Over 29 million website owners use Google Analytics to understand how people come to their websites, how content performs, and how to get more conversions. Google Analytics is clearly the dominant analytics tool used by web marketers. The main purpose of such analytics tools is to help understand digital users and their interactions better.
Identifying buyers/prospects and associated personas is vital for improving marketing strategy. Given that Google Analytics provides detailed reports based on behavior data collected from users, insights from these reports can be used to create buyer personas.
Buyer personas are usually created through user surveys and interviews. Such qualitative methods can be expensive, time-consuming, and cover only a small section of the entire base of buyers.
Using reports from Google Analytics to create personas and complementing qualitative methods, enables incorporation of buyer insights from data at scale. In an era of fast changing consumer behavior, it also allows for frequent updates that keep personas relevant. Furthermore, they may help uncover customer groups or niches that you were previously unaware of.
This guide will show you the best ways to use your Google Analytics data to create buyer personas. You will learn how to create personas by:
Here are some of the key reports in Google Analytics that empower you to understand your users better and help you create personas.
You can use Audience reports in Universal Analytics (UA) to segregate your users based on attributes related to who they are. They include reports such as age, gender, location, interests, and devices used. You can evaluate distinct groups of buyers based on their geographical location (Audience > Geo > Location) or their purchase habits (Audience > Interests > In-Market Segments).
Similarly, you can use User reports in Google Analytics 4 (GA4) to understand how users are interacting with your website. You can segment users based on their age, gender, language, location, and interests (User > Demographics > Overview). The reports in the User tab also allow you to see the platforms, devices, device models, screen sizes, operating systems, and app versions used by them (User > Tech > Overview).
You can include secondary dimensions/filters and design customized funnels to further interpret your segmented audience.
Acquisition reports in UA illustrate how your audience came to your site. Reports under this section include channel-wise contributions to the acquired traffic (All Traffic). Channels include Direct, Organic Search, Paid Search, Social, Referral, Email, Display, Affiliates, and Other Advertising.
The Acquisition reports in GA4, in addition, show you the number of users who have visited your site or app, the total number of sessions that have taken place, and the percentage of users who have completed a conversion goal. Reports are also available on the number of conversions and revenue generated by your marketing campaigns.
By drilling down further into each channel under Acquisition, Social channel for example, you can get information about specific social networks that serve as better traffic sources for your business. By integrating your Google Ads with Google Analytics, you can see how your paid campaigns are contributing to revenue. Similarly, Google Analytics in combination with Search Console, allows you to see search related data, including queries and landing pages, all in one place.
Behavior reports in UA help you understand how users interact with your website content. It includes reports such as Behavior Flow (user flow), Site Content, Site Speed, Site Search, and Events (user actions).
You can also get valuable content related insights, such as top pages on your website (Site Content > All Pages), landing pages (Site Content > Landing Pages), and exit pages (Site Content > Exit Pages), helping you understand which content users are more attracted to and what they are looking for. Internal Site Search report (Behavior > Site Search > Search Terms) reveals what buyers are searching for on your site. Exit Pages report (Behavior > Site Content > Exit Pages) gives insights about the pages that your users are using to leave your site.
In GA4, you will have to use Engagement reports to understand how users engage with your content (Engagement > Engagement Overview > Pages and screens). You can view metrics like session duration, pages per session, screen views per session, events, and conversions by event names. To view landing and exit pages, you will have to define them as events in GA4 for them to be monitored efficiently.
Conversions reports in UA contain Goals, E-commerce, and Multi-Channel Funnels reports. They show how your users are progressing towards transactions or goals that you have set up in Google Analytics. With these reports, you can see events, purchases, and values of the products along with the time taken to purchase.
Multi-Channel Funnel report shows the contributions of various channels (Referral, Paid Search, Direct, Organic Search, Social Network) to conversions. You can also track users' journeys to becoming customers (Goals > Reverse Goal Path) and understand which features/content on your site work well, which do not, and what needs improvisation.
Google Analytics also offers custom reports (Customization > Custom Report > New Custom Report), attribution reports, and seamless integration with other Google tools.
In GA4, you can find an overview of all your conversions in Conversion reports under the Engagement tab (Engagement > Conversions). To track Goals, you will have to create events specific to your website or use the predefined ones set up by the GA4 system. Once set, you can see which channels, campaigns, and locations are driving the most conversions.
