Resources – Kayle Larkin https://kaylelarkin.com SEO and Analytics Services Mon, 17 Apr 2023 21:41:38 +0000 en-US hourly 1 https://wordpress.org/?v=6.4.3 https://kaylelarkin.com/wp-content/uploads/2021/11/Fav-icon-Kayle-larkin-150x150.png Resources – Kayle Larkin https://kaylelarkin.com 32 32 Get to Know Google Analytics 4: A Complete Guide https://kaylelarkin.com/get-to-know-google-analytics-4-a-complete-guide/ Mon, 17 Apr 2023 21:41:36 +0000 https://kaylelarkin.com/?p=2969 In October, Google announced the most significant change to Google Analytics ever: Google Analytics 4.

There is a lot to learn with large updates and it’s natural to wonder how this will affect your job or business.

While we’ve not heard any indication that traditional GA will be going anywhere anytime soon, new properties now default to GA4. This is a strong sign that learning Google Analytics 4 is worth prioritizing.

In this complete guide, you’ll learn everything you need to know to get started with Google Analytics 4:

  • What’s Changed.
  • Making the Switch to GA4.
  • How GA4 Helps Reporting.
  • Best Ways to Use GA4 Reports.

Google Analytics 4: What’s Changed?

In short… a lot.

GA4 uses a significantly different data structure and data collection logic.

Now, everything is built around users and events – not sessions, as we’ve been used to.

An events-based model processes each user interaction as a standalone event.

This change is significant because historically we relied on a session-based model which grouped user interactions within a given time frame.

Moving the focus from sessions to events provides major benefits to marketers such as cross-platform analysis and an enhanced capacity for pathing analysis.

By moving to an event-based model, GA4 is more flexible and better able to predict user behavior.

Should I Switch To Google Analytics 4?

This is the big question – do you need to switch to Google Analytics 4 right now?

Short answer: yes.

Set up a GA4 property to run in parallel with Universal Analytics.

Even if you don’t plan on using it right away, collecting data and strengthening your machine learning (ML) models will make future analysis more meaningful.

Better data collection = better-informed marketing strategies.

How To Set Up GA4

Configuring GA4 is as simple as a few clicks.

The analytics property you are familiar with will be left unchanged, continuing to collect data. Your UA view will continue to be accessible via the admin screen.

Here’s how to connect a new GA4 data stream to your current Universal Analytics. (If you are setting up a brand new property, refer to Google Tag Manager: A GA4 Beginner’s Guide.)

Steps For Configuring GA4

  1. Login to your Google Analytics Account.
  2. Click Admin. Gear icon, bottom left navigation.
  3. Confirm that your desired account is selected.
  4. Confirm the desired property is selected.
  5. Click GA4 Setup Assistant, the first option in the Property column.

Once inside the Setup Wizard, click the large blue button, Get Started.

Google Analytics Click GA4 Setup Assistant Screenshot.
Screenshot of GA4 Setup Wizard to get started.

There is only one more step, click the blue button to Create property.

It truly is this easy!

Screenshot of GA4 Setup Assistantto create property.

Important Note: The GA4 setup assistant works automatically with gtag.js. If you use a website builder such as WordPress, Wix, etc., you will need to add the Analytics tag yourself.

Event Tracking

After creating your property, the setup assistant will automatically activate enhanced measurement in your Google Analytics 4 property.

Custom code is still needed to track third-party elements and form submissions but the most basic forms of event tracking are automatic and ready to go.

How Does GA4 Help With Reporting?

A data collection strategy is only as strong as the information you can extract from it.

So how will switching to GA4 help with reporting?

With the push for user privacy, it’s becoming increasingly difficult to track users as they travel across multiple platforms, using multiple devices.

GA4 is a forward-thinking solution using enhanced machine learning techniques to help fill in the missing data gap. Creating a single user journey for all data linked to the same identity.

Lastly, GA4 simplified the reporting interface making it really easy for marketers to spot key trends and irregularities in data.

Instead of a long list of predefined reports that try to cover every use case, GA4 uses overview reports in summary cards. If you want to dig in deeper, simply click on the scorecard.

Best Ways To Use Google Analytics 4 Reports

This final section of getting to know Google Analytics 4 will cover the best ways to use GA4 reports.

When you first log in, you’ll see that the home page summarizes overall traffic, conversions, and revenue for that property. This is best used as a quick check to make sure everything is behaving as expected.

Your home page report will quickly answer:

  • Where do new users come from?
  • What are your top-performing campaigns?
  • Which pages and screens get the most views?
GA4 Home Page Screenshot.

Realtime Report

Realtime report is the next default report in the left navigation, and it shows events that happened within the past 30 minutes.

Use the Realtime Report to quickly:

  • Confirm tracking code is working.
  • View Effects from a YouTube Video.
  • View New Product Drop, as it happens in real time.

Cool Feature: “View User Snapshot”

Click View user snapshot in the top right corner of the Realtime report to see a literal snapshot for a single user.

This includes information about the user’s device, location, and real-time engagement with the site/app through events triggered.

Realtime report on GA4.

Life Cycle Reporting

Life Cycle reporting mirrors the funnel of acquiring, engaging, monetizing, and retaining users.

It’s ideal for analyzing how users enter the conversion funnel and how they behave once they’re in the funnel.

Life Cycle Reports will quickly answer:

  • How do users enter the conversion funnel?
  • How do users behave once they’re in the funnel?

GA4 also includes user reports on demographics and technology, as well as events and conversions.

Life Cycle Reporting Options_GA4 snapshot.

Explore Reports: Analysis

This may be the most powerful change in GA4 (or at least what I think will be the most beneficial for marketers): the new Analysis Hub.

While default reports help you monitor key business metrics, the GA4 Analysis Hub gives you access to several advanced techniques and a template gallery that isn’t available anywhere else.

Creating A New Exploration

  • Login to your Google Analytics Account.
  • Click Explore.
    • Left navigation. Icon looks like a magnifying glass with a graph arrow up.
  • Select the technique you want to use to analyze your data.
GA4 Analysis Hub Screenshot.

