{"id":788,"date":"2020-05-25T13:48:58","date_gmt":"2020-05-25T10:48:58","guid":{"rendered":"https:\/\/persona.qcri.org\/blog\/?p=788"},"modified":"2022-10-05T05:26:49","modified_gmt":"2022-10-05T02:26:49","slug":"persona-creation-using-google-analytics-summary-of-methods","status":"publish","type":"post","link":"https:\/\/persona.qcri.org\/blog\/persona-creation-using-google-analytics-summary-of-methods\/","title":{"rendered":"Persona Creation Using Google Analytics: Summary of Methods"},"content":{"rendered":"<p><em>This post is co-authored with\u00a0Noor-ul-Anam Ruqayya<\/a>, a Software engineering graduate from the University of Karachi. Noor is currently working as a content writer and digital marketer.<\/em><\/p>\n<p><span style=\"font-weight: 400;\">In this post, we summarise seven articles that explain the process of creating buyer or user personas with Google Analytics. The purpose of this post is to discuss various methods bloggers and marketers use to create buyer personas. In brief, Google Analytics can be used to discover clients and gather data about them through reports.<\/span><\/p>\n<p><!--more--><\/p>\n<h2><span style=\"font-weight: 400;\">5 Google Analytics Reports to Help Build Your Buyer Persona\u00a0<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">In the <\/span><a href=\"https:\/\/www.semrush.com\/blog\/5-google-analytics-reports-to-help-build-your-buyer-personas\/\"><span style=\"font-weight: 400;\">article<\/span><\/a><span style=\"font-weight: 400;\">, the author Clayton Coomer explains why the buyer personas are important. He further reasons that Google Analytics makes the process of creating personas simple and presents five analytics reports to help build buyer personas. The reports are as follows.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Report 1: Demographic Overview\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The demographic overview report is quite generic and presents the basic age and gender information. A quick analysis of data shows:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">The age range is between 25-34-year-olds<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Majority of the audience is male<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">To pull the age demographic review report, navigate to the Audience tab -&gt; demographics -&gt; overview.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Report 2: Demographics: Age<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">This report presents the age breakdown<\/span> <span style=\"font-weight: 400;\">and details about the targeted age segments. This report is useful as it tells us the specific age group we should be targeting.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A quick analysis of the data shows:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Ages 25-34 range:<\/span>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Generates the most revenue<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Are responsible for the most transitions and sessions\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Have the best conversion rate<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">To pull the age report, go to the Audience tab -&gt; demographics dropdown -&gt; age.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Report 3: Demographics: Gender<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Similar to the age report, the gender report<\/span> <span style=\"font-weight: 400;\">gives insights into the gender of our client. The usefulness of this report depends on the product\/service, as some products or services are gender-neutral.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A quick analysis of data shows:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Males have:<\/span>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">A higher conversion rate (over 1% better)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Generated over 1M more in revenue compared to women<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">A majority (56%) of the traffic is generated by the male\u00a0<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">To pull this report, find the Audience tab -&gt; demographics -&gt; gender.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Report 4: Demographics: Age (+Gender)<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">This report is not a generic report, so it\u2019s not available in the left sidebar.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To access this report, pull the age demographics report, and click on the age range to display gender breakdown. A quick analysis of data shows:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Males between the ages of 25-34,<\/span>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Generate the most revenue (nearly \u00bc of the total)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Account for 22% of all transactions\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Account for 25% of all website sessions.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">This report gives more details but we still lack personal information, which the author targets in the next report.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Report 5: Demographics: Age\/Gender + Interests\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Staying in the current report, click male. Your Google Analytics should take you to the <\/span><b>\u201cother categories\u201d, <\/b><span style=\"font-weight: 400;\">change to the <\/span><b>\u201cAffinity categories\u201d<\/b><span style=\"font-weight: 400;\"> and click the green correspondence box. Once the process is complete, the report should be ready.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The quick analysis of the report indicates that the segment is:\u00a0<\/span><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Tech-savvy<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Loves watching TV (Netflix mostly)\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Loves to travel and watch the news (on mobile)<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3><span style=\"font-weight: 400;\">Example of the Persona<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The next step is to go back and see who the next profile should be and create at least three. Use the data collected from the Google Analytics report to create the buyer persona.