During our previous conversation (granted it’s one-sided), we talked about Persona building for inbound visitors: collecting data on their behavior, matching it against existing segments in your DB, and serving content to the unknown inbound visitor.

What content?

Let’s assume that you have identified your personas, however you see fit to appropriately define them. For the sake of this example, there are 4 different persona groups. Each persona group has its own set of behavior nuances, and their behavior has been defined by their clicks, time spent on digital properties, reactions to content served, etc.

Your content creation process needs to be adjusted accordingly! A generic white paper available to all is no longer applicable or desired by you. Your content is now modified to appeal to the different personas, not only the content itself but the format in which it’s delivered. Persona A receives a white paper specific to the nuances of Persona A, delivered in a format appealing to Persona A. And this could be radically different from Persona B.

Persona A is characterized by behavior, and based on that behavior, receives content that is thought to be appealing. The key is how that behavior is translated into digital responses, because that’s what is used to match against unknown visitors. Content is dynamically served to the inbound visitor that is thought to appeal based on similar known segments.

Here’s the key: a person’s behavior is fluid. It’s constantly changing, and sometimes what you thought was Persona A turns out to be Persona B. And what you thought was appealing to all Persona A’s no longer applies, and needs to be adjusted.

Enter alarms, testing and optimization.

An alarm is setoff when content falls below a preset threshold that indicates something’s amiss: the content that was once appealing to the Persona A group is no longer the case. Got it. Now’s the time to adjust the content, test and optimize so that it returns to delivering value to your audience segment.

The next question: can this be done with tools currently available in the marketplace? More next time…

"With great marketing technology spending comes great ROI responsibility." 

iNeoMarketing 

8/4/2014

Marketing Technology…NOW!

Have a comment? Email it to info@ineomarketing.com or comment below. I’ll publish it here.

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We concluded that it makes far more sense to create/modify personas based on actual behavior than scenario-playing or demographic variables. How exactly should this work?

First, you should think of behavior as breadcrumbs that allow for the definition of your visitor. As breadcrumbs are left, you can discern a click-trails, permitting you to define your visitor based on where they’ve been, and what they will want to view next.

So through data mining and the application of algorithms against that data, a marketer should be able to discover of clusters of individuals with similar click-trails. How many clusters? That depends on the marketer’s tolerance of diversity, i.e., it could be as low as 2 to as high as 16 (Myers Briggs).

Once these clusters are defined, the marketer then overlays these clusters with descriptors, but what descriptors?

The behavior clusters are answers to personality questions that allow the marketer to apply a pre-defined personality definition to the visitor, and based on that personality, serve up content that meets that personality cluster’s desires. Take Myers-Briggs as an example for a framework to use to classify your audience. ENTJ (lower right) is a strategic thinker, a planner and organizer, so ENTJ’s would enjoy blueprints and statistics, and would want to share this information.

What you do defines who you are, and who you are allows marketers to compare you to others and find similarities. And with these similarities come clusters, and these clusters receive content specific to them.

But how do you know it’s the right content? More on this tomorrow…

"With great marketing technology spending comes great ROI responsibility." 

iNeoMarketing 

8/4/2014

Marketing Technology…NOW!

Have a comment? Email it to info@ineomarketing.com or comment below. I’ll publish it here.

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 Using personas for your outbound efforts are straightforward: each record in your DB is parsed and categorized as a member of one of your established personas based on the criteria that you’ve established, i.e., whatever known variables in the record are indicators as to which persona that record belongs.

It’s a stake in the ground, but is it correct? CMO Bill may have the attached persona CMO X, but CMO Bill is really more like CIO Mary.

Now add to this the great uncertainty associated with your inbound effort where you don’t know who’s who until information is volunteered. You’ve got visitors in and through your digital properties, but until they self-identify, e.g., via a registration form, you’ve no clue as to what resonates.

You’ve got a vast degree of uncertainty associated with your database, both identified records as well as mysterious IP addresses. What good are personas if you can’t apply them accurately to your database so that the appropriate messaging and content is forwarded?

Personas need to be applied via past behavior, not static demographic variables. A person who views page X, Y, Z and downloads A and B has provided enough information to correlate with others who have done the same, and they can be classified as Persona 1 even though their titles, responsibilities, etc. are dramatically different.

Think of it this way: the Myers-Briggs personality ENTJ could apply to the CEO or the VP Engineering, so why would you send different messaging based on their title?

How can we solve this? More tomorrow…

"With great marketing technology spending comes great ROI responsibility." 

iNeoMarketing 

8/4/2014

Marketing Technology…NOW!

Have a comment? Email it to info@ineomarketing.com or comment below. I’ll publish it here.

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