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3 Examples of User Personas – Clear and Practical Way

The following post provides 3 examples of user personas created using Google Analytics and Data Studio. Automated data collection and consolidation is done by Data Studio to generate dashboard and reports.

What are user personas?

User personas are profiles of our customers to help understand their needs, behavior, and goals. These users share similar characteristics, attitudes, personalities, and preferences.

There are 4 different perspectives on types of user personas:

  • Goal-directed focus on the wants of users to do with our product or service.
  • Also to the user’s goals, roles also include their behavior. The personas are based on massive amounts of data.
  • Engagement personas include goals, roles, emotions, psychology, and background are examined to make them relevant.
  • Fictional personas make assumptions based on prior interactions with the users, and products, to present a picture of, perhaps, typical users

In this article, we will create fictional examples of user personas. The template for persona will be used to develop engaging stories that illustrate the personas.

Why do we need user personas?

The user persona identifies common traits and behaviors. The main purpose of these fictional personas is to segment visitors to our website.

Our product and marketing initiatives are guided by this information. Moreover, we gain insight into our customers.

These are based on the main groups of users we are targeting. We use this dashboard to identify which group(s) are most effective for our website and target our products/services accordingly.

Why are we using Google Data Studio?

Normally, team members have a hard time creating these personas. Data is obtained through research and interviews with real people. Data collection is time-consuming.

Also, our personas need to be updated regularly as well. The behavior of users will continue to change. As a result, we may need to revisit our personas every six months to two years.

We can create fully automated reporting dashboards using Google Data Studio. This technology saves me countless hours on reporting. Also, report sharing and collaboration features allow business partners to communicate more easily. Individuals can also see each other’s reports at any time, ensuring a constant flow of information.

User understanding is the key to business success, and personas are a vehicle for this. Market research can be done poorly with any tool. Personas can be created based on Google Analytics data of people visiting our website. This helps to select the right tool and use it effectively.

How to Build our Google Analytics Personas

Users are not all the same, so data is important. Google Analytics data offer us a jump start to the research. It helps us to understand the audience already visiting our website. It allows us to create customer personas.

To answer these four questions, I gathered the following information:

  • Which country or city are they in?
  • What are their age and gender?
  • How would we describe them, e.g., interests, values?
  • What do they do e.g. entertainment, hobbies, employment?

Data Studio Dashboard

A user persona can be defined using data collected from Google Analytics. The process of describing these personas begins with choosing a period of time long enough to collect data. To generate robust personas with fewer seasonal biases, I chose the period between 1st January 2020 – 3rd June 2021. Thus, we can be confident in our Google Analytics personas being relevant and have time to get them.

We have a short demonstration of the dashboard on YouTube

Get to know key elements

The purpose of creating user personas is to gain a better understanding of potential and existing clients. We will now walk through each step of this interactive dashboard to see how it works

In particular, we identified their gender and age demographics.

Age and Gender

To create the profile, I am using Sessions as my metric. An interaction with our website that occurs within a specified timeframe is called a session.

Apart from sessions, we can understand the differences in age groups based on user %, pages per session, and average session duration.

For our examples of user personas, we notice that most users are between 25-34 years of age and are male.

Location

We drill down further into Location (Country, Region, City), once the gender and age of the user persona have been identified. This helps us to see the countries our users are from and the metrics associated with them.

In our first example, clicking on the top country (the United States) reveals the top regions, provinces, states, and cities where the users are from. If we select City, we can also see the top cities (New York) where the users are.

We can specify where the persona is based on this information (in this case, New York City, USA).

Spoken Language

Also, we can find the language spoken by our users so that we can speak to them in their own language. Based on the settings of the users’ browsers, the Language report provides insights into language preferences.

For our examples of user personas, data consists mainly of English-speaking US audiences. This means that we can use ‘color’ without the ‘u.

Beliefs, Values, and Interests

Next, we dive into using Interests report & Affinity. When combined with other demographics, these reports can be invaluable.

We can get their hobbies (Leisure interest) using Other Category. This gives an indication of their interests. Gender + Age + Interests shows which particular interests are relevant to this target group.

The top interest in our first example is [Life Events] Moving/Moving Soon. Moving means we can assume that users are trying to settle down.