<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-803\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/google-analytics-persona-example-1.jpg?resize=650%2C292&#038;ssl=1\" alt=\"\" width=\"650\" height=\"292\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/google-analytics-persona-example-1.jpg?w=650&amp;ssl=1 650w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/google-analytics-persona-example-1.jpg?resize=300%2C135&amp;ssl=1 300w\" sizes=\"auto, (max-width: 650px) 100vw, 650px\" \/><\/p>\n<h3><span style=\"font-weight: 400;\">Takeaways<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">In this post, the author has discussed five audience analytics reports: demographics, age, gender, age+gender, and age+gender+interests. Each report is extended from the previous report and adds some new information which is then used to create a buyer persona. For example, the first report (demographic overview) shows the gender and age of the audience, and the next report (age demographics) presents the age breakdown and targeted age segments, and so on.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Segment Analytics Data Using Personas\u00a0<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">A persona is usually created at the beginning of the design and strategy phase of a project. In this <\/span><a href=\"https:\/\/www.nngroup.com\/articles\/analytics-persona-segment\/\"><span style=\"font-weight: 400;\">article<\/span><\/a><span style=\"font-weight: 400;\">, the author has introduced a method of creating persona-inspired segments using the analytics tool. Although the author does not specify the tool being used, the reports listed by him indicate the tool is Google Analytics.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">By creating the user segments based on personas, one can analyze how real users interact with your website. This information can be used to validate and refine the assumptions made during the research phase and uncover the information you may have missed before.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The key step in this method is to include segment filters that separate the prime characteristics of a specific group of users by analyzing user activity.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">According to the author, a few ways to segment users derived from the persona include:\u00a0<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Demographics<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Geographic locations<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Device and\/or browser<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">New vs. regular visitor<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Source (how they found the website)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Keywords and pages targeted by the users\u00a0<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">As personas are categorized into segments, the volume of data is reduced. That makes it easier to analyze and draw very specific conclusions. Segments do not just enable us to analyze metrics but help uncover behavioral patterns in specific segments.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Consider an example of analyzing the <\/span><a href=\"https:\/\/support.google.com\/analytics\/answer\/1009409?hl=en\"><span style=\"font-weight: 400;\">bounce rate<\/span><\/a><span style=\"font-weight: 400;\"> of a page. You have the bounce rates of two users, Mary (83%) is a subscriber, and Mark (37.5%) is not. The difference between the bounce rates of Mary and Mark is 65%. This information gives you a better understanding of how the page performs given the specific goals of each user.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In conclusion, the quantitative data from the analysis tools (like Google Analytics) tells you how the user behaves. To understand why they behaved in a certain way, you can help with user-research activities like <\/span><a href=\"http:\/\/usabilitytesting.sg\/user-experience-course\/lesson-5-qualitative-user-testing-methods\/\"><span style=\"font-weight: 400;\">qualitative usability testing<\/span><\/a><span style=\"font-weight: 400;\">. The triangulated data from both sources can help optimize your website to address the needs of each user.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Takeaways<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The author discussed the creation of user segments to analyze buyer persona in order to improve website performance over time. This process can be completed using any analytics tool and users can be segmented in a number of ways like demographics, interests, etc.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">How to Create Personas using Google Analytics<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">User personas are usually created using qualitative data. In this <\/span><a href=\"https:\/\/www.userzoom.com\/blog\/how-to-create-personas-using-google-analytics\/\"><span style=\"font-weight: 400;\">how-to guide<\/span><\/a><span style=\"font-weight: 400;\">, the author shows how to build personas using quantitative data collected from Google Analytics.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the post, the author explains that the best way to achieve business goals is by figuring out who the audience is. Then identify the key patterns that are driving the most conversions to the business. Identifying these patterns reveals the core audience.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Before going forward, one must understand the difference between qualitative and quantitative research.