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The History of Buyer Personas

A look at the origin of buyer personas and its history till date. Covers user/marketing personas, Jobs To Be Done theory, qualitative/quantitative personas, data-driven personas and automatic persona generation.
16 Min Read

Table Of Contents

    Buyer personas are now extensively used in marketing. But did you know that the first user persona was created by a software designer? Or that it was called Kathy? Take a look at the history and development of buyer personas in the following article.

    The marketplace is made up of two types of people: the ones who sell and the ones who buy. There are also the ones who promote or market the products/service. Of course, everything is null if you don't have a product.

    That said, the marketplace and its buyers are much more different now than they were in the past.

    Imagine if your company wanted to sell a new lawn mower in the 1990s. As an employee, you would use newspapers, direct mails, fax ads, Yellow pages, TV ads, or billboards to advertise your product. Once the buyers came to know about the new lawn mower, they would directly contact your salespeople. And then, they would hopefully buy your product.

    Although marketing was by no means easy in the 1990s, it was relatively straightforward. You didn't have to keep track of your customers' preferences and buyer journeys across multiple platforms and devices. In recent years, people have evolved many tools to make this process easier. One of those effective marketing tools is the buyer persona.

    A buyer persona is a fictional prototype that represents your actual buyers. It not only helps you understand them but can also predict their future behavior.

    But how were buyer personas initially created? What were some of the methods used to create them? Continue reading this article to get a thorough understanding of the history and development of buyer personas through the ages.

    The evolution of buyer personas

    You must have had a sip of Coke at least once in your lives. If you're a fan, you should have also heard of the marketing blunder Coca Cola made in 1985.

    As the story goes, the Coca Cola Company changed the recipe for Coke to compete with Pepsi in the summer of 1985. You'd think it would work (it almost did), but it didn't. The New Coke was a colossal failure with the masses, taken off the shelves just 79 days after it was introduced.

    So... why did it happen?

    Well, it's not because the company didn't do any market research. In fact, Coca Cola conducted a series of blind taste tests which proved that the new formula was better than the old one. According to Wikipedia, more than 90% of the taste testers said that they would buy the product. Other stats, surveys, and reports were also in their favor.

    The only thing that wasn't, were 10% of the taste testers who absolutely hated the new flavor.

    By ignoring this customer segment, Coca Cola also ignored the love and attachment people had with its original product. Although the company eventually turned this blunder around, the incident will still be remembered as one of the worst product strategies to ever be implemented.

    That said, the New Coke teaches you a lot about the importance of listening to your buyers.

    Earlier, the easiest way to do this was by using demographic and psychographic data. Demographics included the buyer's age, gender, ethnicity, income, marital status, and education. On the other hand, psychographics focused on the buyer's life experiences, motivations, values, opinions, preferences, and lifestyle.

    The former tells you who your buyer is while the latter tells you why your buyer is what he is.

    This data was mostly collected through surveys, interviews, focus groups, sales records, or existing buyer details. Both the methods helped companies know their buyers to some extent. You could easily learn a lot about the different types of customers that endorsed your products.

    However, at the end of the day, this was just numerical and textual data with no character whatsoever.

    Dimensions were added to customer data with the invention of buyer personas in the 1980s. Although you'd generally expect marketers to "invent" them, personas were initially created by a software designer named Alan Cooper.

    Evolution of buyer personas

    1985: Alan Cooper creates the first persona

    Alan Cooper created the first persona named Kathy in 1985. While writing a new project management software program, he recognized the need to understand his users in order to make his designs more user friendly. As a step in this direction, Cooper interviewed a number of users (mostly colleagues) who were likely to use his software.

    Kathy was the result of all his user interviews.

    Named after one of the interviewees, she was a composite that represented a fictional software user. Kathy helped Cooper decide which functions and behaviors of his program were necessary and would appeal to the users. Furthermore, he could also think about the expectations and problems that they might have with the design.

    The software program, called Plan*It, was a critical and commercial triumph. Over the next few years Cooper built two more programs of a similar nature. One of them was a visual programming language code that became the core of Visual Basic, first introduced in 1991.

    Goal-directed Cooper personas

    Now a consultant to software companies, Cooper developed three new personas for Sagent Technologies in 1995. Pioneers in the field of "Business Intelligence" software, the company wanted him to help them design the interface for their new product.