How To Read Explorations Reports (Previously Analysis Hub)

How to Read GA4 Analytics Hub.
  1. Return to Explorations.
  2. Variables Column: The variables column is where you will select the data you want to use in your analysis. Date range, segments, dimensions, metrics.
  3. Tab Settings Column: The tab settings column is where you will specify the analysis technique, add dimensions, metrics and apply segments.
  4. Segments: Segments are different groups of users. Drag and drop different groups of users to your report to compare and contrast how they are behaving. If you don’t see the segment you want to use, add your own by clicking on the plus icon.
  5. Dimensions: Dimensions are the things you want to analyze. For example, event count, active users, transactions, etc. Drag and drop dimensions as rows or columns in the Tab Settings area.
  6. Metrics: Metrics provide the numbers in your analysis. Add metrics to the Values area in Tab Settings.
  7. Visualization: Choose what the report will look like. Exploration options include table, pie chart, line graph, and more.
  8. Values: Drag the metrics that you want to display as columns in the report. Cell type can be displayed as a bar chart, plain text, or heat map.
  9. Tabs: Tabs display your visualizations. An analysis can contain up to 10 tabs. To add a new tab, click the plus icon.
  10. Display: Interact with the data by right-clicking a data point in the visualization.

Types Of Analysis

Exploration

GA4 Exploration provides more control over the data visualization than was previously available in Universal Analytics.

There are a ton of configuration options within exploration to help you uncover new insights and represent your data in a way that makes sense to your team or client.

One of my favorite features within exploration is anomaly detection because it automatically flags any data points that are outside of what the expected outcome was.

Funnel exploration

How do website visitors become one-time shoppers and then how do one-time shoppers become repeat customers?

Find out in the GA4 funnel analysis report. Here, you can visualize the steps shoppers take to complete an event and see how well they are succeeding or failing at each step.

Path exploration

If you liked the behavior flow reports in universal analytics, you will love the analysis hub pathing reports in GA4.

Path analysis visualizes the event stream in what is known as a “tree graph.” An event stream is the series of events users triggered along their path.

The path analysis technique helps marketers uncover looping behavior which may indicate users becoming stuck.

Segment overlap

Segments can be used in both Universal Analytics and Google Analytics 4 properties.

In GA4, segments can be used as user events or sessions. Marketers can even build segments containing multiple conditions and arrange those into a “condition group.”

Think of a segment as a specific group of your site users. For example, a segment may be users from a specific city, those who visited a specific page, or users who took a specific action such as purchasing from a particular product category.

Cohort exploration

A cohort is a group of users with a common characteristic, such as the same acquisition date, an event, or conversion.

For example, you can create a cohort report to see how long it takes people to convert in relation to a specific marketing tactic.

User lifetime

The user lifetime report is extremely powerful for search marketers because it lets you create reports that visualize which source is driving users with the highest lifetime revenue — not just revenue for a selected month.

With GA4, you can uncover the marketing campaigns that are acquiring the most valuable users, with the highest purchase probability and lowest churn probability.

This is thanks to Google Analytics predictions models.

Conclusion

An analytics tool is one of your most powerful marketing weapons. It helps develop an understanding of website traffic and how users behave once on site.

Better analytics insights = better marketing decisions.

GA4 is the analytics upgrade we all needed. It provides marketers with more flexibility and a means to predict user behavior while upholding user privacy.

Once you get through the learning curve, you’ll find GA4’s flexibility and enhanced insights are more than worth it.

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Why Google Analytics is Going Away and How to Update to GA4 https://kaylelarkin.com/why-google-analytics-is-going-away/ Wed, 16 Mar 2022 20:22:11 +0000 https://kaylelarkin.com/?p=2151

Google Analytics announced on Twitter, LinkedIn, and the GA blog that Universal Analytics will begin sunsetting next year.

UA is going away_Google Analytics twitter screenshot_Kayle Larkin GA Consultant

Beginning July 1, 2023, all standard Universal Analytics accounts will stop processing new hits.

Woah.

Sorry, there’s more. After July 1, 2023, you’ll only be able to access your previously processed data in Universal Analytics for at least six months.

 

Until today, I have recommended that business owners and marketers add GA4 even if they didn’t intend to use it – just in case Google Analytics ever decided to sunset Universal Analytics.

 

That time has come, and now it’s no longer a recommendation. Add Google Analytics 4 today.

 

When January 2024 (6 months after July 1, 2023) rolls around, you will wish you had some historical data to build strategies from.

Why is this happening

The rug has been pulled out from under your feet, but this has been brewing for the past few years. Just none of us knew what the exact solution would be.

 

Here’s a quick modern history lesson on data privacy.

Mini Data Privacy History Lesson

July 12, 2016: Privacy Shield was approved and deemed adequate to enable data transfers under EU law.

 

May 25, 2018: General Data Protection Regulation (GDPR) was drafted and passed by the European Union (EU); it is the toughest privacy and security law globally. GDPR will levy hard fines into the tens of millions of euros against those who violate its standards.

 

July 16, 2020: Court of Justice of the European Union issued a judgment declaring Privacy Shield, the mechanism used by thousands of companies to move data from the EU to the US, to be illegal.

 

August 2020: NOYB fils 101 complaints against EU companies that included Google and Facebook functions on their websites. 

 

October 14, 2020: New Google Analytics 4 is introduced. Google explains how GA4 is “built for the long term” with a new approach to data controls and user privacy. 

 

December 22, 2021: Austrian data regulator, Datenschutzbehörde said using Google Analytics on NetDoktor breached the European Union’s General Data Protection Regulation (GDPR)

 

Simply put, the EU does not want data being sent to the US at all because it isn’t properly protected against potential access by US intelligence agencies.

 

“The EDPS made it clear that even the placement of a cookie by a US provider is violating EU privacy laws. No proper protection against US surveillance was in place, even though European politicians are a known target for surveillance. We expect more such decisions on the use of US providers in the next months, as other cases are also due for a decision.” Max Schrems, Honorary Chairman of noyb. EU

 

That brings us to the marker that affects all of us using Google Analytics. 

