Understanding who your customers are will allow you to make sound, data-driven decisions in connecting, reaching out, and selling to them. Creating buyer personas is an important starting point for all marketing efforts because it will allow you to customize your marketing strategies for each potential customer segment.
In the past, I have created personas from data extracted from Google Analytics data (It can be done much more easily when you have a brand that generates significant traffic that already accomplishes Analytics “Goals” that you have set up already). If you don’t have this data, you can create a survey and ask your customers to complete it (you can offer an incentive to do so). Here is a sample template from HubSpot to help you create questions that will get you valuable information for your buyer personas.
Below is a very simple example (A real persona would be more in depth, but this will give you a good summary) that I created for a presentation at University of Miami some years ago:
The first step is to create your goals in Google Analytics. A simple goal to set up is a destination page goal. This means, the only way a perspective lead can get to that destination goal page is through your lead form. With this logic in mind, you know 100% that a lead form submission was triggered when this goal fires on Google Analytics.
The second step is to collect lead information. Using basic Statistics rules, we can find out our sample size needed with a 5% margin of error via a Sample Size Calculator. Without getting to crazy into mathematics, I waited until I had over 400 leads collected. (About half of the leads had blocked Google’s cookies, so I ended up with 201 leads. It’s not ideal, but for time constraints I had to run with it). Below is a sample lead form from University of Miami.
In the third step, you’ll need to organize the data you have been collecting via a custom report. It took about 1 month for me to collect the lead data I needed. When you create a custom report, make sure that you select the “flat table” option. You can add a number of different dimensions to filter data that you’d like to include when creating buyer personas. I kept it simple and chose gender, age, device type, and browser type. Once you have your custom report, you can export this data to Excel.
Step four in the process is to take the data you’ve exported from Google Analytics and organize it with a Pivot Table. There are a lot of cool things you can do with your data, but I chose to keep it simple so that all my data could be easily interpreted:
Here is another view to help visualize the data:
Step five is creating buyer personas. Your buyer personas can be as simple or as complex as you’d like. The more data that you have, the better to help you define who you should be targeting. Based on the analysis, I created my fictitious buyer persona, “Jennifer Law”. Jennifer is 31 years old, she primarily uses her mobile phone to browse the web, and she uses both Android and Apple phones.
As you can see, I have pulled out key information for this specific product. I would advise you to play around with your Analytics account and see all the possible data that you can pull out to better define your buyer personas. Please let me know your thoughts!
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