After Interests (personal preferences related to food, travel, etc. ), we look at the Affinity Category. In terms of online customers, affinity categories help to identify them at scale.

Various factors are taken into account when Google Analytics creates a user profile (e.g. shoppers, technophiles, foodies, music lovers). By knowing this more, we can develop a better understanding of our persona.

For our examples of user personas, the lifestyle interests of our audience are represented as Technology/Technophiles, value shoppers, media, and entertainment.

Work (Employment status, designation) is available in In-Market Segments. It is a  way to reach customers who are researching and comparing product services across the Google Display Network  (YouTube, paid search results via AdWords, display ads via AdSense, etc).

Our example describes the product and service of interest in the areas of Computers & Peripherals/Computer Accessories & Components.

Technology and Devices

We may also look at what technology the users are using to find out how they connect with each other. The browser version and operating system of the users are viewed.

Furthermore, the Devices report provides insight into the devices that our users prefer to use (computers, mobiles, or tablets), including the brands and models of the devices used as they interact with our website. The Technology and Mobile reports help us identify which devices to optimize for our website.

Users of Windows Operating System and Chrome are depicted in our example. There are also more desktop users than mobile users.

Channels

The channel tells us how the user reached our website. For our first example of user personas, direct search is much more popular than paid or affiliate marketing.

Building User personas

As a result of collecting all this information about our best performing group (e.g. age group, gender, interests, location, technology preferences) from the Google Data Studio dashboard and reports, we can construct our first persona. 

Remember to make it look super clear and give it a personality by using these 3 sections:

Name – Give persona a name that is very generic for virtual identification. Each type of customer must have a unique name so that teams across our organization can identify them.

Photo – Use a picture of people that we have available for reuse or create an illustration or vector image of the character. Make identity as realistic as possible.

Brief Bio – is a space where we describe the persona’s characteristics. Write them in sentences to make it a narration or use bullets. Mention the persona’s age, gender, profession, interests, hobbies, social lifestyle, and needs. Include any information that applies to our industry or market under it.

After we have completed the above process, we can repeat it with different criteria of metrics, such as low engagement for our less interested audience, to create even more personas.

Examples of User Personas

1st

Examples of User Persona -1

2nd

For our 2nd persona of a user, we select a person between 18-24 years of age and female. We select India as a country. She resides in Delhi (city). Our sample consists mainly of English-speaking audiences. The top interest is again a life event of either a job change or recently started a job. This interest is followed by Arts & Entertainment/TV & Video/Online Video.

These users have recently graduated and starting a new job or changing their employment. They also like to enjoy themselves.

The lifestyle interests of our audience are represented as :

  • Lifestyles & Hobbies/Fashionistas
  • Beauty & Wellness/Beauty Mavens
  • Media & Entertainment/Movie Lovers

Our example describes the product and service by interests of the company in the areas of Employment/Career Consulting Services.

Users of the Windows Operating system and Chrome are depicted in this example. In this example, direct search is the preferred channel.

Examples of User Personas – 2

3rd

For our 3rd persona of a user, we select a person between 55 – 64 years of age and male. We select the United Kingdom as a country. He resides in London(city). Our sample consists mainly of English-speaking audiences.

The top interest is Arts & Entertainment/Celebrities & Entertainment News/ TV & Video/Online Video. It is followed by News/Business News/Financial Markets News. This shows that the person has settled in his life. The interest is also different than previous personas.

The lifestyle interests of our audience are represented as :

  • Food & Dining/Frequently Dines Out/Diners by Meal/Frequently Eats Lunch Out
  • Lifestyles & Hobbies/Green Living Enthusiasts
  • News & Politics/Avid News Readers

Our example describes the product and service by interests of the company in the areas of

  • Financial Services/Investment Services
  • Business Services/Advertising & Marketing Services

Users of the Machintosh Operating system and Chrome are represented in this example. Also, direct search is the preferred channel.

Could you create the 3rd persona based information?

Feel free to share the user personas you created in the comments below!

Conclusion

The purpose of this article was to explain how to create personas by using Data Studio to visualize the Google Analytics data. We are able to identify customers for our business.

We were also able to gather information and create 3 different personas. These personas are data-driven. We will be able to refine our marketing, product strategy according to these personas to better serve our customers.

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