 

March 16, 2022: Google Analytics announces they will be sunsetting (obliterating) Universal Analytics next year. 

 

July 1, 2023: All standard Universal Analytics properties will stop processing new hits.

 

October 1, 2023: 360 Universal Analytics properties will stop processing new hits.

GA4 and Data Privacy

Google Analytics 4 does not store IP addresses. This solution is necessary for the international data privacy landscape (ahem, EU) demanding greater privacy protections.

Community Response

There is an overwhelming response from the community that dislikes GA4.

 

They either can’t find the metrics and reports they have relied on for years, don’t like the new interface, or haven’t gotten started.

 

The example I use is last year (2021). Facebook updated its user interface, and there was a big uproar too. No one could operate it. No one could find what they were looking for.

 

And now, a year later – no one remembers that it ever happened or what the interface looked like before.

 

Why? Because we use Facebook every day.

Universal Analytics is Going Away

Whether we are ready or not, Universal Analytics is going away. So, you need to prioritize GA4. Learn how to set it up and familiarize yourself with the reports.

 

Or, work with a GA consultant (Hi!) who can help you design a Data Studio dashboard that is easy to use, and you won’t have to dig around in GA4.

 

The important information I want you to take away here is that you need to set up and be ready to use GA4 as your data source.

 

GA4 Resources

Link to YouTube Channel: Analytics in Minutes, where you can learn how to use GA4 for FREE.

Link to SEJ article to learn how to set up GA4.

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Why Rank Math and Google Analytics Do Not Match https://kaylelarkin.com/why-rank-math-and-google-analytics-do-not-match/ Wed, 13 Oct 2021 20:31:56 +0000 https://kaylelarkin.com/?p=899

You’re trying to figure out analytics to better understand your site traffic because you need to know if your marketing efforts are working.

As you dig in, it’s not always clear which numbers matter and it’s very confusing when numbers don’t match up.

For example, Rank Math is a popular SEO plugin. Rank Math Analytics tells us: search traffic, search impressions, total keywords, search clicks, CTR (click-through-rate) and Avg. Position. 

But when you look at Google Analytics data and Rank Math search traffic data – the numbers do not match up. Why is this?

The numbers are not matching because Rank Math measures “search traffic” acquisition by pageviews while Google Analytics measures “search traffic” acquisition by Users and Sessions.

It’s not that the numbers don’t match – it’s the pesky terminology.

So let’s dive into what these terms mean and in doing so, we will learn why the numbers don’t match.

What’s the Difference Between Users, New Users, Sessions and Pageviews?

There are many different metrics that correspond to “search traffic,” and they all mean something slightly different. The main three you will see and hear are Users, Sessions, and Page Views. 

Each of these measure “search traffic” differently:

  • Users is the number of site visitors who initiated a session during the chosen timeframe. This includes new and returning visitors.
  • New Users are site visitors who initiated a session during the chosen timeframe who have not visited the site previously according to browser cookies.
  • Sessions is looking at a grouping of user interactions (hits) that took place during the chosen timeframe. Stay with me, this term will make more sense in the upcoming example.
  • Pageviews is every time a page on your website is loaded by a User. 

It is absolutely possible that a single user will trigger multiple sessions and that a single session will trigger multiple pageviews.

Search Traffic Example

For a practical example, a desktop user clicks on your webpage in Google’s search results and reads 3 articles in your content silo then exits. This is (1) new user with (1) session. 

You were really smart and remarketed your LP for this content silo to the user’s insta (mobile) during their lunch hour and they returned. (1) new user (1) session.

That evening, the user now opens your email and clicks on the link returning for the third time to your site (mobile) and reads another well-targeted article in your beautiful content silo.

How much traffic did your website get from the organic channel?

Rank Math will display this site traffic as:

  • 3 Pageviews
    • 3 articles during initial Google search from desktop

Google Analytics will display this site traffic as:

  • 2 Users
    • 1 desktop user
    • 1 mobile user
  • 3 Sessions
    • 1 desktop session
    • 2 mobile sessions
  • 5 Pageviews
    • 3 articles during initial Google search from desktop
    • 1 landing page during return mobile visit
    • 1 article recommended in the email

Why does Rank Math Traffic not Match Google Analytics Traffic?

Google Analytics All Traffic report is the number of users or sessions by all organic traffic sources whereas Rank Math Search Traffic is the number of pageviews by visitors only from Google.

In our example, Google Analytics traffic would say search traffic was 1 meaning one user from the Organic channel. Rank Math Analytics would say search traffic was 3 meaning 3 pages were viewed by visitors from Google.

Both Rank Math and Google Analytics is correct, it just depends on what you’re looking for the data to tell you.

If you have any questions, please send me a note. Happy to help.

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Data Studio Tutorial: Interactive Google Map https://kaylelarkin.com/data-studio-tutorial-interactive-google-map/ Fri, 03 Sep 2021 20:41:24 +0000 https://kaylelarkin.com/?p=922

Aside from being a fun, engaging element to your SEO report, an interactive Google map can be used to help increase the ROAS of paid ads.

In this Data Studio tutorial you will learn how to add a Google map and drill down from a regional to city view, add organic search KPIs as optional metrics. 

How-To Add a Geochart Map

  1. Open Google Data Studio
  2. From the top navigation bar click, “Add a Chart.”
  3. There will be three maps to choose from, select “Geochart.”
  4. Dimensions: Slide the toggle that says “Drill Down” and move from country to region to city. 
  5. Our default filter down level is going to be the one that shows first on our view, so we want to start out at our furthest point, “country.”
  6. Set your metric to “New Users” or “Users.” 
  7. Slide the optional metrics toggle and add a secondary metric for “Goal Completions.” Goal completions is going to be a total number of every goal conversion that you have set up in Analytics.
  8. Set Zoom area will be “World.” 
  9. Default date range will be set to “Auto” so that it automatically updates as we interact with our date range filter for the dashboard. 
  10. Click the blue “View” button on the upper right to take a look and make sure that’s doing what we expect it to. 

