In June 2022, the Moz team released The Professional's Guide to SEO — a resource to help level-up anyone comfortable with the basics of SEO, who have some experience practicing it professionally, and who crave the challenge and reward of moving from intermediacy toward mastery.
And now, we're excited to announce a series of bonus chapters for different SEO niches, that will be added to the core guide over the next few months!
Managing the on- and off-page optimization tasks for a large business's website (or websites) is only part of the battle for enterprise-level SEOs. In order for your SEO tactics to be successful, you also need to consider the bigger operational and interdepartmental workflows and priorities that will come into play. With all that in mind, this chapter will help you:
Break silos and create a culture of SEO
Scale your SEO efforts
Use SEO to bolster your brand
Develop meaningful content at the enterprise level
Improve your link acquisition strategies
Who should read this chapter?
If you're an in-house or agency SEO that works for or with large businesses (think Fortune 1000), or large websites with thousands of pages (like travel and listings sites) this chapter is for you!
Ready to learn?
Level-up your enterprise SEO with this bonus chapter to the Professional’s Guide to SEO! Use the tips in this chapter as a guideline when you need to scale up your efforts, and be sure to check out the rest of the guide for more expert SEO advice.
Estimating the opportunities within your various SEO efforts is an important component of your analytics, not only to help determine where to focus your energy, but also to prove the potential value of your work to others. Building on the recent post about Aira’s new keyword estimation worksheet, in today’s episode, Robin walks you through a good strategy for this all-important estimative work.
Click on the whiteboard image above to open a high resolution version in a new tab!
Video Transcription
Good evening, good afternoon, and good morning wherever you happen to be in the world. My name is Robin Lord. I work for a digital marketing agency called Aira here in the UK. I'm going to be talking to you about estimating opportunities with different searches. Now, it's really important that we're able to estimate opportunity because it gives us a way to talk about how valuable our projects are to other people and it helps us to figure out where we should be focusing our energies.
So being able to know how much opportunity we might get in different places is pretty crucial. So we're going to start with the most basic way of approaching that, and then we're going to work our way up to a slightly more complex, slightly more nuanced approach.
Number of keywords you're targeting
But to begin with, the kinds of things that we have, when we start to estimate opportunity with different searches, are usually the number of keywords that we want to target, for example here's one "setting up a business," and the search volume that we have for those keywords.
So here in this case, "setting up a business" we think is searched about 6,500 times a month. So 6,500 times a month someone is searching for "setting up a business." Now, we're not going to assume that every single one of those is going to come straight to our website. We're not assuming that we could get 6,500 clicks straight to our website. We get an idea that probably most people are going to click position one, but some people are going to click position two, and some people are going to click position three and position four, and so on and so on.
So even if we were in the best possible position, we can't be everywhere. So we can't just assume we're going to get that 6,500 clicks through to our website.
Click-through rate curve
The way that we start to handle that is by using something called a click-through rate curve, which, if you haven't encountered it before, looks roughly like this. You can probably see why it's called a click-through rate curve.
Here we've got the curve. We've got all of our positions, 1 through 10 here at the bottom, and the side is how likely we think someone is to click through to our site. So the easiest way to kind of visualize it is in a graph. But what we usually have is in a table so that we can use something like a VLOOKUP. If we are saying position one, then we know that our click-through rate for that is probably going to be about 35%.
So we use that to estimate what we could get out of this search for position one. Likewise, if we're looking at like position eight, we might say our click-through rate for that is more like 5%. So if we're in position eight, that's kind of what we assume we're going to be able to get out of it. We use that in a formula kind of like this one. So we say the search volume, so how many how many times something is being searched here at the top, multiplied by the click-through rate is how many clicks we expect to get.
So in this case, 6,500 is our search volume. Thirty-five percent for position one gets us about 2,300 clicks a month or 27,000 clicks a year. You can see here I've hidden up here you can kind of mark it here at this line just to visualize it for you.
That's kind of what we're doing here. We're assuming position one will get us this kind of click-through rate, and that would result in about 27,000 clicks a year for this search term.
Factor in current rankings
Now, we could stop there, and some people would stop there, in terms of, okay, well, I'm going to assume I can get position one for every keyword and I'm just going to multiply it out to make sure that I'm not making wild predictions about how much traffic I might be able to get.
But that's the way I'm going to leave it. That can give you a slightly more accurate estimate, but it's not factoring in times when we might already be ranking a bit for a keyword. So say, for example, we are already ranking position eight for this specific search. Now we can see here, position eight is already getting some clicks.
So if we if we move up to position one, sure, we're going to get more than we're currently getting, but we're not going to get 27,000 clicks more than we're currently getting. We're going to get a bit more than we're currently getting. But we need to factor that in because there could be other searches, for example, that have smaller search volume, but we're not ranking at all. So the opportunity for us is bigger, because really what we want to focus on is how much more could we get than we're currently getting at the moment.
