If you’re immersed in the world of content, it’s more than likely that you hear the word “engagement” dropped into marketing conversation on a daily basis. It’s often phrased as a question: How do we engage audiences? How do we measure and score engagement? And how does engagement stack up against other metrics?

These are all important questions. Engagement is not a passing buzzword. It’s an incredibly powerful metric. It captures not just interest, but a wide range of detailed information about your users’ experiences and activity. Engagement allows you to “listen” to the feedback provided by their data. What’s more, it can be linked to revenue and other important organizational outcomes—finally applying a clear ROI for what has previously been difficult to measure.

In the not too distant past, companies looked to the number of “clicks,” “likes” and “fans” to measure the success of a campaign. However, the metric of engagement is much more substantial than a simple head count. It captures information about audience behavior—behavior patterns that are likely to repeat through large groups of people, and ultimately allow for predictive analytics. That’s why I believe that engagement is today’s ultimate metric.

In this white paper, I explain why engagement is the best metric to measure and score success. I review the history of engagement as a metric. Based on my experience, I propose a framework for understanding engagement, and describe how the availability of data has made measuring engagement so accessible for all marketers.

The Emerging Metric

While the measurement of engagement is a recent phenomenon, the concept is not new. In the age when marketing was dominated by signs, leaflets, and face-to-face interactions, engagement was measured by actual relationships.

Engagement is the obvious next step in the evolution of satisfaction, loyalty, awareness, and favorability. With digital analytics, engagement has the ability to measure actual behavior, rather than measure behavior by proxy—with questions of intention.

Take, for example, the Net Promoter Score. Asking, “How likely is it that you would recommend [your company] to a friend or colleague?” the NPS aims to capture customer loyalty. It was accepted as the industry standard in 2006 (1), but it has its drawbacks. The question has to be posed directly to the consumer, and the score relies upon self-reported information that doesn’t necessarily match the consumer’s actual behavior. Engagement bypasses these pitfalls. You don’t have to ask the question, because you already have the information—real, reliable data collected at the time of the experience.

Yet, engagement has been surprisingly absent from the discussion and largely ignored by academics. For example, a 2007 publication from Wharton School Publishing and a 2013 publication from a top marketing professor—both documenting the top rated marketing metrics—did not include engagement. (2)

But that’s changing. In a review of peer-reviewed publications about engagement and audiences, I found that the frequency of these texts has since steadily risen:

Frequency of Scholarly Publications About Engagement:

The research tells the story of engagement’s recent emergence as a metric. It’s only been in the past few years that engagement has been seriously considered in academia, as it has gained awareness in marketing, advertising, and business. The reason for this is the ability to extract behavioral data from the relationship between audiences and brands, galvanized by the drive towards engaging content and personalized experiences. A handful of forward-thinkers recognized the value of engagement, the ability to measure it, and began to discuss the necessity and logistics of a metric.

The Search for a Definition of Engagement

Research institutions, academics, and businesses have developed definitions and metrics of engagement that work for both broad and precise examination of engagement rates.

The first suggestion of a comprehensive definition came in 2006, when the “The Engagement Steering Committee,” a collaboration of leading media and advertising organizations, formed with the express purpose of creating an industry-wide definition and audience engagement metric. They decided on “turning on a prospect to a brand idea enhanced by the surrounding context.” (3)

Since 2006, other specific metrics have been advanced to measure engagement. These include the following:

• Trial, Repeat, Penetration, and Volume Projections: new visitors, returning visitors

• Usage: click-depth and duration, likes, ratings, votes, comments, shares, uploads, blogs, podcasts, suggestions, feedback, comments, recommendations, endorsements, spinoff content

• Attitudes: responses to emotion-based statements like “the organization is perfect for people like me,” “I am proud to be their customer,” and “the organization always delivers on promises”

• Recency, and Retention: the frequency with which audiences return

• Baseline Sales, Incremental Sales and Promotional Lift: brand-lift, post’s reach, reach influencers, traffic directions

• Impressions, Page views, and Hits: impressions, hits, play rate, play-through rate, completion rates, median video viewing time, expansions, content downloads, pages or sessions per visit, clickthrough rates, interaction time

• Visits, Visitors, and Abandonment: unique visitors, visitor frequency, bounce rate

The tactics used to collect these metrics vary. They include websites, apps, digital tracking, software, and online platforms. The data collected are touch points with stakeholders. The methods are often innovative and creative ways to create a unique audience experience. Moreover, they simultaneously and strategically collect valuable data.

