Jeff Baker

Everyone LOVES to talk about “buyer personas” these days. Sexy buzzword? Definitely. Valuable exercise? Certainly, but only if you wield these personas correctly.

Why Create Personas, Anyway?

Logic tells us we ought to create personas of our buyers in order to understand who they are, what they care about and how they are motivated. We want to know about their age, job title, favorite snacks, and whether or not they wear socks with sandals. As marketers, we want it all.  

But what happens if you create these awesome buyer personas and these people never actually visit your website?

How the Hell Could That Happen?

It’s possible your site visitors and your buyers are two completely different people.

But before we dig into all that business, we need to get a better understanding of what a “buyer persona” is before we start creating a better light bulb. Hubspot defines a buyer persona as follows:

This is all very logical. The process takes a very scientific approach to marketing rather than operating off hunches.

Through extensive CRM research and 10 years of conversion data, we determined Brafton’s main buyer persona to look something like this:  

Name: Chris Berenson
Age: 49
Title: CMO
Reports to: CEO
Commercial motivations: Driving qualified leads to the sales team. Hitting lead-gen quotas.
Savvy: Relies on his employees to specialize in digital marketing tools and trends. More interested in results than processes.
Content interests: Interested in strategies that produce results. Theoretical pieces do not resonate. To capture his attention, he needs content to reference actual case studies and success stories.

Cool, so we start writing content for Chris now?

Not so fast. Let’s not congratulate ourselves on our awesome new persona just yet, or we may create an entire treasure trove of content for the completely wrong audience. There is no guarantee your buyer personas ever see your content. So we need to crunch the data and determine who is actually consuming your content.

Evaluate Your Age Groups

Now we need to get down with our Google Analytics stalking. We need to learn everything we can possibly glean from GA about the people who are actually visiting our website.

You need to have Demographics enabled and a sufficient amount of data collected to make educated assumptions. Go to Audience → Demographics → Age.

You should see a colorful graph that looks like this:

Pretty. You’re looking at total site traffic segmented by age group. The first thing we want to do is understand which age groups drive the bulk of our traffic.

It’s already not looking good for our buyer persona theory. Eighty-four percent of our traffic comes from visitors between the ages of 18 and 44. Our supposed target audience (45 to 54) only makes up 11 percent of all traffic.

Now that we know which age groups make up the majority of our traffic, we need to understand which ones are contributing the most commercial value.

Macro Conversions

A macro conversion is any goal completion that has direct commercial value. For us, it’s a request to contact a salesperson or for a product demonstration. We want to know the volume and conversion rate at which our different age groups drive these conversions.

Uh oh. Still not looking good for our buyer persona. The data shows over 87 percent of macro conversions are being generated from an audience under 45 years old. The 45-plus crowd may be an accurate representation of our end buyers, but they certainly are not the folks reading or converting on our website.

It’s much more likely the age groups between 25 and 44 are heavy influencers, and introduce Brafton to our 45-plus buyer personas.

By looking at our CRM historical conversion data, we can also infer the majority of our 18 to 24 audience is submitting contact information to request an internship, or are seeking information for a school project. These folks are avid consumers, but do not provide commercial value.

Micro Conversions

A micro conversion is any goal completion that has an indirect impact on commercial interests, but may provide commercial value in the future with substantial nurturing. We will use newsletter subscriptions as our example here. Similar to before, we will take a look at the rate at which each age group subscribes to our newsletter.

Interesting. While the 24 to 44-year-old age groups contribute the most overall subscriptions, it is the older age groups that are most likely to subscribe, converting at nearly double the frequency as their younger counterparts. Note that micro conversion rates increase incrementally as the audience gets older.

Age Demographic Conclusions:

Our most important age group is between the ages of 25 and 44, with emphasis on the 24 and 35 demographic, which drives 40 percent of all macro conversions on the site. Meanwhile, our 45 to 54-plus “buyer persona” only contributes 11 percent of all commercial value.

Our buyer may be a 49-year-old CMO, but that person isn’t reading our blog or converting on our site. Our true champion is the mid-level director-type who brings Brafton to our buyer.