Furthermore, you can view Conversion paths (Advertising > Attribution > Conversion paths) to map buyer journeys and touch points throughout your website and apps.
Available in GA4, Monetisation reports give you insights into the factors and products contributing to the revenue of your website (Monetisation > Ecommerce purchases) as well as your app (Monetisation > In-app purchases). You get to see metrics such as item revenue, items purchased, items viewed, and items added to cart, which give you an understanding of how your website is generating revenue.
You can use the reports under this tab to analyze the performance of specific products (in terms of price, number of units sold, revenue generated) and learn the purchase habits of your buyers. This will allow you to make decisions about your product offerings, pricing, and marketing strategies.
With all these features available for free to website owners, it is no wonder that Google Analytics remains an imperative tool for businesses and their sales and marketing teams.
Though the concept of personas was introduced by Alan Cooper in 1985, they continue to remain active in the discussions of marketing teams today.
That said, what are buyer personas? Why do they still matter? Most importantly, how can they help your business grow?
A buyer persona is a fictional representation of your ideal customers based on various factors. They include inputs from customer demographics, behavior, needs, motivations, goals, competitors data, etc.
Creating buyer personas, as targeted as possible, will help you create actionable content, develop products, understand buyers' pain points, eliminate communication gaps, and strategize to optimize your revenue. Detailed personas will also help you identify platforms you need to be active on in order to reach your buyers.
The steps involved in creating buyer personas include:
If you assume the qualities of your audience and create content for such audiences, they will not be effective. Your trial-and-error method can cost you time and money. This calls for the need to research your customers to understand their challenges, needs, and motivations.
These steps involve addressing personal and work-related questions to recognize their interests, geography, purchasing power, and mediums of communication. To do this, you need to conduct surveys, talk to employees who are directly in touch with customers, and set up one-on-one calls with the ones that you think are your ideal customers.
Once you have the raw data from your customers in hand, segregate them based on their most common attributes. Research and arrive at groups with common demographics, behaviors, interests, pain points, job roles, and mediums of communication.
After segmenting the customers, create buyer personas for the important groups based on the similarity in their challenges and intents. Determine who they are, what they need, and how much they are likely to spend on it. Create a template, give them a name, define their demographics, needs, work, goals, and challenges.
You can start with creating as little as one buyer persona and let your ideal customer profile develop.
After creating buyer personas, you must build strategies to advance your marketing, sales, and product development using the information available on the persona. Determine the communication gaps and increase the awareness of your products and services by inspiring your customers.
In this section, we highlight the reports in Google Analytics that are useful for creating buyer personas.
Before you begin creating personas, make sure that you select a long enough date period for all your reports. A period of twelve months is recommended to generate personas that are more robust and have lesser seasonal biases. The date period can be set using the date range selector, located at the top right corner of each report.
For creating buyer personas, it is best to start with reports under the Audience tab. Screenshots shown below for illustrative purposes are from the Master View of Google Analytics demo account (Google Merchandise Store).
Look at the age range and gender based user distribution shown in the Demographics > Overview report. You can quickly identify the top age group (25-34, as per the screenshot below) and gender (male).
Optionally, you can add segments (+ Add Segment) such as Bounced Sessions, Converters, Made a purchase, etc. to understand variations in age-gender demographics across various segments.
By drilling down into the Demographics > Age report, you can understand the variations across age groups in terms of other key metrics, apart from user percentage, such as sessions, pages per session and average session duration. For e-commerce and SaaS websites, transactions and revenue are the most important metrics. Using these reports, you can determine the best-performing age group(s) for your website.
Similarly, by drilling down into the Demographics > Gender report and evaluating performance across key metrics, you can determine your best-performing gender (male or female) for your business.
However, you must keep in mind that age-group and gender is relevant only when creating personas for B2C (business-to-consumer) businesses, and not for B2B (business-to-business) buyer personas.
From the information gathered so far for this example, the best-performing buyer persona can be assumed to be a 25-34 year old male.
To validate this hypothesis, you can click the top performing gender (male in this case) in the Gender report and use the next level report that combines Gender + Age information.
