Using reverse engineering, an International education organization in Shanghai was able to rise to the first position in Google’s carousel growing its brand visibility by 80% YoY.

Background

An inbound marketing team was frustrated that despite following best practices their client’s were not included in Google’s carousel.

The carousel is a feature that appears at the very top of Google search results page for certain queries in a list-like rotating image display.

Because of how this feature influences brand visibility and search queries for educational organizations, it is imperative to be included. 

The Solution

By analyzing the school profiles for those displaying we were able to find a pattern between: 

• Wikipedia infobox
• Wikipedia categories
• Google knowledge graph card
• Google My Business listing

Once each of the above were aligned the educational institution became the top position in the carousel within 24 hours. 

2020 was a year unlike any other in ecommerce—the global coronavirus pandemic changing so many aspects of business. One of which being consumer behavior.  

An outdoor recreation equipment company had been doing exceptionally well with organic traffic at the beginning of the pandemic – until heavy hitter brands encroached in their niche. 

Visibility and sales were plummeting in the months leading up to the Holiday shopping season. 

When the online retailer needed to shift strategy quickly, they sought out an SEM partner with a track record of success and ability to right the ship quickly.

The Solution

A thorough audit of Analytics, Ads, Social, and Sales was conducted. 

Once the initial audit was complete, I began with quick fixes: correcting attribution to clean up data and tightening in the targeting to stop unnecessary spend. 

Quick fixes are minor adjustments to the Ad Account and Campaign settings that ensure greater control of where Ads are placed. 

Reviewing time lag and path length reports in Analytics increases the efficacy of attribution models. Better data means you can make better marketing decisions. 

Applying audience segments by targeting interests, age/gender and geolocation set up Ads to show only to users most likely to make a purchase.

Behavior flow charts provided insight into the ad language, extensions, and landing pages buyers were most interested in. 

Once these Ads ran for 7 days – or collected a minimum of 50 sales – we moved manual CPC bidding to ROAS bidding.

The last step, likely the most crucial step, to maximizing the return on ad spend is to carefully monitor actual search queries daily and respond appropriately.

Axe anything that does not serve you.

Brands tend to hang on to keywords that they want to work; even though historically it doesn’t serve them. 

Utilizing historical data to inform this Ad Campaign is the main reason it was able to generate $65K with a $3K Ad Spend. 

This wasn’t a one time fluke either. This Brand has consistently hit close to – and more often than not – over 1,000% ROAS month-over-month. 

Here’s a snapshot of results from when I first stepped in to manage this company’s Google Ads up until mid-March 2021. 

What is next?

With this level of success, naturally you want to continue striking while the iron is hot. So back to the data I went.

Ah-ha, search engines in Microsoft Ads network have less users but a much higher ecom CVR than Google. 

Our strategy is now extending ad campaigns to target more high-intent buyers and I very much look forward to sharing Microsoft Ads results with you.

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.

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

10. Green arrow checkmark at the bottom of the formula box indicates that your formula syntax is valid. 
11. Click “Save” and “Done.”
12. On the right-hand navigation menu, under “Dimensions,” add the new field that you just created and named.
13. Under “Metrics,” choose the following:
    • “Queries”
    • “Impressions”
    • “Clicks”
    • “Click-Through Rate”
    • “Position”
14. Set “Sort” to be by clicks. 
15. Set “Default Date Range” to “Auto.”
16. 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.