    After a thorough interview with their users, Cooper created Chuck, Cynthia, and Rob. He called them the first goal-directed Cooper personas. Each of these personas were grouped on the basis of their goals, tasks, and skill levels.

    Needless to say, the personas dramatically increased the quality and usability of the product after being included in the design process. Cooper's personas were so successful that the company used them to define a new product segment.

    Personas in The Inmates are Running the Asylum

    Cooper published The Inmates Are Running the Asylum in 1998. The book was originally "intended to alert managers of the problems inherent in designing software for use by non-engineers." To do this, he offers entertaining personal experiences in the corporate world to show how talented people constantly design bad software.

    It was in the pages of this book that Cooper makes the distinction between "user personas" and "buyer personas" and first introduced the term "buyer personas". He defines personas in the following manner:

    "Personas are not real people, but they represent them through the design process. They are hypothetical archetypes of actual users. Although they are imaginary, they are defined with significant rigor and precision."

    Creating personas allows one to identify with the user's goals, pain points, and focus on the program's essential features. Cooper states that developers should base their designs on specific user personas. By doing this, they will be able to design software that will be easy to use and adapt to the needs of its users.

    Cooper's principles on personas and product design have been widely discussed and accepted. User personas have become a tool that gives developers the ability to peer into the minds of their users. Using the resultant insights, they can design software that can be easily used by the average buyer.

    1994: Jenkinson develops Customer Prints

    Alan Cooper developed personas that could be used in software designing. However, marketers were already using similar models to define demographic segments in the past. These segments were usually formed to respond to people with similar tastes and provide a product with which they could easily relate.

    Angus Jenkinson is credited with the development of personas in the field of marketing. A former professor of integrated marketing, he developed the concept of understanding customer segments as communities with a coherent identity in 1994.

    Furthermore, Jenkinson stressed on the need for marketing to move beyond segmentation and group buyers with similar attitudes together. Although segments and groups have a lot of similarities, they essentially perform different functions. While segments divide people on the basis of age, gender, and other factors, groups bring people with similar behaviors together. This grouping gives marketers a more personal understanding of their buyers.

    Jenkinson's concepts were adopted by OgilvyOne to form fictional profiles called Customer Prints that described buyers in their real environment. Marketed as "day-in-the-life archetype descriptions," these personas revealed more than just the buyers' age, gender, and routine. They explored the buyers' goals, attitudes, values, frustrations, and motivations, which makes them what they are.

    2003: Clayton Christensen's Jobs to Be Done Theory

    Prior research solely focused on knowing the products and its buyers. You'd usually take customer data, segment it, and create buyer personas. Using these buyer personas, you would study buyers' goals, motivation, behaviors, and thus form a marketing/product strategy.

    This process should ideally make it easier to innovate new products that customers will buy. Sadly, despite having more customer data than they know what to do with, companies struggle to create products that will woo its buyers. This is mainly because they do not know which data to look at.

    In 1991, Tony Ulwick proposed a solution to this problem. He stated that companies should start focusing on the "job" buyers are trying to do when they start using a product. Clayton Christensen used this idea to form the "jobs to be done" (JTBD) theory in his book, The Innovator's Solution in 2003.

    "When people find themselves needing to get a job done, they essentially hire products to do that job for them. The marketer's task is therefore to understand what jobs periodically arise in customers' lives for which they might hire products the company could make," says Christensen.

    You essentially need to know the answer to one simple question: What is a person hiring your product to do? What is the job that your product should perform?

    For example, a person uses or "hires" PayPal to make secure and easy payments online. What is the job that PayPal performs? It provides customers with secure payment options that saves them the hassle of visiting the bank.

    Most companies fail because they do not ask these questions. Instead of focusing on customer attributes and buying behaviors, they should study what job the buyer is trying to get done. If companies understand this, they will be able to create products that help customers get the job done better.

    2006: Qualitative and quantitative personas

    In 2006, Steve Mulder and Zeve Yaar outlined three new approaches for persona creation. They specified the creation process of qualitative personas, qualitative personas with quantitative validation, and quantitative personas.