The engagement metric is an important component of research that helps evaluate a brand’s performance, audience experience level, and brand reputation. Here are a few examples:

• The WetPaint/Altimeter Group focused on an organization’s social media presence across eleven possible channels. It performed a regression analysis to compare this ‘engagement score’ with financial performance. (4)

• PeopleMetrics, Inc.’s Customer Engagement model asked customers to rate two companies on a service experience from the past three months. The model consisted of eight dimensions—six emotional (authentic, attentive, engaged employees, reputation, accountable, valued) and two functional (service delivery, service/product quality). (5)

• The Marketing Science Institute showed the difference between engagement and satisfaction with a targeted survey testing the engagement rate of specific newspapers and concerts. Through interview questionnaires focused around various experience factors, the study determined that engagement is a better metric than satisfaction for reflecting a customer’s motivation to consume more of a product. (6)

• The CMO Council gauged how organizations were achieving highly adaptive audience engagements through an online brand survey. They indicated that satisfaction studies (62%), repeat sales (40%), web metrics/online engagement metrics (39%), and NPS (38%) were the best measures to assess audience experience impact and performance. (7)

• Google’s Universal Analytics tracks user activity across multiple platforms and devices, associating engagement with one unique user ID.

As these definitions, metrics, and studies show, different purposes call for different concepts of what engagement is, and how it should be measured and scored. (8) Engagement is not “one size fits all.” A significant strength of engagement metrics is that they can be customized based on what success means for your organization. Organizations should define the term in a way that shows integrity to the question at hand, and makes efficient, pragmatic use of the data available to create the best content and experiences possible.

A New Framework For Engagement: View + Attention + Connection

Although engagement measures and scores can be customized, the word still lacks clarity for data scientists. I propose that the best framework of engagement is view + attention + connection. This framework is the result of a review of literature on the subject, and my experience in conducting such research for a range of organizations.

View, attention, and connection, taken together, create a comprehensive metric that accurately, efficiently, and pragmatically measures an individual’s engagement with your brand.

• View: Your audience is aware of your brand’s engagement effort. A view is an email opened, an article clicked, an app downloaded, a video watched, and so on.

• Attention: It’s captured their time beyond a passing glance. They’ve considered it, and showed some interest.

• Connection: They act in a desired way. They shared, commented, bought, or otherwise took a positive action.

Some industries have recently begun using a variation of this view + attention + connection framework in their ROI analyses. Upworthy’s “attention minutes” (9) and Chartbeat’s “engaged time” (10) calculate if viewers are actually paying attention to the content, and for what period of time.

I believe this concept of measuring different engagement activities, scoring those activities, and finally providing an engagement score or rating will become stronger and more robust as time goes on, and will serve as the ultimate marketing metric.

Why Engagement?

My framework, as described above, creates a structure that organizations can easily understand and implement as a performance indicator. So why choose engagement over other metrics? Simply put, engagement is the ultimate metric because it is measurable and it provides a reliable way to predict future behavior.

Above all, engagement is pragmatic. Its focus on action and behavior gauges authentic involvement with a brand, rather than intention. That allows for more effective and discernible analysis. Best of all, gathering and analyzing this kind of data has become increasingly simple. Ultimately, what marketers want is an ROI calculation on their investments and a way to predict future behavior. Engagement scores can provide both.

The ability to measure engagement means that you no longer have to rely on personal observations and self-reported estimates that are inherently flawed. Digital analysis allows for ongoing sample monitoring, rather than occasional sampling that requires frequent and time-consuming surveys. Response biases in questionnaires are mitigated by focusing on what a person does—their actual behavior—rather than what a person feels obligated to say, or their stated intention. The Big Data sets are incredibly extensive, and allow for testing of alternative tactics and strategies.

Engagement improves on the shortcomings of other metrics, such as the Net Promoter Score, awareness, familiarity, and purchase intent. It combats errors of self-reported data, by doing a complete analysis of digital and in-store engagement rather than small survey samplings. It allows you to measure not only mindshare, but also attention level.