Viewing a Data Studio Map

  1. Click optional metrics to select your view: new users or goal completions.
  2. Select a country of interest to drill down from country to region. 
  3. Select a region and drill down from region to city.

Video: Interactive KPI Map Data Studio SEO Dashboard Analytics in Minutes

Transcript of “Interactive KPI Map Data Studio SEO Dashboard Analytics in Minutes” video:

This piece to our organic overview is our interactive KPI map. Let’s get started. The first thing we need to do is make our page longer because we’ve run out of space. Click anywhere outside of your graphs. In the right hand navigation, “Theme and Layout,” select “Layout.” Middle of the page, select canvas size, and adjust your height to 1900. That should give us plenty of space to add our interactive map. 

At our top navigation, select “Add a Chart.” There are three maps to choose from. The bubble map by Google Maps is pretty cool but I do like the Geochart best. And then you’ll just adjust positioning to fit within your report. 

Data source is going to be from your Analytics data source. 

“Dimensions”–we’re going to click or slide the toggle that says “Drill Down” and move from country to region to city. 

Our default filter down level is going to be the one that shows first on our view, so we want to start out at our furthest point, country metrics. If this is breaking, if it’s saying invalid configuration, it’s most likely your metric. You want to use “New Users” or “Users.” Slide our optional metrics toggle and add a secondary metric for “Goal Completions.” Goal completions is going to be every goal conversion that you have set up in Analytics, like a total of those. Zoom area will be the world. Default date range will be auto so that it automatically updates as we interact with our date range. 

And let’s take a look and make sure that’s doing what we expect it to. So, we can select our optional metrics here to view new users or goal completions. We can select the country and drill down from country to region. Select a region and drill down from region to city. Now, we can see our new users or our goal completions. One more stylistic piece I’m going to show you. Select your geo map style. Instead of “Show on Hover,” we’re going to do “Always Show,” that way you don’t have to fight it, and it’s always going to be there. And that is our SEO dashboards organic overview page.

Subscribers to Analytics in Minutes get a new video every Friday. Don’t miss another tutorial to level up your SEO marketing skills, saving time and energy while achieving greater reach based on your growing knowledge of your audience and their engagement with your site.

 
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Short Tail and Long Tail Keywords in Data Studio https://kaylelarkin.com/short-tail-and-long-tail-keywords-in-data-studio-post-author-by-kaylelarkin-post-date/ Fri, 03 Sep 2021 20:40:03 +0000 https://kaylelarkin.com/?p=917

When analyzing the results of an SEO campaign it is important to separate short-tail and long-tail keywords to truly understand where the opportunity for optimization lies.

Short tail keywords are very generic and usually consist of one to two words.

Long tail keywords, depending on your brand, can use upwards to five words. You may hear them referred to as key phrases because they tend to be posed as a question or a very specific product that the user is looking for.

Because short-tail and long-tail keywords are SEO industry terms we need to tell Data Studio what we consider to be or what those two terms are defined by.

To do this, we will create a new field using a case formula in Data Studio.

How to Add a New Field Using a Case Formula in Data Studio

  1. Open Data Studio.
  2. On the right-hand navigation menu, check to see that your data source is “search console site impressions” for the desired GA account.
  3. On the far right, under “Available Fields,” scroll all the way to the bottom and click “Add a Field” and give it a name.
  4. In the Formula box, write your case query. In our example, it’s:

CASE 

WHEN query length > 4 THEN “Long tail”

ELSE “Short tail”

END

  1. Green arrow checkmark at the bottom of the formula box indicates that your formula syntax is valid. 
  2. Click “Save” and “Done.”
  3. On the right-hand navigation menu, under “Dimensions,” add the new field that you just created and named.
  4. Under “Metrics,” choose the following:
    • “Queries”
    • “Impressions”
    • “Clicks”
    • “Click-Through Rate”
    • “Position”
  5. Set “Sort” to be by clicks. 
  6. Set “Default Date Range” to “Auto.”
  7. Click the blue “View” button on the upper right to ensure the formula functions as expected and see your table showing short tail and long tail keywords reporting.

Schedule a call with SEO expert Kayle Larkin for a more customized approach to SEO analysis, and let her show you the best strategies for making the most of your Google Data Studio data.

Turn your data into usable insights that will help you identify action areas regardless of your industry or company size.  

Video: Short Tail and Long Tail Keywords Reporting a Data Studio Tutorial

You’re watching Analytics in Minutes, where we teach people how to build data studio dashboards. Today we’re going over the keyword analysis page on our SEO report. This breaks out your search queries by short tail and long tail keywords. Short tail keywords use one to two words and are very generic queries. Long tail keywords, depending on your brand, can use upwards to five words, usually posed as a question or a very specific product that the user is looking for. Here’s how to do it. 

Short tail and long tail keywords are SEO industry terms so we need to tell Data Studio what we consider to be or what those two terms are defined by. To do this, we will create a new field using a case formula. If you’ve been building an SEO dashboard along with us, you will need to add a third page to your report. Copy and paste your date range and data source controls. 

Select “Add a Chart” from the top navigation and add a table. Data source will be your search console site impressions for whichever account you’re working on. 

The far right-hand navigation– scroll to the bottom and click “Add a Field.” The name is for internal use so you can name this whatever you would like. This formula field is where you’re going to format what’s determined to be long tail or short tail. 

The formula is: case when query length is greater than– for this particular account, we determined that longer than four words was a long tail– else short tail. And once you get a green arrow check down here, that means your formula syntax is valid. So you can go ahead and click “Save” and “Done.” 

Now we can add our dimension to be that new field that we just created.

In the metrics, we want to stay consistent for our viewers, so we’re going to add “Queries,” “Impressions,” “Clicks,” “Click-Through Rate,” and “Position” or average rank. We will sort by clicks and make sure that our default date range is set to auto. 