    Qualitative and Quantitative personas

    Qualitative Personas

    Often referred to as the "traditional approach", this process of creating qualitative personas includes user interviews, field studies (observing users in their original environment), and usability testing.

    The data obtained is used to segment users into different groups based on the common points found across each group member. Some similarities included are the users' goals, motivations, and attitudes. Later, each segment is used to create a persona.

    A segment turns into a persona when "you add more detail to their goals, behaviors, and attitudes." By enriching personas with names, photos, and other demographic details, it becomes easier to envision them as real people rather than 2D characters.

    Qualitative personas can increase your understanding of buyers and their buying decisions. As they are based on interviews with a few customers, they often do not require much effort, time or money. However, qualitative persona creation is problematic since it does not use quantitative data. This makes it harder to prove their credibility at scale and accuracy (rightly so) against stakeholders who need quantitative evidence.

    Further, segmentation using qualitative means is great as long as you don't involve your biases and preconceptions in the research process. You might be knowledgeable about your business and its buyers. Nonetheless, with qualitative personas, you must let your assumptions take a back seat and focus solely on your buyers.

    Qualitative Personas with Quantitative Validation

    This is another approach to persona creation for companies that can spend some more time and money on the process. The personas are created in the same way as qualitative personas but the segments formed are verified using quantitative research.

    The validation is done using customer survey data, statistical analysis, or any other kind of quantitative method. The main aim here is to verify your segments using a large sample of data. This gives you the quantitative evidence required to successfully present your personas in front of various stakeholders. Once you have the quantitative research ready, you can proceed with persona creation.

    Personas created in such a manner have all the advantages associated with qualitative personas. Furthermore, they are more realistic as they are backed up by statistical data. The chances of making an error are still there, however, they are less than the former.

    Despite their advantages, qualitative personas with quantitative validation do have their drawbacks. The additional step of data verification will increase the time taken for persona creation. Additionally, you require additional skills for data analysis. Existing biases can still influence personas in the initial steps which could prove detrimental to the overall project.

    The biggest problem, however, is when the data does not support your segmentation theory. If this happens, you will have to restart the entire exercise which will lead to additional expenses. So the best thing to do here would be to ask the right questions at the right time.

    Quantitative Personas

    To create quantitative personas, you begin with the qualitative analysis of your buyers. The behaviors discovered are then used to form a hypothesis about segmentation options rather than reach a final segmentation model. Data is collected on the available options and put through quantitative research.

    The main aim of this research is to find the model which will be most suitable for persona creation. Using statistical cluster analysis to segment users based on a set of variables, you will end up with a number of clusters or segments. Your final step would be to personify the desired segments obtained by repeating the same steps as before.

    Personas thus generated are much more believable since they are created using quantitative as well as qualitative approaches. The possibility of human influence is greatly minimized, thus making personas much more accurate and objective. You can also discover and examine additional behavioral patterns and differences that wouldn't have been possible manually.

    Quantitative persona creation is tough work. You require a lot of time as well as advanced data skill sets to generate results. The personas may sometimes present information contrary to your expectations and can be difficult to interpret. Nevertheless, they can give you better insights about users and their motivators.

    Criticism against buyer personas

    Buyer personas definitely have their advantages when it comes to giving you a firm understanding of your buyers. However, they also have certain problems associated with them.

    Personas are expensive

    Creating quality personas manually takes a lot of time and effort. If you want them to be accurate and precise, an in-depth research and investigation of your user base is required. This makes persona projects really expensive, resulting in the expenditure of thousands of dollars. The high cost factor makes it difficult for start-ups and small businesses to create personas.

    Personas do not represent reality

    Concerns have been raised over the validity of personas as well. Since they are often based on qualitative interviews that may not really represent the whole user base, the resulting personas may include certain biases. These biases may be at the individual, organizational, or user level. Similarly, personas can be influenced unconsciously by their creators, rendering the entire process meaningless.

    For example, buyer personas can cause gender and racial stereotypes since they include only a specific sample/segment of users. This can cause unnecessary biases and distract companies from focusing on actual buyer behaviors.

    Personas lack credibility

    Personas lack the assurance usually associated with numbers since they are typically not based on statistics. Hence, they are thought to be subjective and interpretative rather than objective and believable. Sometimes, buyer personas may come into conflict with the impressions that decision makers have about their users. This conflict can further lead to an unwillingness to adopt personas.

