Building Buyer Personas? Here Are 5 Insightful Reports You Should Pull

Building buyer personas can be tricky -- you need a delicate balance between quantitative and qualitative data to get something that's accurate and useful. You also have to know which information out of all the data in your CRM, marketing automation, and customer support systems will actually be helpful -- and which could steer your marketing astray. 

How can you be sure that you’re focusing on the right data to build out your buyer personas? Here are five reports to pull that will provide guidance for the quantitative part of your research. (And if you'd like help with the qualitative part of the buyer persona creation process, you can check out this blog post.) 

Note: All of the information below can be pulled using the HubSpot and DataHero integration. Click here to learn more about it.

1) Company Information

You can get a lot of information about the companies that you serve simply by analyzing the information you collect through forms on your website, such as the number of people at a company, an individual’s role/level at a company, or the industry they work in. 

Plot this information visually to quickly see which roles are most prominent. You can even filter by company size to get a better idea of specific segments. The chart below, for example, shows that the role that brings in the most revenue is “individual contributor” at companies with 51-100 employees. Knowing this will help you prioritize marketing to certain buyer personas. 

2) Demographic Data

Your marketing software should easily pull in geographic data for visitors, leads, and customers, allowing you to easily visualize demographic data on these individuals. Visualizing customers based on location or other demographic data builds the foundation for other research, including the language they speak or whether your customers live in urban, suburban, or rural areas.

To see this in action, check out the example below. The chart shows us that most customers are located within the US, with some in Canada, South America, Europe, and India. Knowing this information could affect timing of campaigns as well as messaging within your campaigns.

3) Content Consumption

You can also pull in information like the form submission page title and job roles to see who is interacting with which type of content. Then you can build out customer personas based on this information, and determine how to better market to these personas with more specific, relevant content.

In the example below, we can see that individual contributors tend to become prospects through Academy documents, while managers tend to come in through the blog. This helps you to tailor your content to these personas in marketing efforts moving forward.

4) Site Behavior

You can also break personas down by purchase or visit behavior, helping you uncover conversion opportunities by buyer personas.

For example, some personas may visit frequently, but do not convert to paying customers. You could categorize these as "audience personas" -- people who may visit but convert at a much lower rate. Once you identify them, you could either ignore them to focus on personas who actually purchase, or spend time creating different content and promotional campaigns that could improve your conversion rates. 

5) Cohort Behavior

Cohort analysis is another great tool to analyze user behavior. It allows you to bucket users who performed a certain action within a specific period of time. You could find out the answer to questions like, "Do customers who sign up in January tend to engage more with your product than customers who signed up in March?" Segment on something like customer creation date and transaction date to visualize how these cohorts behave over time -- and then fold that information back into your buyer personas research.

Limitations of Data

Data analysis is a great foundation to find out more about your customers. However, nothing beats speaking with them to learn their pain points and how your product fits in. You can use interviews, surveys, or focus groups as a way to confirm or deny hypotheses that are formed through data analysis. Coming with hypotheses before you dive into qualitative analysis allows you to focus your conversations with customers and save everyone a lot of time.

What other data do you use in your customer persona research? Let us know in the comments.