(Alternatively, you can drill down from the Demographics > Age report, as shown in step 2 above. Click on the top performing age 25-34 in the Age report and use the next level report that combines Age + Gender information to validate the hypothesis.)
Once the age and gender for your buyer persona have been identified, drill down further to the Interests report to get ideas on what they are interested in. To do so, click on the top performing age-group (25-34) in the Gender + Age report.
The Other Category report (Gender + Age + Interests) shows the specific interests of this target group. As can be seen, this group is technology-savvy, loves mobile gadgets, and consumes videos and celebrity/sports news online.
Click on the "Other" dropdown next to "Primary Dimension" to view two other types of interests: Affinity Category and In-Market Segments.
Affinity Category report provides information on the lifestyle interests of this group of users at a more abstract/generic level than Other Category report.
In-Market Segment report lists their current purchase interests for product and services.
Geo report (under Audiences tab) provides insights about the languages that users primarily prefer (Geo > Language) and the locations from where they access (Geo > Location) your website.
The Language report provides insights into language preferences based on the settings of the users' browsers and are listed as per their ISO codes.
The Location report allows you to view the hierarchy of countries your users are from and the associated metrics.
When you click on a specific country (United States being the top country in this example), it shows you the top regions/provinces/states of that country where the users are from.
By changing the Primary Dimension of this report from Region to City, you can also see the top cities that the users are from. Use this information (New York City in this case) to define where the persona is based.
Use the Technology report (Audience > Technology) to view information about the users' browser versions and operating systems.
Further, the Mobile reports (Audience > Mobile > Overview, Audience > Mobile > Devices) help you understand the type of devices that your users prefer to use (computers, mobiles, or tablets) and in the case of mobiles and tablet device types, the brands and models of the devices used while interacting with your website.
The Technology and the Mobile reports reports help you identify the devices that you should use to optimize your website.
Keyword report (Audience > All Traffic > Channels > Organic Search) provides the list of keywords used by users to reach your website. You should ignore the rows with keyword values matching "(not set)"", "(not provided)"" and URLs.
As with the Universal Analytics version of GA, you have to make sure that you select a long date range for your personas to be accurate. Google Analytics 4 (GA4) comes with a number of predefined date ranges that make it easier to select a date range for your personas. Set the date period to the Last 12 months using the date range selector, located at the top right corner of your dashboard.
You can also create customized date ranges in GA4 according to your needs and goals.
Once you have selected the date range you want to create personas for, move onto the User tab. The screenshots given below are from a GA4 demo account and being used for illustrative purposes only.
You can find the age range and gender based user distribution in Demographics > Overview. Here, you can simultaneously identify the top performing age group (25-34) and gender (male).
By looking at the Demographics > Overview > Age report, you will be able to identify and compare variations across age groups in terms of key performance metrics like engagement sessions, engagement rate, events, conversions, and revenue. This information will allow you to identify the top-performing age groups for your website.
Similarly, the Demographics > Overview > Gender reports will allow you to determine the best performing gender based on various key metrics for your business.
From the reports generated so far, you can deduce that your persona is shaping out to be a male belonging to the 25-34 age category. To validate this, you can click on Demographics > Overview > Gender report and add Demographics > Age. This will allow you to combine the Gender+Age information.
Once you have identified the gender and age of your ideal customer persona, you can find out their interests in Demographics > Overview > Interests. Set the filter as Gender > Male and Age > 25-34 and find out what they are interested in.
This report will give you insights into the general topics your ideal customers are likely to be interested in. As the screenshot above indicates, this segment of users are value shoppers who seem to take an interest in technology, movies, travel, and finance.
Sadly, GA4 does not give you Other Category and In-Market Segment reports. Hence, you cannot get specific information about users' lifestyle and purchase interests.
You can also segment users by the language that they use (Demographics > Overview > Language) and the country (Demographics > Overview > Country) from where they access your website.
A noticeable difference between UA and GA4 Language reports is that the latter does not list languages as per their ISO codes. However, it gives the necessary information about your users' language preferences.
Similarly, the Country report allows you to see the top countries that your users are from.
You cannot just click on the country (in this case USA) to view the top performing regions of that country in GA4. Instead, go to Demographics > Demographic details > Region and add a filter specifying the country.