\u00a0<\/span><\/p>\n<p><b>Qualitative research<\/b><span style=\"font-weight: 400;\"> helps one understand the underlying reasons, opinions, and motivations behind customer behavior. Qualitative research is conducted through methods such as:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Observation<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Focus group sessions<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Interviews\u00a0\u00a0<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In <\/span><b>quantitative research<\/b><span style=\"font-weight: 400;\">, the results can be presented in numerical values. It answers the \u2018how many\u2019, \u2018how-often\u2019, and \u2018how much\u2019 kind of questions. Types of quantitative research include:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Surveys<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Online polls<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Both research types have their advantages and drawbacks. To understand the audience accurately, The holistic approach is taken to combine the quantitative and qualitative research results.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To generate a complete persona, the author pulled four reports in different steps.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Step 1: Age and Gender<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">To pull this report, go to the Audience tab -&gt; Demographics -&gt; overview.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The largest demographic is, \u201825-34-year-old male\u2019. It\u2019s not much but you have the basis to create your persona.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To add more detail, click Age and then the <\/span><b>secondary dimension <\/b><span style=\"font-weight: 400;\">section to find and add \u2018Affinity\u2019.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Step 2: Affinity\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The \u2018Affinity\u2019 category helps identify the online prospective customers at scale. Google Analytics uses factors like browsing history, time-on-page, and associates them with the user-profile (foodie, shopper, etc).<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the image, the affinity category has been added to the age demographic that shows the main interest of the client.<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-806\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig2-creating-persona-using-GA.png?resize=1024%2C542&#038;ssl=1\" alt=\"\" width=\"1024\" height=\"542\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig2-creating-persona-using-GA.png?w=1024&amp;ssl=1 1024w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig2-creating-persona-using-GA.png?resize=300%2C159&amp;ssl=1 300w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig2-creating-persona-using-GA.png?resize=768%2C407&amp;ssl=1 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/p>\n<h3><span style=\"font-weight: 400;\">Step 3: In-market<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">In the <\/span><b>Secondary Dimension <\/b><span style=\"font-weight: 400;\">category, find the <\/span><b>in-market segment. <\/b><span style=\"font-weight: 400;\">This gives you customers that are actively searching for products\/service across GDN (Google Display Network) i.e. YouTube, AdWords, AdSense, etc.<\/span><\/p>\n<p><b>See the image below:<\/b><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-804\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-creating-persona-using-GA.png?resize=580%2C409&#038;ssl=1\" alt=\"\" width=\"580\" height=\"409\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-creating-persona-using-GA.png?resize=1024%2C722&amp;ssl=1 1024w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-creating-persona-using-GA.png?resize=300%2C211&amp;ssl=1 300w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-creating-persona-using-GA.png?resize=768%2C541&amp;ssl=1 768w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-creating-persona-using-GA.png?resize=1200%2C846&amp;ssl=1 1200w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-creating-persona-using-GA.png?w=1300&amp;ssl=1 1300w\" sizes=\"auto, (max-width: 580px) 100vw, 580px\" \/><\/p>\n<h3><span style=\"font-weight: 400;\">Step 4: Geo<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The language and locations reports tell you where your ideal client segment lives and their language. For instance, if your major clients are UK-based, then you may benefit from adding \u2018u\u2019 to color.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To see the devices you audience use, go to the Audience tab -&gt; Mobile -&gt; Devices.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Build the persona<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Use the collected data set to build a buyer persona. It is crucial to name the person and give it a face. That makes it easier for marketers to empathize with their customers. Present your user attributes and character in a table under a chosen name.<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-807\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig6-creating-persona-using-GA.png?resize=1024%2C577&#038;ssl=1\" alt=\"\" width=\"1024\" height=\"577\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig6-creating-persona-using-GA.png?w=1024&amp;ssl=1 1024w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig6-creating-persona-using-GA.png?resize=300%2C169&amp;ssl=1 300w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig6-creating-persona-using-GA.png?resize=768%2C433&amp;ssl=1 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">You can also present the persona in a more appealing way.\u00a0<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-808\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig7-creating-persona-using-GA.png?resize=1024%2C687&#038;ssl=1\" alt=\"\" width=\"1024\" height=\"687\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig7-creating-persona-using-GA.png?w=1024&amp;ssl=1 1024w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig7-creating-persona-using-GA.png?resize=300%2C201&amp;ssl=1 300w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig7-creating-persona-using-GA.png?resize=768%2C515&amp;ssl=1 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/p>\n<h3><span style=\"font-weight: 400;\">Takeaways<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The author discussed how important it is to conduct both qualitative and quantitative research to collect user data. He further used four Google Analytics reports, age and gender, affinity, in-market, and geo to analyze\u00a0<\/span><span style=\"font-weight: 400;\">user data to build the buyer persona.