    Personas are inconsistent

    Another argument against the use of personas is that they are inconsistent. Since they are created by combining information from various sources, it is hard to validate their accuracy.

    Change in buyer behavior (online purchase behavior, search behavior, online content consumption), often rapidly, is a feature of online businesses. As data collection is expensive, personas are not updated to reflect these behavioral changes. This expiration date on buyer personas is another factor why businesses shy away from using them.

    Personas are created but not used

    One of the most pressing concerns about buyer personas is that they are largely theoretical and not used in real situations. There are cases when a considerable amount of time is used to develop personas that were never really used or implemented. Even if they are used, they seem to have had little to no impact on the actual work.

    These concerns arising from the use of personas have led many to move on to data-driven personas.

    2008: The rise of Data-driven Personas

    Data-driven personas have developed in response to the rise of social media, online data, and user analytics platforms. Buyer personas are now being defined using algorithmic methods that produce accurate and up-to-date personas using statistical data. They not only help bring productivity in your work but also facilitate the segmentation of a diverse number of buyers.

    In 2006, K.L. Williams first introduced the term "data-driven personas." His concept was further developed and popularized by Jennifer McGinn and Nalini Kotmaraju in “Data-Driven Persona Development” in 2008. These researchers created data-driven personas for a training organization using factor analysis, surveys, and statistics. In doing so, they discovered that the personas generated were much more accurate and readily accepted by various stakeholders.

    According to Jansen et al, the following factors have contributed to the rise of data-driven personas:

    Rise of data driven personas
    • Data access: Large quantities of data is readily available through social media services, APIs, and online analytics platforms. This makes it easier for companies to analyze customer behavior and preferences in order to create data-driven personas.
    • Data science: The advancement in the field of analytics, programming, and artificial intelligence has made it easier to gather and process data.
    • Data expectations: More and more companies are using customer data to make informed decisions about their customers.
    • Online technologies: Many online technologies are offering ways to create dynamic and life-like personas using pictures, voice-overs, and simulations.

    These causes have contributed to the development and rapid adoption of data-driven personas over the past few years. You can now create data-driven personas using persona generator tools that derive data from analytics tools like Google Analytics and social media platforms (YouTube, Twitter, Instagram, or Facebook).

    2016-17: Automatic Persona Generation

    Jung et al introduced the concept of using social media data for automatic persona generation in 2017. Theirs was the first system to analyze real customer data to automate the process of persona generation. This data was collected in aggregate forms from major social media networks and grouped according to user attributes. Once the segments were formed, they were enriched with other details to form personas.

    Automatic Persona Generation is a method wherein personas are created using online user data for solutions distributed via online platforms. The data is collected in aggregate forms and thus maintains customers' privacy. Using online analytics, the system combines both behavioral and demographic segments to create personas representing real groups of people.

    Often, such systems also provide an interface wherein you can interact with your personas. This makes it easier to learn about why, when, and how buyers interact with your products/services.

    Traditional vs Data-driven Personas

    Data-driven personas obviously have some advantages over traditional personas. That said, traditional personas are still a viable option for implementing strategies that require a thorough understanding of its buyers.

    Take a look at some of the advantages data-driven personas have over traditional personas.

    • Data-driven persona creation is much faster and cheaper than the creation of personas using manual and high-quality ethnographic techniques.
    • As opposed to traditional personas, data-driven personas analyze the whole user base to produce qualitatively rich and statistically accurate personas.
    • Personas created using online analytics are less likely to be personally biased as they are based on online statistical data.
    • As compared to traditional personas, data-driven personas are statistically representative and legitimate.
    • Data-driven personas are responsive to changes in the underlying customer behavior and can be frequently updated to reflect these changes.
    • As compared to traditional personas, data-driven personas can better handle the increasing complexity of user bases. For example, they can be used to identify hundreds of unique behavioral patterns in a large audience.
    • Data-driven personas can be used to predict future user behavior more accurately.

    It is evident that data-driven personas can solve many of the problems associated with traditional personas. This method presents online statistical data in a humanized form, thus generating empathy towards the buyers.

