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How to Create Data-driven Personas

Customer personas are useful to make decisions that will impact the way businesses reach out to customers. In this article, we help you create a data-driven persona efficiently in a step-by-step format.
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    Understanding your users can mean everything to your business. If there is no proper explanation about who your customers usually are, why they prefer your solution, the steps they had to take to become your customer, etc., you will never be able to target the right people. If your targeting is off the charts, no matter how fancy your product is or how clever your marketing tactics are, it will not make a dent in your customer’s psyche. We have written about finding customer persona and competitor analysis to find out more about your customer.

    Customer persona is arrived at based on a variety of factors including behavior, motivation, demographic factors, firmographic factors, objective of the customer, and so on. Personas are useful to make decisions that will impact the way businesses reach out to customers, create content and position themselves. Data-driven personas are a more efficient method because it allows you to draw more meaningful conclusions based on thousands of data points.

    What is a data-driven persona?

    There are ample sets of data available already which you can use to strategize your marketing. Data-driven personas use your readily available data to understand your target audiences deeply. It uses data collected from traditional personas as well when including its own sources.

    Data from data-driven personas come from sources like web analytics, digital surveys, digital panels, social media insights, social listening tools, etc. The above sources help us to arrive at personas even faster than normal. Since most of the data can be collected real-time, the personas keep changing too.

    It helps us know about the devices that are being used at each stage of the customer journey, channels where the personas are posting content, what they are talking, the research they do to buy products, their attitudes and how it affects their buying behavior.

    What’s wrong with traditional personas?

    Even though it is effective, traditional personas do have a few flaws. By building data-driven personas on top of the inputs from the traditional persona, we will be able to develop a much more nuanced persona of your ideal customers.

    Customer bias:

    Understanding the true feelings of your customers can be a great help when developing personas. But when most of your research is based on what your customers think, then it is bound to be based on their bias.

    For example, users might have reached out to you based on the different types of content you have published that they consumed over the years, but they might tell you that they searched for your solution on Google and then reached out to you. So, businesses are prone to discounting the effort that content had on these users.

    Not actionable:

    The information that businesses collect to understand their customers and arrive at a bunch of personas needs to be used for it to be effective. Traditional personas, by itself, are not actionable, which is where data-driven ones make all the difference.

    Aspirational data:

    Some of the information that you get from traditional personas might be aspirational where the real needs of the customers might not be reflected. It is the discretion of the business on how to use it. Thankfully, by adding additional data on top of it, you can get closer your ideal customers.

    How to create your data-driven persona

    In this section, we are going to help you build a data-driven persona in a step-by-step format.

    Steps to create your data-driven persona

    #1 Write your objectives

    You need to know the objective behind spending so much effort and time to find your personas. There are a number of reasons why personas are important, you need to be clear about why exactly is your company doing this. Some of your objectives could be the following:

    • Finding new types of clients
    • Knowing what kind of content your customers consume
    • To understand about their journey with you
    • To find out the best channels to reach the customer
    • Understand more about the interests and motivations of your customer
    • Providing them a better customer experience

    It is perfectly all right to have more than one goal, but ensure that you don’t go overboard with it. The goals should not be exclusive of one another, but have to complement each other.

    #2 Gather customer data

    Understanding your target audience requires you to find out what they do, who they are, their motivations, behaviors, and more. The more sources you have, the more refined would be the information that you will get. It is advisable to use both qualitative and quantitative data of your customers. Below are some of the sources that you can use to collect data about your customers.

    Website analytics:

    The analytics on your website, which is either available on Google Analytics or any of the other tools that you are using is a great source of information to understand the behavioral pattern of your website visitors. Simple factors like how long they stay on the website, the blogs that they read, and the product pages that they frequent, and more will tell you a lot about your target audience.

    Your company’s CRM:

    The CRM you use is another treasure trove of data that will tell you a lot of in-depth information about your present customers. What is the plan that they are using, what is their designation in the company, how much do they spend annually, how long have they been customers with us, etc.

    Market research:

    Find out where your customers lurk. Check out the applications and products that they use. How do they find the products that they buy. What are their sources of information? Are they active on any forums or communities? If yes, then spend a lot of time on these places too as you could get their true thoughts which they share with other customers like themselves.

    Statistical analysis:

    Statista is a popular source to get statistics on a variety of things. Google Public data, Knoema, Numberof.net, Gapminder, USA.gov reference center, Gallup, Data Market, Find The Best, are some of the other sources that are highly reliable.

    Learn from your previous marketing campaigns:

    The results from your previous marketing campaigns is a great source to learn from. It will help you identify the mistakes that you made, but it will also assist you with understanding what worked and how customers reacted to a certain copy or a landing page.

    Find the ads that resonated the most with your customers while focusing on the leads that eventually converted based on these ads. Ask your sales team the tactics that they used to convert them, the objections that they handled and the benefits that they promised. When someone clicks on your ad, it means that your copy resonated with what they wanted, studying their behavior and persona will help you narrow down your ideal persona.

    Conducting surveys:

    Getting answers directly from your customers is one of the most powerful ways you can understand them. Thankfully, there are tools available which can be used to make it happen thus reducing the effort required for it. Ask questions to your customers and target audience to understand more about why they are looking for a solution like yours and other questions that are relevant to understand them deeply.

    Interview salespeople in your company:

    Your salespeople are the ones who talk to your customers directly. They face a barrage of questions from them and are better suited to answer all your queries because they have a first-hand account of your customer’s needs. Understand what are the questions that customers usually ask during a sales call, why are they interested in our service, and why did they choose our service over a competitor’s.

