How to Create Personas from Data
Identifying your ideal customer profile(ICP) and buyer personas is the first step in building the foundation for an effective marketing strategy.
Developing these profiles is not solely a marketing responsibility. Mining and interpreting this data should be a group effort with contributions from your company’s leadership, sales, product team, data analysts, and any other team that plays a part in shaping your customers’ experience.
A Step-by-Step Guide
We want to make a clear distinction between ICP and buyer personas here:
Ideal customer profile: Describes firmographic and technographic attributes of the specific companies targeted in an account-based strategy
Buyer personas: Describes the individuals that typically make up the buying committee at target companies for your type of product
For your ICP, you’ll want to know the following about the companies you should target:
Technographic: Relevant tools in their tech stack
And for your buyer persona, the following attributes should act as a baseline for learning about the individual prospects you should target:
Job Titles | Seniority Level | Role in the purchase decision
Working with existing customer data
Common sources for this type of data about existing customers include:
Your existing sales funnel
Your database Sales calls
“Who has actually purchased your product?”
“Which methods of targeting and segmenting have worked in the past?’
Take these answers, turn them into a coherent metric, and use the trends in your data to build out your customer profiles.
Gathering data from scratch
Maybe you’ve yet to build a large enough customer base from which you can pull this data. Your focus should still be on gathering the most reliable information for defining your ideal buyers.
You can use credible third-party data about your industry and solutions like yours as a starting point, then supplement it with primary data about your specific buyers.
There are a few methods for retrieving this primary data when you don’t have a large enough sample size of customer accounts to reference.
Conducting one-on-one or group interviews with customers or your suspected personas
Developing online surveys targeted at possible personas (offering incentives to complete these research surveys works well too)
Using sales development reps for cold outreach to speak directly with leads and validate suspected markets
Requesting feedback from sales teams about conversations they’ve had with prospects and customers
Solicit insight and feedback from the product team about buyers’ needs and common pain points in the market
Notice that there are two main perspectives we’re interested in for this research—your buyers and your internal teams.
Of course, speaking directly with those who are most likely to purchase your product is necessary for understanding your buyers. But you should always seek input from the people who are actually responsible for selling your product too.
Salespeople and SDRs spend their time trying to better understand your buyers in order to sell to them better, so they have a unique big-picture perspective on what an ideal customer looks like.
Here’s an example survey created in Google Forms that we use to poll our sales teams and get an idea of the ideal buyers for our outsourced Customer Service offering.
A Step-by-Step Guide
Qualitative information that is often most useful for B2B tech companies includes:
How they prefer to communicate (over the phone, through email, via live chat, etc.)
How many people at the company are involved in purchase decisions
Which applications make up their current technology stack (you can use tools like BuiltWith to find this information)
Knowing these more personal details about your ideal customers, how they work, and what drives them to purchase is an important piece of the foundation that your entire marketing strategy will be built on.
We wrote at length about the qualitative attributes you should know about your buyers in this blog post about well-defined B2B buyer personas. You’ll need these details when completing the market analysis discussed in the next chapter.