Let’s view and make sure that that’s functioning as expected. Great, and that is how to display short tail versus long tail keywords in Data Studio.

If you’d like to know more about SEO analytics and ways to turn your data into actionable insights, subscribe to Analytics in Minutes, bite-sized weekly videos delivered by Kayle Larkin, SEO expert, that show you step-by-step how to build your own SEO tools using Google Data Studio and Google Analytics resources. 

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Data Studio Tutorial: Keywords by Position https://kaylelarkin.com/data-studio-tutorial-keywords-by-position/ Fri, 03 Sep 2021 20:36:27 +0000 https://kaylelarkin.com/?p=910

When analyzing the results of an SEO campaign, it is important to separate keywords by average position to truly understand where the opportunity for optimization lies.

In this Data Studio tutorial learn how to create a table, filter your data by the average position, and filter your data by page. Simple adjustments to tailor your reports and make informed decisions using reliable and accessible data. 

How To Display Keywords by Page Rank

  1. Open Data Studio
  2. Click “Add a Chart.”
  3. Add a table. 
  4. Data source: search console site impressions.
  5. Dimensions: Query.
  6. Metrics: Impressions, Click-through-rate (CTR).
  7. Set the rows-per-page to 5.
  8. Sort by CTR. 
  9. Default Date Range: Auto.
  10. Scroll down on the right-side navigation menu to add a table filter
  11. Edit the filter as follows:
    1. Change “Select a Field” to “Average Position.” Make sure the command is include.
    2. Name the filter “Position 1” or something similar.
    3. Check to make sure your data source is accurate.
    4.  Click “Save.”
  12. Repeat: Copy and paste the chart. 
  13. Scroll down on the right-side menu and update filter for your second table.
  14. Set the parameters to include queries with an average position between two and five.
  15. Style your tables, select select wrap text to improve the formatting of the queries in your table data.
  16. Click the blue “View” button on the upper right to see your completed tables. 

For targeted assistance in mastering your company’s keyword performance, turn to Kayle Larkin for expert SEO analysis. With insight and understanding, her approach to SEO analytics and reporting is responsive and growth-oriented.

Video: Data Studio Tutorial: How to Display Keywords by Page Rank

Keywords on page one consist of three tables showing their respective average rankings for position one, between positions two and five, and then positions six through ten. 

The scatter chart shows all keyword positions one through ten, and we made it into the same type of scatter chart that you’ll find on the keywords type page of the report. In case you missed it, I will link to that video at the end of this video. Let’s get started. 

First thing you’ll need to do is add a new page to the report we’ve been building. Let’s copy over our controls as well. We’re going to copy our data and our date range over to page 4. Great, now in our top navigation, we will add a chart, table, data source– you want to make sure you’re using the search console site impressions, and then we’ll adjust our dimension to query since we are working with queries. 

The metrics I’m going to use are “Impressions” and a click-through rate percentage so I’ll quickly be able to filter which keywords are receiving the greatest impressions and where we have some site click-through rate issues. Now that we have that set up, I’m going to set the rows per page to five, just so that’s not out of control. Pretty easy to understand, and sorting by– you can sort by “Impressions” or I choose “Click-Through Rate” so that I can quickly see what’s working really well and what needs some additional help. “Default Date Range”– you want that to stay auto so that when you adjust your date range, it’ll automatically update your table. 

And then we’ll come down here. We need to add a table filter so that we’re only showing the queries that are hitting the average rank that we want. Name it something like Position One. Ensure that the data source is matching. So the search console site impressions– you’ll click to include Average Position because we want to filter to the queries that just have the average position equal to one. Go ahead and click “Save.” 

Let’s do this one more time and adjust our average position range. 

Let’s go ahead and copy and paste your chart, and now we’re going to scroll down here and update our table filter. Instead of position one I’m going to do positions two through five. So now we’re going to include queries with an average position between two and five. 

We can even do this one last time so that you get the full thing. We’re going to need to add some stylistic elements so select your graph across the board, and we can come down here in our style to wrap text. And that will make that bit nicer for us. Now let’s check our date range and just make sure it’s working the way we expect it to.

With quick and simple instructions, Analytics in Minutes offers busy professionals a convenient way to improve their SEO analytics skills.

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Measure SEO Success with Google Data Studio https://kaylelarkin.com/measure-seo-success-with-google-data-studio/ Sun, 13 Jun 2021 21:27:05 +0000 https://kaylelarkin.com/?p=1029

Your company will naturally feel and see the results of a well-designed SEO campaign through the increase in leads and social chatter.

Being able to quantify that feeling into visually compelling data instills trust and allows for greater flexibility with future campaigns.

Here’s how to measure SEO success with Google Data Studio.

Define Success

There needs to be a clear, measurable goal.

What defines SEO success for every company is going to differ however there are a few solid KPIs that most service based businesses focus on:

  • Lead generation.
  • Customer engagement.
  • Brand visibility.

This article is going to focus on lead generation because ultimately that is what makes money.

Setting Up Goals

Lead Generation

Now that you have defined your content’s key performance indicators – or what you determine to be a success – we need to record those goal completions.

Our team prefers to use a combination of Google Analytics, Google Tag Manager and Data Studio to create interactive reports anyone can view at any time.

To measure lead generation, you must set up a custom goal for each successfully submitted form.

The most obvious method to collect data is a unique thank you page for a unique form fill.

Google Analytics does a great job explaining how to set up destination tracking in this documentation

Creating a New Goal in Google Analytics

  1. Sign in to Google Analytics.
  2. Click Admin.
  3. Navigate to the desired View:
    • Should be filtering out company IPs here.
  4. In the VIEW column, click Goals.
  5. Click + NEW GOAL
  6. Select Custom from the list of options.
  7. Click Next Step.
  8. Select the goal Type: Destination.
  9. Destination: Equals to “/campaignname_thankyou”
    • Edit this to your campaign’s unique thank you page.
  10. Value: Assign a monetary value for how much each lead is worth.
  11. Click Save.

Google Tag Manager can be used to measure more complicated touchpoints, like call schedulers or when destination tracking is not possible.