We have a visitor/buyer gap.

Let’s Talk About Gender

If we are going to build personas, we’re going to need to look at GA’s gender classifications. Go to Demographics → Gender. You should see another colorful graph that looks like this:

Let’s take a look at overall traffic by gender.

Slightly more men visit the site than women, however, the two groups have nearly identical engagement metrics. Just as before, we need to know what kind of commercial value each gender brings to our company.

Macro Conversions

We will toggle our conversion drop-down to see if one gender converts more than another:

Now we are starting to see some slightly different behavior; men contribute about 56 percent of all macro conversions compared to women at 44 percent.

Micro Conversions

Now let’s toggle our conversion drop-down to Newsletter Subscriptions to see if there is any variance between the genders.

Whoa. That’s pretty significant. Women are 50 percent more likely to subscribe to our blog than men. It’s curious that women contribute less overall traffic volume, and a lower macro conversion rate, but have a significantly higher newsletter subscription rate than men.

Let’s explore this further. I want to look at the age groups of this female segment.

52 percent of all female newsletter subscriptions come from age groups 35 and older, with the age group 35 to 44 almost twice as likely to convert as the age group 25 to 34. The 35-plus female age group appears to be our avid reader.

Gender Conclusions

At a surface level, men and women appear to behave similarly on our site, with comparable traffic numbers and nearly identical engagement metrics. It’s once you start digging into conversion metrics that behavioral differences start to emerge.

Men are more likely to contribute direct commercial value, generating 56 percent of all macro conversions. Women are more likely to contribute indirect commercial value via newsletter subscriptions.

We have two very unique personas that both contribute value, directly and indirectly. With the behavior data we pulled, we’re now able to make educated assertions about our personas.

Our Commercial Influencer

Our Avid Reader

The Researcher/Intern

Our Buyer

Our Strategy

We are going to narrow our focus to the two main personas that are most likely to consume our content and contribute commercial value: Vince and Christina.


What we can say definitively about Vince is the following:

  • He contributes the most commercial value to Brafton (most macro conversions).
  • Knowing that our end buyers are 45-plus, we can assume Vince is a strong influencer, likely bringing Brafton to his VP/CMO/CEO as a content marketing solution.
  • Vince is less apt to subscribe to our newsletter. It’s likely he gets too much email in his inbox and has a short attention span.

We need to create content that does two things: Captures Vince’s attention in a way that resonates with his professional and personal interests, and is a strong enough piece for Vince to bring to his boss as a proof of our work. The content we create for Vince needs to be able to speak to his bottom line and revenue potential if he is to share it with his boss.

Our content strategy is to create middle-of-funnel content comprised of success stories (both internal and external) that speak to tangible results.


What we can say definitively about Christina is the following:

  • She is less likely to request a demo of our products, but will if our content is compelling enough and she is convinced we are worth the time.
  • She is our most regular blog content consumer by voluntarily opting into our newsletter.
  • Being a more engaged content consumer, we can assume she either has a longer attention span or puts a higher premium on consuming and understanding content marketing trends and best practices.

Christina is a true student of content marketing. She regularly consumes our content, and likely that of our competitors so she can become as savvy as possible in her field. As a self-educator, we will need to produce the most informative, educational content available in the market. We need to differentiate ourselves from our competitors by creating material that utilizes real-world subject matter expertise and examples.


Armed with 10 years of solid CRM data about our end buyers, we were able to create accurate buyer personas. Unfortunately, that’s only half of the story. We uncovered indisputable data in Google Analytics that proved our end buyers are not the same people consuming our content. Were we to rest on our laurels and take our buyer personas for gospel, we would be creating content for merely 11% of our audience!

Our true content consumers are more likely junior influencers that present Brafton to their boss as a recommendation after taking a meeting with one of our business development executives. These influencers are the people we need to be delighting with content on a regular basis.

Our new tactic is to target the needs of these two unique personas and provide them with the richest content experiences available. This is how we turn data into personas, and personas into revenue.