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">How to Create Buyer Personas With Google Analytics<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">The author, Ben Jacobson discusses why it is important to <\/span><a href=\"https:\/\/www.socialmediaexaminer.com\/social-media-buyer-personas-google-analytics\/\"><span style=\"font-weight: 400;\">create a social media buyer persona<\/span><\/a><span style=\"font-weight: 400;\">. He also discusses the step-by-step method of creating personas with Google Analytics.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Jacobson argues that the definition of buyer personas is not just about the target audience but about finding similarities among the target audience.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">With a perfect social media buyer persona, one can create content that targets user concerns and interests making for a more engaged audience.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The data about the user persona can be found in the website analytics. The data can be used to create a buyer persona with Google Analytics in four steps.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Step 1: Research your Website Traffic by Keyword<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">To begin, open Google Analytics and go to <\/span><b>Acquisition -&gt; All Traffic -&gt; Google\/Organic,<\/b><span style=\"font-weight: 400;\"> and set the \u2018<\/span><b>Secondary Dimension\u2019<\/b><span style=\"font-weight: 400;\"> to <\/span><b>Keyword<\/b><span style=\"font-weight: 400;\">.<\/span><span style=\"font-weight: 400;\">\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This will pull the keyword searches that bring visitors organically to your site. You will be able to see all the keywords, but there\u2019ll be enough to get started. Copy and store the list to a spreadsheet.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Step 2: Find Similar Users in Search Traffic<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The author suggested going through the spreadsheet and grouping the data into themes and categories.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For instance, if you market sports goods, then place them into separate categories like, clothing, footwear, or location-specific queries, etc. These categories can determine who is searching and find the right questions to ask yourself.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">You can make a list of personas such as, \u2018serious runner looking for sneakers locally under $100\u2019. This is a rough version of a buyer persona.\u00a0\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Step 3: Refine Buyer Personas by Social Channels<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">One a rough persona has completed. Referral traffic data from Analytics can be used to create prototypes of the audience for each of your social media channels.\u00a0\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To create the prototypes, go to, Acquisition -&gt; All Referrals. Choose your secondary dimension and click on the landing page.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The preference and patterns will help create specific content for each social network. Through this data, a restaurant may find that Facebook refers to people looking for reservations and Twitter refers mostly to people looking for daily specials.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Step 4: Fill Out Social Details for Your Personas\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">You can also look for patterns among your fans and followers on social media. <\/span><a href=\"https:\/\/analytics.twitter.com\/about\"><span style=\"font-weight: 400;\">Twitter analytics<\/span><\/a><span style=\"font-weight: 400;\"> can give relevant insights from <\/span><b>\u2018your followers also follow\u2019<\/b><span style=\"font-weight: 400;\"> and <\/span><b>\u2018interests\u2019<\/b><span style=\"font-weight: 400;\"> sections.<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-809\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-create-persona-with-GA.png?resize=344%2C562&#038;ssl=1\" alt=\"\" width=\"344\" height=\"562\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-create-persona-with-GA.png?w=344&amp;ssl=1 344w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig3-create-persona-with-GA.png?resize=184%2C300&amp;ssl=1 184w\" sizes=\"auto, (max-width: 344px) 100vw, 344px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">To pull common keywords, the author used <\/span><a href=\"https:\/\/followerwonk.com\/\"><span style=\"font-weight: 400;\">FollowerWonk<\/span><\/a><span style=\"font-weight: 400;\"> for Twitter and Graph Search (original graph search was discontinued by Facebook, <\/span><a href=\"https:\/\/developers.facebook.com\/docs\/graph-api\/\"><span style=\"font-weight: 400;\">Graph API<\/span><\/a><span style=\"font-weight: 400;\"> can be used as a replacement) for Facebook. Examining other social media platforms like Behance, Empire, Quora, and OpenForum can further narrow down your search. For instance, people who spend time on Q&amp;A sites enjoy content pieces written by experts while those who like picture-sharing based social media networks look for content that is rich in images.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">These analytics help you connect with your understanding of the community and connect with them on a more personal level. This is vital for effective social media marketing (SMM).<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Takeaways<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The author discussed the importance of user persona in creating a social media marketing strategy. He explained Google Analytics and other analytics tools like Twitter Analytics, and tools like followerWonk and Graph search to help understand one\u2019s social media following.