitter’s 229 million daily active users are not seeing them at all. 

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6 Lessons marketers can learn from these high-profile ad fraud cases 

All of these cases demonstrate that ad fraud is a pervasive and ubiquitous practice that has incredibly damaging and long-lasting effects on even the most well-known brands around the world. 

The bottom line is this: Marketers and advertisers can no longer afford to ignore ad fraud if they’re serious about reaching their goals and objectives. Here are some of the most important lessons and takeaways from these high-profile cases. 

  1. No one is safe from ad fraud 

Everyone — from small businesses to large corporations like Uber — is affected by ad fraud. Plus, fraudsters have no qualms over location: no matter where in the world you operate, you are susceptible to the consequences of ad fraud. 

  1. Ad fraud is incredibly hard to detect using manual methods

Fraudsters use a huge variety of sneaky techniques and channels to scam and defraud advertisers, which means ad fraud is incredibly difficult to detect manually. This is especially true if organizations don’t have the right suggestions and individuals dedicated to tracking and monitoring the presence of ad fraud. 

Even worse, when organizations do have teams in place monitoring ad fraud, they are rarely experts, and cannot properly pore through the sheer amount of data that each campaign produces to accurately pinpoint it.

  1. Ad fraud wastes your budget, distorts your data, and prevents you from reaching your goals

Ad fraud drains your budget significantly, which is a huge burden for any company. However, there are also other ways it impacts your ability to deliver results. 

For example, fake clicks and click bots lead to skewed analytics, which means that when you assess advertising channels and campaigns based on the traffic and engagement they receive, you’re actually relying on flawed data to make future strategic decisions. 

Finally – and as a result of stolen budgets and a reliance on flawed data – your ability to reach your goals is highly compromised. 

  1. You’re likely being affected by ad fraud already, even if you don’t know it yet

As seen in many of these cases, massive amounts of damage were caused because the brands weren’t aware that they were being targeted by fraudsters. Plus, due to the lack of awareness surrounding ad fraud in general, it’s highly likely that you’re being affected by ad fraud already. 

  1. You have options to fight the effects of ad fraud  

Luckily, as demonstrated by these cases, there are some options available to counteract the impact and losses caused by ad fraud, such as requesting a refund or even making a case to sue. In such cases, ad fraud detection solutions are extremely useful to uncover ad fraud and gather evidence. 

  1. But the best option is to prevent ad fraud from the get-go

The best ad fraud protection is ad fraud prevention. The only surefire way to stop fraudsters from employing sophisticated fraud schemes and attacking your campaigns is by implementing equally sophisticated solutions. Anti-ad fraud software solutions that use machine learning and artificial intelligence help you keep fraud at bay, enabling you to focus on what matters: optimizing your campaigns and hitting your goals. 


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