Visualize the Data

Visualize the data with Google Data Studio, this is a free tool available by Google that is easy to use, customize and share.

Because we have laid out conversion tracking in the previous steps, we can now turn this hard data into an appealing interactive report that team members can access 24/7.

Making the hard-earned increase in organic brand visibility, user engagement, and/or leads generated easy to convey and understand.

Sample Data Studio Campaign Report: this image uses sample data to protect the privacy of our partners.

This tip is going to stay focused on proving the ROI of an SEO campaign. So, lead generation. 

The full step-by-step guide including Brand Visibility and Organic Audience Engagement metrics is available in the full article posted on SEJ.

Bottom left table is where our previous work setting up goals (KPIs) in Google Analytics and assigning values comes into play.

The lead generation table displays:

  • How many users are navigating to the new content pages.
  • How many goals are completed per page.
  • What the monetary value of that content campaign is.

Note: If this is not new content you will be notating the difference in goals and page/goal value after edits are made.

lead gen by landing page report in a data studio tableLead Generation by Landing Page Table: This image uses Sample Data provided by Google to protect the privacy of our partners.

It gets even cooler when you start adding MCF assisted conversions to show which LPs have contributed to all conversions.

SEO Return on Investment

ROI for search engine optimization seems hard because value of edits and new campaigns can stretch over months and the leads generated continue long after.

I promise it’s a lot easier than you think. The key is to work with your client or partner to not only define goals but assign a value to that goal. 

As an SEO provider, your work should be organized with a planned strategy. Roll out your edits in bundles and measure the monetary effect.

Do not work through a “checklist” and throw darts at a wall until something sticks. Understand what will stick, know the probability and risk, before spending a client’s money.

Return on investment is calculated by dividing the goal value by your SEO costs + project management: strategy, developers, editors, management, etc.

SEO Investment

First, you need to know the cost of your investment. Add up the expense for each step involved in creating, launching, and reporting on an SEO campaign.

For example:

  • $1,500 site audit
  • $1,500 campaign #1 strategy
  • $3,500 strategy implementation
  • $500 custom reporting

Total SEO Investment = $7,000 for Campaign 1

Now, let’s calculate the return.

Return on SEO

Jot down the average percent of leads (or downloads) that turn into a sale. And, what the lifetime value of that partnership is.

In other words, what is the average consumer’s profit margin over the course of their relationship with your company?

Number of Customers Example:

  • Campaign average monthly traffic: 5,000
  • Conversion rate to lead: 2%
    • 100 leads
  • Closing conversion rate (lead to sale): 2%
  • Customers attributed to the campaign per month: 2

Customer Lifetime Value Example:

  • Average customer contract is $90,000
  • X average duration (3 years) = $270,000
  • Profit margin per client is 15%
  • Average customer lifetime value is $40,500

Projected Profit:

  • CLV x # of new customers = $81,000

SEO ROI Formula

Search Engine Optimization ROI can be calculated by multiplying customer lifetime value by the number of new customers per month minus cost of investment divided by cost of investment.

Example Continued:

($40,500 x 2) – $7,000 / $7,000

($81,000 – $7,000) / $7,000

$71,000 / $7,000 = 10.14

The ROI for SEO Campaign 1 example is 1,014.28%.

If you are making edits that affect pages that are currently live on the site, be sure to calculate the ROI of these pages before and after your edits so you can show the % lift.

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Data Studio Tutorial: Branded vs Generic Regex https://kaylelarkin.com/data-studio-tutorial-branded-vs-generic-regex/ Fri, 16 Apr 2021 20:42:56 +0000 https://kaylelarkin.com/?p=930

When analyzing the results of an SEO campaign, it is important to separate branded and generic (non-branded) keywords to truly understand performance and where the opportunity for optimization lies. 

By visualizing this data, you can improve your SEO marketing methods and balance them to capture the greatest number of customers. 

In this step-by-step tutorial for separating brand vs non-branded keywords in Google Data Studio, you’ll learn how to add a second page to your Data Studio report and include a table. Learn how to create a new field and master the REGEXP formula for branded vs. generic keywords as part of Analytics in Minutes’ series on building the Ultimate Search Console Report for SEO marketing. 

Or, skip ahead to the branded vs generic video and learn in under 3 minutes.

How-To Display Branded vs Generic Keywords in Data Studio

A brand vs generic page in Google Data Studio separates search queries into two segments: branded terms, which are search terms that include your brand name, and generic terms, which are search terms that do not include the brand name.

Here’s how to do it.

  1. Open Google Data Studio
  2. Click “Add a Page” in the top left corner.
  3. Click “Add a Chart” in the top navigation bar and add a table to the page.

Now we need to build our data source using the menu options on the right side of the page.

Make sure you set Data Source to “Site Impressions.” The Search Console_Site Impressions data source includes the field “average position.”

You can imagine “average position” is important to visualizing how a website is ranking for branded and nonbranded search queries.

Creating a Custom Field in Data Studio

To get a branded vs generic dimension, you will need to create a custom field in data studio.

  1. Click “Add a Field” on the bottom right of your screen.

This will bring up a half-screen where you’ll be able to adjust your query in the formula box.  

  1. Name your field.

Field name is for internal purposes, name it something that’s going to make sense for you and your team.

  1. Type in the regex formula:
Branded vs Generic Keywords Regex for Data Studio Reporting

A green check mark will appear in the bottom left when the formula syntax is valid.

  1. Click Save.
  1. Click the blue “Done” button.

New calculated option will display under “Fields” in the right-hand menu.

  1. Select your brand vs nonbranded custom field as your dimension.
  2. Edit display title for your “Dimension.”
  3. Select Metrics:
    • Query
    • Impressions
    • Clicks
    • Site- CTR
    • Avg. Position
  4. Click – Hold – Drag the vertical blue lines to align table.

That’s it! Click the blue “View” button in the upper right-hand corner to see the finished result.

Check out more data studio tutorials by Analytics in Minutes.