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Your Website Personas &#8211; How to Quickly Find out with Google Analytics\u00a0<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">In <\/span><a href=\"https:\/\/mattish.com\/blog\/post\/how-to-create-personas-from-google-analytics-data\"><span style=\"font-weight: 400;\">this post<\/span><\/a><span style=\"font-weight: 400;\">, the author explains that while creating personas can be difficult, there is a way to create personas in 10 minutes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As Google Analytics data usually narrows it down to one persona, this persona can be used as a guide for content and marketing development. One can start by asking if the user was a person, who would he\/she be?\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Create a user statement, who the person is, and match it to the ideal user. This step helps make sure that one is targeting the right users and if not, then how to find and target the ideal user.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The author uses six types of data to create a user statement with Google Analytics:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Country\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Gender<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Age\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Device<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Operating system\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Coming from<\/span><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">The author pulls data from Google Analytics and puts each one in a generic statement:\u00a0<\/span><\/p>\n<blockquote><p><span style=\"font-weight: 400;\">\u201cOur typical user is [age] years old [gender] from [country] on a [device type], who has found the site by [where they come from].<\/span><\/p><\/blockquote>\n<p><span style=\"font-weight: 400;\">With the data in the image below, we use the most popular brackets to create our user persona. For example, the most popular bracket is 25-34, but the 18-24 group is close behind. So, we will skew the age towards the younger end of the former bracket. Our user statements should look like:<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-810\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig1-website-personas.png?resize=866%2C482&#038;ssl=1\" alt=\"\" width=\"866\" height=\"482\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig1-website-personas.png?w=866&amp;ssl=1 866w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig1-website-personas.png?resize=300%2C167&amp;ssl=1 300w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig1-website-personas.png?resize=768%2C427&amp;ssl=1 768w\" sizes=\"auto, (max-width: 866px) 100vw, 866px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Our typical user is a <\/span><b>26<\/b><span style=\"font-weight: 400;\"> years old <\/span><b>woman <\/b><span style=\"font-weight: 400;\">from <\/span><b>the USA <\/b><span style=\"font-weight: 400;\">on a <\/span><b>windows desktop<\/b><span style=\"font-weight: 400;\">, who has found the site by <\/span><b>originally searching Google<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The author urges people to ask themselves if the user statements match the ideal customer persona. If not then how can we improve the marketing strategy? The insights are credible and can lead to multiple features, and ideas on how to position a brand.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Takeaways<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">In the blog post, the author discussed six types of data to create a personalized user statement. He argues that although creating full user personas can be difficult, a user statement can help guide the design process.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">He pulls analytics reports from different websites and uses them to create user statements and urges people to see if their user statements match their ideal users, and if not, then how to handle the situation.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">How to Design your Buyer Personas with Google Analytics<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">In <\/span><a href=\"https:\/\/blog.yourtarget.ch\/en\/how-design-buyer-personas-google-analytics\"><span style=\"font-weight: 400;\">this article<\/span><\/a><span style=\"font-weight: 400;\">, the author discussed why understanding the prospective client is important and how we can use Google Analytics to collect data and create a prospective buyer persona using that data. In the end, he discusses how to create a strategy considering your prospective buyer persona.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Recognizing your client, understanding what they need, and creating useful content at every stage can generate dialogues. The author suggests collecting the following data for persona creation with Google Analytics:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Demographics\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Interests\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Sources of traffic\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Visitor\u2019s Geolocation\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Use of website\u00a0<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Google Analytics gives you three areas to understand your clients and how they interact with your site: audience, acquisition, acquisition, and conversion. These are explained in the following.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Audience<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">In this area, you can analyze four reports: demographics, interests, geography data, and mobile devices.<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Demographics: this report show, age, and gender of the client. It tells which age bracket and man\/woman is creating the highest rate of conversion.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Interests: This report tells us three things: affinity (interests like tech, sports, etc), in-market segments (purchase interests of the users), others (custom interests added in the affinity category).