To view the top towns or cities, click on Demographics > Demographic details > Town/City and apply the same filter as before. All of this information will allow you to pinpoint exactly where your persona is located.
You can also find information related to user platforms, browsers, devices, device models, operating systems, and screen resolutions. Click on Tech > Overview in the User tab to access this data.
These Tech reports will help you identify and analyze the devices, platforms, and browsers that you should optimize your website structure for.
Using all the information thus obtained from various Google Analytics reports listed above about your best performing group (age group, gender, interests, location, language, and technology preferences), you can put together your first persona (primary persona).
You can then repeat these steps with different criteria of metrics, such as high bounce rates/low engaged sessions for your less interested audience, to create additional personas. With 3-5 personas in place, you will likely be able to identify differences between them. Use these personas to refine your marketing strategies and sell to /serve your customers better.
Make an outline of the key elements needed to define buyer personas. Find below an initial list of such features, along with the Google Analytics reports that provide the relevant information.
In Universal Analytics:
Given that Demographics and Interests reports provide key insights that help create more accurate buyer personas, you should enable Demographics and Interest reports in Google Analytics, if not already done so.
Follow the steps below to enable Demographics and Interests reports in Google Analytics.
In Universal Analytics:
Now that you have identified the information that you need to create customer personas and how to get them using data reports from Google Analytics, it's time to pull the raw data. Use a time period of six months to a year. The larger the data that you have, the better it is for your personas.
As businesses usually form more than one buyer persona, generate reports based on multiple metrics/segment criteria so that you can create several personas under distinct customer types.
Export the reports, and save them, grouped by customer types. Look for patterns and filter out the best performing user categories. Write them down in a separate document.
With the information you have obtained, you can map them out as personas. Write the information like narrating a character. Here are some details to keep in mind while drafting personas.
Name: A buyer persona is a fictional representation. Give it a name that is very generic for virtual identification. Each of your customer types must have a unique name which will make teams across your organization easily identify with them.
Photo: This is essential for the persona's identity. You can use actual pictures of people available for reuse or create an illustration or a vector image of the character. Make identity as realistic as possible. Consider age, professional factors, and geographical factors while doing so.
Description: Description is a space wherein you 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 you think applies to your industry or market segment under it.
Buying triggers and process - Buying triggers include the kinds of advertising or situations that the buyers consider while making purchase decisions. Get this information via Google Analytics under Acquisition reports. We can view the buying process and channels involved under Conversions > Multi-Channel Funnels in UA and Engagement > Conversions in GA4.
Challenges - Every customer has challenges and constraints. For each customer type, find what constraints are relevant to your users and list them down.
Although the process of creating your initial set of buyer personas ends here, it is important to keep in mind that your users and their behaviors will keep evolving. As a result, you must update your personas every six months or so, depending on your industry. Regularly updated personas will keep you informed on changing user behavior and trends in your industry's ecosystem.
Business-to-consumer (B2C) and business-to-business (B2B) buyers differ in their needs and behaviors. Our blog article on B2B buyer personas explains how B2B purchasing processes are more involved compared to B2C buying processes. It also summarizes the differences in characteristics between such processes, including navigation, time, people involvement, intent, and purpose. These considerations must be kept in mind when developing buyer personas for B2C and B2B businesses.
Nowadays, various online platforms and services can automatically create buyer personas using multiple data sources. However, first let's take a look at some of the challenges associated with the manual process of creating personas.
The manual process of creating buyer personas using analytics data from sources like Google Analytics can be tiring and intimidating. Here's a list of some of the key challenges associated with manual methodologies.
An alternative to employing manual techniques to create buyer personas from Google Analytics is to use automated tools such as Live Persona by Delve AI. You no longer need to manually create mental models of digital users and buyers from dimensions and metrics and can get humanized views in terms of buyer personas automatically.
Using automated tools help eliminate errors and ensure robust personas. It creates personas based on business type (B2C/B2B) considerations and extracted industry specific insights. Additionally, segments and associated personas are automatically generated based on behavioral differences, thereby providing insights into variations across groups.
Live Persona by Delve AI is the world's first software used to generate personas automatically from web/mobile analytics data. It works on aggregated and anonymized analytics data from Google Analytics, adds industry specific insights, automatically segments users based on their behavior, and leverages advances in machine learning to generate personas for each segment.