Video Transcript: Brand vs NonBranded Keywords

Now we will move on to brand vs generic. What the brand vs generic page does is separates the search queries from branded terms, terms that include your brand name and generic terms, and terms that do not include the brand name. Let’s get started. 

First thing you’ll want to do is, in the top left corner, click “Add A Page.” And then add your table, which is found underneath. Add a chart. Now we need to build our data source. Make sure you have “Site Impressions” selected. This will give you the available fields of average position so you can see now the ranking for branded and generic terms.

You will need to create a new field in order to get our dimension of branded vs generic. So our formula is going to be a regular expression: case when match. Going to be adjusting my query. And then here you will include all variations of your brand: brand name and separate. Here we are, and you’ll get this green check mark down here when the formula syntax is valid. And then name your field. Name it something that’s going to for internal purposes that will make sense for you, and click “Save.” 

You will see this calculated field now as an option underneath your fields so you can create your “Dimension”. You’ll want to edit the title because that’s what your header up here is going to be. And then our metrics. We want to know how many are indexed on google, so “Query,” then “Impressions,” “Clicks,” “Site click-through rate,” and “Average position.” Again, this vertical dotted blue line–you can adjust so that you get your full chart. So that’s the end of step one for the branded first generic page of our SEO report.

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Google Analytics Help

Schedule a meeting with Kayle Larkin to view Data Studio reporting options or discuss how analytics can power your search engine marketing strategy.

 
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How to Recapture Lost Customers using Cohort Analysis Report https://kaylelarkin.com/how-to-recapture-lost-customers-using-cohort-analysis-report/ Fri, 05 Mar 2021 22:04:45 +0000 https://kaylelarkin.com/?p=971

To make the most of your marketing efforts, it’s important to understand your customers’ behavior when and how they disengage with your product or service.

In this step-by-step tutorial you will learn a reliable way to identify when customers step away from your company and the best times to reach out for maximum re-engagement.

Kayle Larkin walks you through setting up a group or cohort analysis using Google Analytics as a quick and efficient way to dig deeper into your customers’ actions.

Gain a big-picture view of behavior overall or drill down by business quarter or geographic location to see how segments of customers differ in their behavior. 

Make small adjustments to the settings on your reports to compare among groups.

Google Analytics’ charts and graphs make it easy to visualize trends while also giving you the numerical data needed for in-depth views and tracking.

Using these insights, you can reach out to customers with marketing efforts targeted toward their needs, such as a discount offer or an announcement of newly arrived products or services since their last visit.

Because these outreach efforts are tailored according to customer behavior, they provide a more strategic approach to recapturing customers and their potential purchases.

In addition, using cohort analysis shows roughly how many new customers are needed over a given time period to sustain a business, given the rate of disengagement for that same time period.

How-To Put Together Your Cohort Analysis

Preparing a cohort analysis is simple because Google Analytics offers this as a prepared report function on the user dashboard.

Get the most out of the report by tailoring it to your specific needs. 

  1. Log in to Google Analytics
  2. Select the Audience icon Google Analytics Audience Icon from the menu on the left side of your screen. 
  3. Select Cohort Analysis
  4. Along the top of the Cohort Analysis tab, you’ll see places to set limits and choose metrics like cohort type and date range.
  5. Make your choices based on what kind of questions you want answers to. 
  6. If you want to use segmented markets and haven’t already set them up, create a new segment using the “Create Menu” above the Cohort Analysis tab.
  7. Otherwise, choose, “cohort size,” so you can look at the weekly cohorts.
  8. Use the chart located below the timeline to review the weekly cohort report.
  9. Look for important trends, like where customers drop off. Is it after week one? Week three?
  10. Does customer behavior vary by location, such as the United States or Canada? Use these details to build a strategy for recapturing these customers.

Use your cohort analysis to drive marketing decisions based on data instead of guesswork.

Keep track of previous reports and monitor changes in the data over time to assess the success of your marketing efforts and determine where you can make improvements.

Schedule a call with Kayle Larkin today and explore the best ways to use your Google Analytics insights and data to drive more effective marketing strategies for maximum conversion. 

Video: Recapturing Lost Customers using Cohort Analysis Report

Transcript of “Recapturing Lost Customers using Cohort Analysis Report” video: 

What if you knew the exact moment how and which users tend to disengage with your product? You could set up an email or remarketing campaign to recapture those lost users with a discount or showcasing new products that have been added since the last time they made a purchase. This information is available right now in Google Analytics. All you have to do is set up a cohort analysis report. Here’s how to do it. 

Navigate to the Audience icon in Google Analytics. Select “Cohort Analysis.” And here’s where you will set your dimensions and metrics. This will vary depending on what you’re trying to achieve or what you’re wanting to look at. 

For example, third quarter data is showing an increase in transactions, which is great news, but what happens when we examine the weekly cohorts per market during this period? Up here at the top, you can see that I’ve already segmented my markets. If you don’t have these pre-programmed, you can create a new segment here. Cohort size — we want to look at the weekly cohorts. We’re looking at the total revenue generated and the last 12 weeks or the third third quarter, in this case. My top metrics here going to be for the United States and then followed by Canada. 

So to read the cohort analysis report, you may see that while transactions increased overall, revenues declined in week one and then completely drop off for the most part here in week three. So now we know we need to re-engage users in week one, probably with a discount, and in week three, showing them new products that have been added or new products that they may be interested in before they drop off completely. If we’re unable to recapture these lost customers, we know that in order to maintain the level of growth you want as a company, you need to acquire new users every three weeks. 

Here in Canada, we see after that very first week, we lose them completely so we need to recapture in that very first week or otherwise in Canada, in comparison to the US, we have to be gaining new customers every single week.

Learn real-world practices through step-by-step tutorials you can put to use right away and discover fresh ways to engage with your customers and expand your reach.

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How Many Pages and Keywords are Indexed? https://kaylelarkin.com/how-many-pages-and-keywords-are-indexed/ Fri, 05 Mar 2021 22:03:24 +0000 https://kaylelarkin.com/?p=966

Data Studio is a powerful, user-friendly Google tool that allows you to build custom digital marketing reports with ease.

