Brain Vibe

What is it that we really want to know when we are measuring social media engagement?  It can be an indicator of advocacy, brand affinity, purchase consideration, or actual sales.  In many cases, engagement is considered the outcome showing the value of brand.  The problem that arises in this is that all to often how it is measured has nothing to do with how the value of the brand translates into customer value or initial purchase.

The first problem is that measuring engagement often has more to do with the amount of time spent on site and the amount of view, clicks, and level of content reached.  On the surface, this is a great first step.  When looking closely, flaws abound.  The reason, what is the online experience trying to achieve?  If the purpose is a landing area that drives purchase conversions, then more time on the site and an increase in pathing may actually be an indication of less qualified visitation. If the purpose is education and a first step into creating a customer relationship, then more time on the site, activity, and depth of knowledge seeking can be a good thing,  However, to be realistic, have you looked at your SEO and SEM statistics lately?  My guess is that around 70% of those visiting your site are direct visitors or searching on branded keywords.  That being the case, visitors already know a good deal about you prior to coming to your site and the more time and research they do might also not be a good thing if they are comparison shopping.

Sounds a bit dire, right?

To counter this, web analysts are starting to take a look at measuring actions as they relate to conversion.  Simply spending time on the site, views, or measuring clicks isn’t considered viable and predictive.  However, if desired actions are achieved such as downloading high value content, sharing content, participating in discussions, or taking actions that are highly linked and indicative of purchase behavior, then tracking at this level is more valuable.  Actions can be more connected and aligned to desired results and predict conversion.  Right?  Maybe.  The issue arises of clearly understanding actions that predict conversion to sales or customer value.  The other issue is that measuring the number of actions also isn’t that far off from measuring page views, clicks, and time spent.  It might be more meaningful in that it is a validated initiative, but again, is more actions a good thing?  Once again, as with traditional metrics, at the end of the day, what is your site or landing area intended to do?

Measuring engagement should actually take into account both methods for a hybrid approach.  How this hybrid is determined once again depends on what your desired outcome for the website or online experience should be.  At the simplest level, starting with actions taken and tracked as the foundation of a predictive model is a more sound approach.  These are steps in a desired process for conversion, regardless of what your conversion intent is, that are reliable and accurately measured.  However, actions are part of a process and thus need to be ordered and weighted accordingly.  Processes are relatively linear in fashion and assigning a weight based on the step in the path is important.  It can be a simple distribution or multiplicative, but a step does have relevance and weight.  In a hybrid approach, we also want to introduce the traditional aspects of views, time spent, and clicks.  Starting with views and time spent, leveraging these as coefficients in the model will provide a better perspective on weight on desired actions and ultimately the desired outcome.  Essentially, views act as impressions that influence behavior and time spent introduces the amount of exposure necessary to trigger a desired result.  Taking from online display advertising effectiveness, banner ads as an influencing factor for awareness and conversion increases with exposure even if no action is taken to click through.

That leaves clicks.  This traditional metric introduces a duplicity element that needs reconciliation.  It is important to carefully introduce this measure into the model as it can inflate engagement metrics and thus over forecast results.  Clicks also can be an issue as it is typically a component of measuring effectiveness of ad spend.  What needs to be determined is if the click is associated to intended actions taken on site and avoid double counting or inaccurately measuring ROAS.

Ultimately, engagement is an indicator of a desired outcome and not the outcome.  Combining traditional site tracking methods to weight and adjust models predicated on process actions will create a more accurate predictor of outcomes.