No more time-consuming manual analysis!
Personas are auto-generated and kept up to date. You can gain clarity on your best-performing segments, refine your customer experiences, and get targeting ideas from your most valuable segment to grow your business.
Here are some of the key advantages that you get by using Live Persona by Delve AI for creating buyer personas from your Google Analytics data.
Automatic generation of buyer personas: With Live Persona by Delve AI, accurate segment-wise buyer personas are automatically generated in minutes from your Google Analytics data. You don’t need to spend hours on end struggling to define and characterize your customer profiles.
Raw data from websites/ mobile applications is pulled from Google Analytics in an anonymized and aggregated form by Delve AI platform and put through multiple steps of data enrichment/augmentation, learning based behavioral analysis, automatic segmentation, and humanization to create deeply insightful buyer personas.
Enriched analytics: Data is augmented for deeper user context, with 20+ external/generated data sources/models. These added dimensions, not available natively in Google Analytics, are also used as inputs when creating personas and are available on the Delve AI dashboard. They include:
Industry specific insights: By analyzing user behaviors (e.g. viewed pages and searches), key structured attributes that are specific to your industry/vertical, are also extracted. For example, in the apparel & fashion industry, keywords are grouped and presented in terms of relevant attributes such as size, gender, occasion, type, color, age-group, etc.
Delve AI's analysis systems automatically extract industry specific insights for over 40+ major B2B/B2C industries. Industries supported include:
Behavioral analysis using machine learning: Figuring out buyer intent and their decision phases (with respect to purchase processes) are key elements that can add lot of value when creating buyer personas. Delve AI uses machine learning techniques to unearth these insights, including:
Automatic segmentation: Users are segmented automatically using behavioral factors such as:
Sizes of each segment are displayed in terms of the percentage (%) of users of the entire audience. Personas are separately extracted for each segment.
Humanized representations: As personas require people based representations, Delve AI automatically decodes user behavior and transforms segment-wise data for human assimilation and follow-ups. It does so by adding humanized details such as preferences, personal lifestyles, interactions, and sample journeys to create personas. By moving from data dimensions and metrics based representations, these personas bring empathy to your data driven marketing efforts and keep people at the center of decisions and activities.
User distribution: While a persona representation provides useful insights via a single person representation, it is also useful to see the distribution of attribute values across users in a given segment. The age attribute, for example, is captured in a persona representation as a single age (e.g. 27 years old). User distribution, on the other hand, helps gain a deeper understanding of the distribution of age group ranges across all users in a segment.
Sample user journeys: Delve AI also extracts and displays sample user journeys for each segment. As you will read in this article, personas when used in conjunction with journeys, can help identify and eliminate drop-offs/obstacles and deliver improved customer experiences.
Unlike B2C purchases, buying a B2B product/service typically involves multiple people. Additionally, the usage of B2B offerings may span multiple functions and hence buying decisions involve several departments of the company.
Given these differences, B2B buyer personas and user journeys should ideally be at the organization level and not at the user level.
Delve AI handles such B2B scenarios automatically and provides deep insights into organizations, industries, company sizes, job functions, and job experience levels of likely buyers in each segment.
Further, Delve AI automatically classifies visitors to B2B websites into one of the visitor groups listed below. This list is based on profile, intent, behavior, and persona identification.
Insights from buyer personas can be used to form effective strategies to reach and influence your target buyers across different buying decision stages. The more detailed your buyer personas are, the more personal you can make your messaging and outreach campaigns.
When used along with customer journeys, buyer personas help:
Creating and using buyer personas is essential in today's dynamic market environment. Businesses all over the world are vying for sustainability and growth. Hence, it is important to know your target audience well and stay alert about their evolving needs and priorities. With the vast amount of information currently available about buyers and their behaviors (from sources such as Google Analytics), you can use the steps listed in this article to create buyer personas on your own.
You no longer have to do guesswork to understand your digital buyers.
With tools like Live Persona by Delve AI, you can leverage advances in artificial intelligence and machine learning to generate accurate data-driven buyer personas and get amazing customer insights with ease. You can try it for free and get results in minutes. Making use of these resources not only helps you save time and money but also gives unique ideas to expand your business.
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