Get a reliable and easy-to-read snapshot of indexed pages on Google and indexed keywords on Google over time.

View useful information about how well your marketing efforts are performing and discover areas where improvements can be made.

By setting up a one-time template, running these reports for yourself or your clients on a regular basis becomes quick and efficient while enabling data-driven decision-making. 

In part one of this tutorial, Kayle Larkin shows you how to add Google Search and Search Console data sources to Data Studio for a quick look at how many pages you have indexed on Google, how many keywords are indexed, and how that data is trending.

Learn to add scorecards and a time series line chart to make the data and trends clearly visible. And see how Kayle Larkin uses data control as a time-saving tip. 

How-To Prepare a Data Studio Report

Preparing a new Data Studio report takes just minutes. This example features Google Analytics and Search Console data for pages and keyword indexing but once you understand the process, you can easily adapt it to build additional reports that are specific to your needs. 

Building an SEO Dashboard in Data Studio

  1. Open a new Data Studio report. 
  2. Click “Add Data” at the top of the navigation bar for this report.
    • This will bring up a box where you can scroll through available data sources.
    • Roughly 20 of the options are for Google tools; Data Studio works with more than 300 additional partner connectors.
  3. Select the accounts and properties of the account you want to use.
    • Repeat this process to add more than one data source.
    • In this video example, we’re going to add Search Console and Google Analytics.
  4. Name each data set something unique to make it easier to distinguish what you’re looking at: site data, search impressions from Search Console, and URL impressions from Search Console. 
  5. Come back to the main page of your new report.

Next, we will add a quick visual representation of how many keywords are ranking on Google and how many pages are indexed.

How to Add Scorecards to Data Studio

  1. Click “Add a Chart,” and then “Add Scorecard.”
    • In the menu on the right, you can reformat the scorecards.
  2. Under Metric, select “Landing Page” and “Count Distinct.”
  3. Repeat “Add a Chart” and “Add Scorecard,” and under Metric, select “Query.”
  4. In our video example, we can see that we have 43 pages indexed on Google and 395 keywords.
  5. You can click on the text of the scorecard to edit it; in our example, we use Pages on Google, and Keywords. 
  6. Use the mouse to slide around the position of the scorecards as needed.
  7. The report has a grid lines feature that allows you to align the scorecards precisely; you’ll see those grid lines show up as you hold down and move the scorecard.
  8. The scorecard will show the results of the datasets you previously chose. 

And now you can create a chart to see how these metrics have changed over time.

How to Add a Time Series Chart

  1. Click “Add a Chart” and then “Time Series Chart”.
  2. Drag the perimeters of the chart to fill as much of the page as you want.
  3. Change the type of date to month/year using Default Date Range settings on the right-side menus.
    • There are custom and advanced settings here that allow you to tailor the report.
    • It’s recommended that you use the previous 12 months for clarity and consistency over time, although you can adjust the date range to your needs. 
  4. Now, looking at your report, the metrics you’ve selected will be represented by lines on the chart.
  5. Use the style selections on the right to separate the lines, making them easier to distinguish.
  6. Place series one along the left axis and series two along the right to give each the appropriate series numbers.

Adding a Data Control to Save Time

Click “Add a Data Control” at the top navigation bar so you don’t have to recreate the report for every single one of your clients.

You can just click the data control box at the upper left of the report to select whichever other client you want to view here, and their data will automatically populate the chart. 

Book a call with Kayle Larkin today and learn how Google Data Studio can transform your understanding of your site’s traffic and performance to boost your marketing success and drive performance-led decisions. 

Video: How Many Pages and Keywords are Indexed? SEO Data Studio Report Tutorial 

Transcript of “How Many Pages and Keywords are Indexed? SEO Data Studio Report Tutorial” video: 

Today, I’ll show you the first piece of the all-in-one search console or SEO reporting dashboard: how many pages you have indexed on google, how many keywords are indexed, and then how that has performed over time.

The first thing to do when you open up a new Data Studio report is you’re going to need to add your data. So here we’re going to click “Add Data” for this report. 

We’re going to be using primarily Search Console but also Google Analytics, so we’re going to select our sources here. Not quite done yet… let’s add more data sources. There’s Search Console, and we’ll need to add the site impression and the URL impression. 

And I’m actually going to go into our “Manage Data Sources” here so that we can name these and not get confused in the future. And name this one… was the “site impression”. So let’s see, for Search Console one, we’ll add one more data source–the URL impression. Make sure your property perimeter is the same and we’ll edit this one to have “URL impression.” Done. 

Now we need these little boxes–here are scorecards. We will “Add Scorecard.” And this is going to be a landing page but we’re going to reformat it to be “Count Distinct”–yes–and then we’ll do one more but now instead of “landing page,” we’ll have “query” so we can see that we have 43 pages indexed on Google and 395 keywords… Just going to name this “Pages on Google keywords”. 

And the other thing we want to do is create a chart to see how this has changed over time. 

Now we’ll add a time series chart. And we’re working with the data source URL impressions from Search Console. “Dimensions,” change date but we’re going to change the type of date to probably month/year and our default date range. We’re going to create “Custom” and come down here to “Advanced.”

We want to see the last 12 months. If you do just the last year, you’re going to run into problems when the year changes over, and you want to look at the previous month because if you do just the day before, then your charts are going to look funky until the end of the month and may worry some clients. And then this we want to be…

The metric is going to be what is shown in our line here–query–and our secondary metric will be landing pages. Now we need to separate the lines here so that this flows a little bit nicer.

Series one we have on the left axis and series two, the landing page, we’re going to change to the right axis so that we get that varying flows with their own appropriate series numbers. Let’s see, yes–and if you wanted to, you can add a data control here so you don’t have to change for every single one of your clients. You can just choose whichever other client you want to view here.

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These tutorials guide you through the process of gathering and presenting important metrics in ways that offer new insights built on actionable analysis.

 
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