    The 5 Rings of Buying Insights

    One of the most important objectives of persona creation is buying insights. These insights are important if you want to discover your buyers' perspectives and gain clarity over their buying decisions. Adelle Revella has formulated the 5 rings of buyer insights that represent the different stages of the buyer journey.

    Five rings of buying insights
    • Priority initiative explains why your buyer has decided to purchase a product/service similar to the ones you sell. This insight helps you locate the personal and political reasons that prompt buyers to invest in the solution you provide. Hence, you can create and execute marketing strategies at a time when buyers are most likely to listen to you.
    • Success factors describe the results that buyers expect after buying your solution. These are mostly personal or organizational benefits that they desire your product/service to provide.
    • Perceived barriers are any misconceptions, doubts, or misgivings that buyers might have about your products/services. Once you know which factors create these negative opinions, you will know what to do in order to reassure them.
    • Buyer's journey explains the "work" that buyers do in order to search, select, buy, and recommend your product/service. You will know which factors influenced their decision at each stage of the buying process. Thus, you can easily align your marketing strategies to target buyers at the most influential stages of their buying journeys.
    • Decision criteria is an advantage your solution provides which compels buyers to choose your company instead of your competitors.

    Buyer insights help your product, sales, and marketing teams be on the same page as far as buyers are concerned. These insights allow your company to make customer centric decisions which bring in sales and increase your profits.

    Buyers of the 21st century

    "What we are selling is changing; who we are selling to is changing; and how these customers want to be engaged, marketed, and sold to is changing, too". Says Michael Gottlieb, Vice President, Digital Insight at SAP, one of the world's leading software suppliers.

    Gottlieb's words aptly portray the volatile nature of buyers.

    The buyers of the 21st century are changing since they are constantly exposed to new content, social media, and products. According to a report in 2007, most people see up to 5,000 ads a day. If this was the amount then, imagine the number of ads that buyers see in the tech advanced world today!

    In 2008, Linda Stone coined the term continuous partial attention (CPA) to describe an increasingly pervasive mental state unique to the digital age. A former Apple executive, Stone defined CPA as the state of mind people experience when they try to keep up with multiple sources of information. They do this because they have a fear of missing out on anything that they think is important.

    This makes it even harder for your products/services to be noticed. If you don't use strategies that resonate with your buyers, your content will likely be lost in the sea of information.

    Hence, it is necessary to know how buyers think and what they want. Most B2B customers are almost 70% of the way through the purchase decision before engaging a sales representative. This is also probably true with most consumers buying decisions, wherein buyers rely heavily on social media and online resources to guide their buying decisions.

    If you want to boost your sales, you have to create relevant and engaging content that grabs people's minds. Buyer persona is the best option to tell you what the buyer thinks is relevant.


    Marketing is altogether a different ball game in the 21st century. Gone are the days of newspapers and pamphlets. Now you have to approach your buyers instead of the buyers approaching you.

    If you want your products/services to stand out, you need to digitalize. A thorough knowledge of digital marketing and web design is almost mandatory to keep up with the crowd. The most important aspect, however, is knowing your buyers.

    The buyers of the present are highly independent. They know what they want. They have millions of options, and a thousand ways to discover, choose, and reach them. Hence, it becomes imperative to use and incorporate buyer personas into your marketing strategies.

    Frequently Asked Questions (FAQs)

    What are buyer personas?

    A buyer persona is a semi-fictional representation of your ideal customers and represents their goals, pain points, hobbies, interest, motivations, frustrations, personality traits, and more.

    They are created using different data sources, such as data from your past buyers, current customers, and competitors, offering you a holistic view of your buyers based on the commonalities they share.

    What is the origin of buyer personas?

    The evolution of buyer personas began with Alan Cooper, who created the first known persona named Kathy in 1985. Kathy was an archetype that represented a typical software user for Cooper’s project management software.

    How are buyer personas used in marketing?

    Buyer personas are important in marketing because they help you identify your target audience and personalize your marketing strategies according to consumer needs and preferences.

    Additionally, they allow you to:

    • Understand customer goals, challenges, and motivations
    • Create different market segments (high-value and low-value buyers)
    • Develop organic and paid search campaigns
    • Identify communication, content, and channel preferences
    • Uncover consumer buying behavior and industry trends
    Create personas automatically from your Google Analytics data
    Gain a deeper understanding of your digital customers

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