<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Geographics data: gives you the locality and language spoken by the user.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Mobile device: provides the data related to how the user is connected to your website. For instance, if the device is mobile, tablet, or desktop.<\/span><\/li>\n<\/ol>\n<h3><span style=\"font-weight: 400;\">Acquisition<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">In this area, the channels used by the client to connect to your site.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Sources<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">AdWords<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Search Console<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Social\u00a0<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">The report compares the traffic to the conversion rate to evaluate which platform generates the most clients.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Behavior<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Behaviors give us reports about:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Behavior flow of the users<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Contents of the site (Session duration and rebound frequency)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Website speed<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Research related to the site<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">This report tells us about the user interaction with the website.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Conversion<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">In the conversion state, we measure:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">If the objective was achieved: for e.g. if the user got until the thank you page after filling the form<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">User\u2019s behavior on your site: sales yield, purchasing behavior<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">How users made the purchase: time from form initial interest to conversion, attributing a particular conversion to a specific channel, etc.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">By analyzing the audience, acquisition, and conversion reports, the user persona looked like (see image):<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-811\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig5-design-buyer-persona-with-GA.png?resize=868%2C283&#038;ssl=1\" alt=\"\" width=\"868\" height=\"283\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig5-design-buyer-persona-with-GA.png?w=868&amp;ssl=1 868w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig5-design-buyer-persona-with-GA.png?resize=300%2C98&amp;ssl=1 300w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/fig5-design-buyer-persona-with-GA.png?resize=768%2C250&amp;ssl=1 768w\" sizes=\"auto, (max-width: 868px) 100vw, 868px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">The prospective buyer gives us useful insights to create a strategy to share effective content. It involves social media campaigns, improving SEO, identifying pages that are abandoned the most, implementing content through videos.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This strategy is carried out in two steps. In the <\/span><b>awareness stage<\/b><span style=\"font-weight: 400;\">, the company needs to be found by the prospective buyer. In the <\/span><b>consideration stage<\/b><span style=\"font-weight: 400;\">, Anna must know that your cake designs and courses are beneficial to her.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the end, it is important to consider as much as you can before moving onto the next stage.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Takeaways<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The author explores three areas to collect data about the user, audience, acquisition, and conversion. In the audience report, the demographic data about the user is shown. Acquisition tells you how the visitor found your site, and conversion reports tell you how many visitors you converted into clients. <\/span><\/p>\n<h2><span style=\"font-weight: 400;\">How to Create User Personas with Google Analytics<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">In <\/span><a href=\"https:\/\/www.seerinteractive.com\/blog\/create-user-personas-with-ga\/\"><span style=\"font-weight: 400;\">this post<\/span><\/a><span style=\"font-weight: 400;\">, the author describes how his company (Seer) created a user persona for a credit counseling client using dimensions in the Audience section of Google Analytics.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To begin, your website should meet the following criteria:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">It has a sub-folder or keyword(s) in a group of URLs that can be identified with an audience<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">It has sufficient data on Google Analytics to analyze the subfolders or URLs<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">According to the author, the most relevant dimensions in Google Analytics for persona creation are:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Age\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Gender<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Affinity categories<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">In-market segments<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Location\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Other categories<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">These dimensions can be found in the Google Analytics menu.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dimensions in the interest section can be explained as:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><b>Affinity category:<\/b><span style=\"font-weight: 400;\"> to make the buyer aware of your brand.<\/span><\/li>\n<li style=\"font-weight: 400;\"><b>In-market segments:<\/b><span style=\"font-weight: 400;\"> which user segments are ready to purchase the product.