The term "engagement" is becoming increasingly difficult to define as it often means something entirely different to each individual marketer and digital analyst, within each industry and vertical, and for each digital enterprise and physical business in operation today.
Content publishers in the news business, for example, might determine that page views are their most important engagement metric. Measuring time on site or session depth, on the other hand, may be more appropriate for the consumer engagement campaigns of certain Internet-based electronics retailers, while software-as-a-service providers may only be interested in direct interaction events. Essentially, things are often measured differently based on who we are and the stated objectives and goals of the business.
Today it seems that nearly every metric can be included under the umbrella of consumer engagement and for many that is really where the problem starts as it dilutes a true understanding of performance. Formal endorsements and citations from influencers, on-site activity or interaction events such as video views from unregistered visitors, and conversions such as purchases and sign-ups from current and prospective customers are by far the most common ways to measure something as seemingly abstract as engagement.
The question is, however, is this data enough on its own to provide genuinely valuable insight into whether engagement initiatives are producing actual results? The answer is a resounding "no," unless there is some connection to, and formula for, calculating return on investment (ROI).
While increases in validation (page/profile liking, commenting, bookmarking), referrals and sharing activity (sharing information, creative or transactional messages/data) are certainly useful as they do provide some insight into the behavior of users and the retention efforts of brands, there are others to consider (e.g., time on site, session depth, recency), which are proving increasingly essential when the aim is to assess the success of specific engagement efforts. That can be difficult, of course, as measuring engagement is even less direct today when it comes to individual consumers (particularly in the age of highly refined personalization tactics).
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Developing a formula to measure and predict consumer engagement is no easy task, of course, as it requires factoring in all the nuances of awareness, consideration, purchase (subscription, conversion or even communication) and loyalty phases but those that make the attempt to calculate some form of a customer engagement score are those best positioned for success.
To calculate a customer engagement score, it is best to begin with inputs, such as frequency of usage, depth of usage, specific actions taken, clickstream information, key performance indicators and so on. Combining all these inputs into an actual formula gives publishers a single number representing the sum total of their customers' health, success and, yes, engagement.
Consider the following factors when developing an engagement score for users and the enterprises that serve them:
(SD) Session Depth Input: The percentage of sessions where a visitor clicks beyond more than one website page (which can vary obviously) is very indicative of a high level of engagement.
(VR) Visit Recency Input: A determination of how much of one metric (e.g., page views) occurred in a specified time frame; for example, the percentage of sessions a visitor returns to a website in a set amount of time and views enough pages to be considered engaged. Another (or alternative) way to calculate that might be an available loyalty metric.
(DR) Duration Length Input: The number of sessions that exceed a predetermined amount of time (divided by the total number of sessions).
(IE) Interaction Event Input: The number of sessions where a user completed/interacted with an activity and achieved a specific tracked event.
These are really only a few examples of factors that can be incorporated into a formula for determining (and tracking) consumer engagement. It is important that whatever model is decided upon, however, it meets the needs of the underlying business and that marketers develop scores that are measurable and actionable. Consider dropping the factors that aren't appropriate, and tweak the formula by adding multipliers that will adjust the weight and provide a more accurate understanding of engagement.