    Focus groups:

    Talking to people who are a part of your target market can be great for refining your personas. Focus Groups helps you have a conversation with a bunch of people in your target group in person. There will be discussion about your product, you can ask them about their life, their work, even show them demos if possible. Ask them if they feel any discomfort in working with your product or if they have any preconceived notions because of which they never made the purchase. All the inputs that you get from here can be part of the data.

    #3 Create your hypothesis:

    Based on the data that you have gathered, you should be able to come up with hypotheses. Analyze the data for patterns and see if there are any glaring similarities or dissimilarities. Does it ring a bell? Can it be used to identify users? Using all of this, create your own hypothesis.

    The hypotheses that you make can even contradict each other as the customer's interests are varied. They might even be from different segments which is why there is contradiction in their behavior and motivations, according to your hypotheses. Since your hypothesis is based on observation, you need to vet it by testing it.

    #4 Test your hypotheses:

    Now that we have collected data from thousands of potential leads and customers and created a hypothesis based on them, here is the next step. You need to test the hypotheses to ascertain that your findings make sense in the real world. Have a large pool of people who are ready to be a part of the study.

    Get in touch with people who might be interested in being a part of the study and test your hypotheses by talking to potential customers. Ask them questions which require a detailed answer, write down the findings and segment them.

    #5 Formulate data-driven personas:

    It is pivotal that you include everyone in your team to be a part of the persona creation process. Why? Because the inputs from everyone will have different perspectives and it will come out more refined than what is usually expected of it. The more the number of people involved in the process, higher are the chances of it coming out well-drafted.

    Present the results of the data collection, let everyone know about the hypotheses you created based on the data and the results when you tested the same. Based on this, decide together which are the personas that you are planning to create.

    Benefits of data-driven personas
    benefits of data-driven personas

    Online analytics tools give you data, but it doesn’t provide any meaning in itself. Using numbers to make your team understand about your customers will not work. It is not humanly possible to remember huge sets of data too. Personas using this data which has more relatable attributes are easy to recall. Here are some of the benefits of data-driven personas.

    Updated data:

    Traditional persona involves a lot of data collection over a long period, but the reality is that customer behavior keeps changing based on various factors. With data-driven personas, you will be able to create personas based on real-time data. It collects data from Facebook, YouTube, online forums, etc., all of which are updated on a real-time basis.

    At given time intervals, you can generate data-driven personas which are always updated because data collection happens on auto-pilot and the personas are re-calculated. It leverages data from millions of interactions while combining it with other relevant data.

    Can be generated quickly:

    Did you know that creating a manually-done persona can take up months of your time starting from data collection to analysis? Creating a data-driven persona takes anywhere from a few minutes to a matter of days based on the infrastructure that is already available for it.


    Since there is a lot of manual labor involved in creating a traditional buyer persona, it can get ridiculously expensive. Especially since it involves months of effort. Data-driven personas are relatively cheaper to produce as there is a huge degree of automation involved in the entire process. Data-driven personas use digital data that can be easily collected to create personas.

    Provides full-stack access:

    Data-driven full-stack solutions generate personas automatically based on the various types of data that are available while providing access to the data too.

    Data protection:

    Using aggregated data from a myriad of sources would never involve details that can be personally identifiable. The data that is provided by online platforms like YouTube, Facebook, Instagram, are usually at a group level and it never displays information that can be used to identify anyone.

    Behaviorally accurate information:

    Data-driven persona uses algorithms to create finer segments of customers and uses real-time data to generate characteristics for the description of your personas. It also infers patterns from customer’s interaction with online content and websites that possess such information. Data-driven personas are considered more accurate because they are based on actual data which come from highly segmented audience.

    Representative of a large audience:

    The chances of misrepresentation is high in traditional persona generation methods because the sample size is usually small. If the sample size runs into millions of data, do you think it is possible to use traditional data collection methods? Data-driven methods represent the entire set of data because it can analyze huge volumes of data.


    To create marketing campaigns or build a product without the help of personas are a tall ask. Who do you target when you don’t know who is your ideal customer? This is where personas can change the way you write ad copy, create marketing campaigns, and target potential buyers.

    By making data-driven personas available to customers, Delve AI reduces the burden on small and mid-market businesses, start-ups, and not-for-profit organizations, which would otherwise have to shell out thousands of dollars for manually-made buyer personas. Data-driven personas from web analytics data are auto-generated, usually within minutes, and kept up to date. You can use them to gain clarity on your most valuable segments and to refine customer experiences to grow your business.

    Frequently Asked Questions (FAQs)

    What is a data-driven persona?

    A data-driven persona is a detailed representation of your target audience, built using real-time data from sources like web analytics, surveys, and social media insights. They are constantly updated and help you understand consumer behavior, attitudes, trends, and preferences.

    How to collect data for persona research?

    Usually, there are two types of data sources you can use for persona development: qualitative data and quantitative data. Qualitative data encompasses surveys, interviews, questionnaires, focus groups, customer reviews, and feedback, while quantitative data includes website analytics, social media, and CRM.

    How do you create personas with data?

    You can easily create data-driven personas, or DDPs, by following these five steps:

    Step 1. List your company goals and marketing objectives

    Step 2. Gather customer data from web analytics, surveys, focus groups, CRM, market research, and statistical analysis

    Step 3. Analyze similarities and differences in data

    Step 4. Reaffirm your findings by interviewing customers

    Step 5. Create data-driven personas

    Create personas automatically from your Google Analytics data
    Gain a deeper understanding of your digital customers

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