The best thing about engagement metrics is that they are action-oriented and based on experimentation. Numerical data allows for benchmarking and the strategic creation of content development. There are many ways that you can translate engagement metrics into systematic engagement plans. (11)

One of the biggest arguments for using engagement as a key metric is that you can almost always determine a ROI for it. Take the cost of producing and distributing content. Dividing that number by the number of views will give you a cost per engaged view. Then, you can calculate time viewed and come up with a cost per minute. These measurements give you the tangible, calculated cost of getting a user engaged in your content.

The second key benefit for capturing engagement metrics is that it allows you to predict future behavior. For example, if you know that a person has voted for a single party in the past three elections and contributed to that party’s causes, you can predict with confidence that they will vote for that party’s presidential candidate.

There is a degree of noise in all metrics, but engagement is as clear as any metric you can find. By setting aside intuition and rhetoric, you can focus on a system built solely on facts that can provide more actionable insights.

In a dynamic environment, being pragmatic is smart. Engagement is a metric unaffected by this dynamic environment. Regardless of rapidly changing economic, political, and social realities, audience actions—measured by engagement—will always dictate the eventual success or failure of a business.

The Enabler of Engagement: Data

The enabler of engagement is easily accessible data, ripe for measurement. Audiences who engage with a brand in a digitized or monitored environment always leave a fingerprint, which contributes to a wealth of Big Data. This data tells us who audiences are: their demographics, likes, dislikes, and what other brands they support.

This data can be used aggregately, or small sections can be used to analyze specific metrics about one’s engagement with an organization. The term “engagement” is relevant to any action involved in an individual’s purchase, attendance, or support of a brand.

The results of engagement metrics can be used for “predictive modeling.” Predictive modeling uses engagement metrics to “identify the most profitable customers, accelerate product innovation, optimize supply chains and pricing, and leverage true drivers of financial performance.” (12)

To use engagement as a helpful metric, a brand must first design an offering that can be tracked and measured. It must define the term in a way that is pragmatic for its purpose, and will enable it to interpret data in a way that translates into action and content.

Conclusion

This white paper examined the history and future of the concept of engagement as the ultimate metric for audience behavior, and recommended view + attention + connection as the most comprehensive framework for engagement.

Engagement is emerging as the silver bullet of marketing metrics. You can make a safe assumption that within the next 10 years, more companies will choose analytics as their distinctive capability to outperform competitors.

The attention economy demands consideration and time from all audiences, and there simply aren’t enough of those resources to go around. Engagement is the most efficient, most pragmatic, and most quantitatively sound metric that can be used to determine if your content and brand have captured that time and attention.

Bottom line, it can be used to help formulate a marketing or business plan that will divert those resources away from your competition, and towards you.

This is not to say that engagement is the be all, end all for organizational success. My case is that it is the ultimate metric for marketers and communication strategists where they compete for views, attention, and connections in an increasingly crowded and dynamic environment.

Peter Zandan, Ph.D., Hill and Knowton Strategies, Global Vice Chairman – Research,Research and Data Insights, Global Chairman. With assistance on concept research and writing from Ashlyn Gentry, Ph.D., Vice President, Public Affairs, Hill+Knowlton Strategies

Please contact us for more information.

(1) Reichheld, F. (2006). The Ultimate Question: Driving Good Profits and True Growth.

Cambridge: Harvard Business School Press.

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(7) CMO Council. (2014, September). Mastering adaptive customer engagement:

Looking into how today’s marketing leaders are driving business performance across the customer-centric enterprise

[PDF document]. Retrieved from http://www.sap.com/bin/sapcom/en_us/downloadasset.2014-09-sep-17-22.mast…

(8) Haile, T. (2014, March 9). What You Think You Know About the Web Is Wrong.

Retrieved from http://time.com/12933/what-you-think-you-know-about-the-web-is-wrong/

(9) O’Donovan, C. (2014, February 4). You won’t believe Upworthy’s new way of measuring audience engagement until you read it.

Retrieved fromhttp://www.niemanlab.org/2014/02/upworthy-has-a-new-way-of-measuring-eng…

(10) Chartbeat (2013, September 23). Understanding engaged time.

Retrieved from http://support.chartbeat.com/customer/portal/articles/1249311-understand…

(11) Iny, D. (2011). Engagement from Scratch!: How Super-Community Builders Create a Loyal Audience and How You Can Do the Same!

CreateSpace Independent Publishing Platform.

(12) Davenport, T. H., & Harris, J. G. Competing on Analytics: The New Science of Winning. Boston, MA: Harvard Business Review Press.