Defining Engagement And The Right Metrics

For advertisers to be successful with online campaigns, it is crucial to have a knowledge of how an audience engages with a Web site. Right now there is much disagreement about what engagement entails and therefore how to measure it. If we consider some of the complexities involved with engagement we can see that a single engagement metric just won't do. There is, for starters, a difference between visitors who come to a site once, never to return again, and visitors who come repeatedly to a site. There is also a difference between visitors who come frequently to the same site and those who typically consume multiple types of content. And those who contribute content or collaborate with other site visitors represent a deeper kind of interaction. And then there are those who influence others to come to the site or become more involved. With a nuanced understanding of these and other flavors of engagement, marketers would be a in a strong position to know how to most effectively advertise to an audience.

But go find a definition of engagement! In my previous article, I touched on this challenge: currently we see the major measurement firms offering up facets of engagement. Nielsen has shifted from page views to duration; comScore looks at visits; and newcomer Quantcast looks at site loyalty. All of these offer glimpses but not a full picture into the dynamics of engagement. Consider the challenges of using duration as a metric when users spend a lot of time but never come back. Or perhaps they come back frequently but, due to poor site organization, do not stay long. And how do we capture the metrics of users who are generating content on the site and influencing others to come to the site and get involved?

I propose that we move toward adopting a theory of engagement that allows us to account for a full range of user interaction, involvement, and connection with a site. We need a definition that does more than isolate an aspect of the total relationship a user has with a site. The more that we can articulate the nature of an audience engagement, the better we can get to actionable intelligence about how to connect and influence that audience.

In offering these ideas about engagement, I would say we already have the outline of a working definition: engagement signifies the nature of the relationship with a site and how that is expressed in the full range of user interaction, involvement and connection. It is a definition that is intentionally comprehensive and embraces complexity, one that will require something more than a single metric to understand. In fact engagement would then require a range of metrics that could give us a 360° view of user interaction that would involve how often users came to a site, content consumption, content generation and sharing business or personal information. This kind of data, properly understood, would naturally lead to the kind of insights that would enable publishers to show advertisers how to successfully connect with their audiences. In fact, that will be the focus of my article next week: using engagement intelligence to drive advertising success.

If engagement by its very nature is complex, does that mean it is too difficult to measure and articulate? Fortunately, we've seen some rather significant work done in this area for the past year. Eric T. Peterson, the author of "Web Analytics Demystified," has been leading the way on his blog, proposing ideas about engagement, testing them with sophisticated measurements, and listening to others, such as analytics expert Avinash Kaushik of Google, who have offered thoughts on Peterson's views.

Picking up on a good deal of media industry blogging on dissatisfaction with the current approaches to engagement, Peterson suggested that we look at engagement as a set of interrelated indices that develop a matrix perspective of how audiences interact with sites. An index, as opposed to a raw metric, enables us to compare sites and show trending information. It is important, Peterson said in a recent conversation, that we "create flexible models that can evolve over time, evolving with our understanding of what engagement signifies" for Web sites in general or for a given category of sites. Thinking about how to comprehensively describe engagement, Peterson identifies a range of factors. For content sites with an outward-bound advertising model (direct ad sales to advertisers and agencies) I see six of these factors that can be immediately applicable:

· Loyalty: how often visitors return to a site over a long period of time.

· Recency: how frequently visitors come to a site within a narrow time period.

· Duration: how long visitors remain on the site.

· Click Depth: the degree to which visitors view site content.

· Interactivity: the kinds of actions visitors take with content (downloading content, viewing videos, attending webinars, posting content, etc.).

· Subscription: the extent to which visitors register for services or content.

Are these the right criteria? I think so, as the categories offer a multifaceted view of engagement that gets at the complexity of visitor involvement with a site. It certainly moves us beyond the oversimplification of engagement as merely one metric, and allows us to capture site dynamics that might be missed otherwise. If visitors consume content quickly or download a white paper, duration as a standalone metric will be a poor indicator, but click depth and interactivity will show significant engagement. Conversely, a visitor to Jakob Nielsen's usability Web site will find relatively long articles that take a long time to read by scrolling down one page. Duration catches what click depth might miss in this case.

Can Web measurement companies offer advertisers and agencies engagement insights based on this model? I believe so. And I am convinced that publishers can use engagement analysis to offer advertisers the pure gold of predictive intelligence --showing the kinds of advertising that will work most effectively to engage site visitors.

Next week: How The New Engagement Metrics Can Impact Advertising Decisions
Next story loading loading..