<\/span><\/li>\n<li style=\"font-weight: 400;\"><b>Other categories: <\/b><span style=\"font-weight: 400;\">more granular categories, and identifies the users that are not in either one of the above categories i.e. affinity and in-market segment.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">We start by setting the time range from about six months to a year. Set the primary dimension to \u2018Affinity Categories\u2019 and secondary dimensions to \u2018Landing page\u2019.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The advanced filter will be set to show landing pages with the keyword \u2018student\u2019 in them.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Export the data to excel and create a pivot table using <\/span><b>Sessions <\/b><span style=\"font-weight: 400;\">and <\/span><b>Affinity Category. <\/b><span style=\"font-weight: 400;\">Eliminate the other fields and the table looks similar to the image below:<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-812\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Image-4-Pivot-Table-Set-Up.jpg?resize=833%2C524&#038;ssl=1\" alt=\"\" width=\"833\" height=\"524\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Image-4-Pivot-Table-Set-Up.jpg?w=833&amp;ssl=1 833w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Image-4-Pivot-Table-Set-Up.jpg?resize=300%2C189&amp;ssl=1 300w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Image-4-Pivot-Table-Set-Up.jpg?resize=768%2C483&amp;ssl=1 768w\" sizes=\"auto, (max-width: 833px) 100vw, 833px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">After hitting enter, the pivot table looks like:<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-813\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Image-5-Sorted-Pivot-Table.jpg?resize=589%2C211&#038;ssl=1\" alt=\"\" width=\"589\" height=\"211\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Image-5-Sorted-Pivot-Table.jpg?w=589&amp;ssl=1 589w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Image-5-Sorted-Pivot-Table.jpg?resize=300%2C107&amp;ssl=1 300w\" sizes=\"auto, (max-width: 589px) 100vw, 589px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Sort the \u2018sum of sessions\u2019 column from largest to smallest. The table gives you the most common affinities of users who visited pages related to students and student loans.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Once we have the data, the last step is to turn it into a persona that looks like this:<\/span><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-814\" src=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Student-Loan-Cited.v2.jpg?resize=735%2C573&#038;ssl=1\" alt=\"\" width=\"735\" height=\"573\" srcset=\"https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Student-Loan-Cited.v2.jpg?w=735&amp;ssl=1 735w, https:\/\/i0.wp.com\/persona.qcri.org\/blog\/wp-content\/uploads\/2020\/05\/Student-Loan-Cited.v2.jpg?resize=300%2C234&amp;ssl=1 300w\" sizes=\"auto, (max-width: 735px) 100vw, 735px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Also, as the two key interests of the student loan audience are cooking and deals, so cooking with coupons can be a great idea for a blog.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this post, the session was used as the metric but the process can go further. For instance,\u00a0 you can use purchases or specific landing page views as segmentation criteria.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Takeaways<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The author uses dimensions like age, location, and affinity to create buyer personas for a credit counseling client. He creates a pivot table with the data pulled from the Google Analytics report and creates a persona with it.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Conclusion<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">We discussed seven posts from different authors and websites where they explain the process of using Google Analytics to create personas (and in one case, user statements).\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the blog posts, the author used primary dimensions like demographics and secondary dimensions like age and gender to pull custom landing pages or session reports about the buyer or users. The information from the reports is combined to create personas that represent the dominant users\u2019 demographics, location, and interests.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Some authors also noted weaknesses when using Google Analytics for persona creation. Particularly, creating personas based solely on website analytics can take us further away from the users rather than bringing them closer. <\/span><b>It gives us the where and who but not the \u201cWhy\u201d that we are after. <\/b><span style=\"font-weight: 400;\">On the other hand, Google Analytics is important too as it presents solid quantitative data about the users of the website.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The best way to create personas is to use not just Google Analytics or any other analytics tool but explore as much data as possible, and taking time to understand the users as real people. For this, combining quantitative data from Google Analytics and qualitative data from user interviews (5-10 is enough to get a basic idea of user needs) is advisable.\u00a0<\/span><\/p>\n<p><strong>Want more information? See &#8230;<\/strong><\/p>\n<p>Jansen, B. J., Salminen, J., Jung, S.G., and Guan, K. (2021). <a href=\"https:\/\/www.morganclaypoolpublishers.com\/catalog_Orig\/product_info.php?products_id=1608\" target=\"_blank\" rel=\"noopener\"><u>Data-Driven Personas<\/u><\/a>. Synthesis Lectures on Human-Centered Informatics,1 Carroll, J. (Ed). Morgan-Claypool: San Rafael, CA., 4:1, i-317.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This post is co-authored with\u00a0Noor-ul-Anam Ruqayya, a Software engineering graduate from the University of Karachi. Noor is currently working as a content writer and digital marketer. In this post, we summarise seven articles that explain the process of creating buyer or user personas with Google Analytics. 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