The math
So how could we handle that? Well, fortunately, the math around that is actually fairly simple. It's exactly the same sum as we've done here.
We just need to look at position eight, figure out what our click-through rate is for position eight, and then do that same sum to figure out how much we could get. Now in this case, 5% gives us 325 clicks a month, about 4,000 clicks a year.
So we're getting 4,000 clicks a year at the moment. We could get 27,000 clicks a year. So we just subtract what we're currently getting, and we say, okay, we've got an opportunity here of about 23,000 clicks a year. So that's starting to get us a bit more of a nuanced idea of what our opportunity is in different places, because we're not going to keep pouring energy into something we're currently doing kind of well for, and we can start to focus on the areas where there's kind of untapped growth there.
How about we push things a little bit further still? So we've got this understanding of of how much we could get if we got to position one. Say for this search position one is a government website, and position two is Amazon, and position three is Google. Now, Google, once it has a government website, once it decides a government website is quite relevant, doesn't really like to replace that because they tend to be very trustworthy and they tend to have pretty good information.
Also, it doesn't really like to replace Amazon by and large because Amazon tends to be a great result for a whole bunch of different things. Particularly it doesn't like to replace itself. So if we're starting to think about what we could get for this keyword and we're assuming we could get position one is 35% click-through rate, we might look at some of these results and think, well, actually I don't think I can get up here.
I think we should probably be looking a little bit further down. So maybe we look at something like position fifth or fourth. Say position four is a page about how to start a business. Position five is Wikipedia. Position six is someone offering to sell a service, so that you can buy a business setup.
Seven is 50% off a business setup. So again, offering to sell, but they've got that cheeky 50% discount that you can benefit from. So if we look at all of this, we might start to think, okay, well, I don't think I can reach position one, probably not position two, probably not position three. Actually, I think I probably don't want to assume I can replace Wikipedia here either in position five.
So the best position that I'm looking at here is actually position four. So I should go back to some of my click-through rate estimates. I should estimate based on position four, rather than position one, and then use that to get an idea of the total opportunity we could get for this keyword.
How to do this
Now, you could be wondering how you might do this. Actually, there's a bunch of tools that will give you the full top 20 export for a whole list of keywords. The first time I did this, I used the STAT top 20 export, and I just exported everything and I dumped it into a Google Sheet. So I ended up with all of my keywords and all of the top 20 results row after row after row after row on my sheet.
Then I used a formula, a pretty simple formula to just find any websites that we thought we wouldn't be able to beat. I used that to mark those rows any time we thought we wouldn't be able to beat, and then I just deleted those rows. So I ended up with each of my keywords I only had the ranking positions that we thought we were actually able to achieve.
So in this case, four, six, seven, and eight, which we are currently. Then I just found the highest position that we could get in that list for each keyword, and I used that with my click-through rate curve to try and estimate how much traffic we might be able to get. So this all really boiled down to like IF formulas and VLOOKUPs. So it's very accessible for anyone who wants to get involved in this kind of thing.
Get fancy with it
Now, we could leave it there. That would give us a pretty solid understanding of where we might be able to get, and it's far more nuanced than the picture that we might get at first blush. If you want to get a bit more fancy with it, there's other information that you could pull in to your analysis.
So say, for example, you're able to pull in the titles of all of the pages that are currently ranking. Say in position four, it's how to start a business, and position six, it's buy a business setup, and position seven, it's 50% off a business setup. Again, if we look at these, we could use some fairly simple formulas, even just in Google Sheets, to try to categorize these into different intents. So "how to" is fairly clearly an informational search, an informational result rather. So we're not trying to categorize the search.
We're trying to categorize the individual results. "Buy" is a fairly clear purchase search, and "50% off" again suggests that it's trying to sell us something. So if we start to look at these results, we can filter them down even more if we want to. So say, for example, we're working on a site and we know it has to be a product page. If we're going to target this term, we have to use a product page.
Well, we could do that same filtering process, except this time we're marking anything where the title is something like how to or top tips or instructions how to, or anything that seems like a blog post, and we remove them as well. So we say, actually, we couldn't get this either. This is the highest we could get with this product page.
If we do that across all of our keywords, we know that we have to use product pages. We're saying, okay, for this, we're position six. Well, say position six actually has a pretty low click-through rate. If we're looking at position six for this keyword, we're already at position eight. So maybe the opportunity that we've got for this keyword is actually pretty small, and we decide that we want to focus on other things.
So that's another quick way to filter all of our different opportunities by just removing the kind of results that we wouldn't want to compete with. Alternatively, if we don't already have an idea that it's got to be a product page, we could go through all of our searches and say we know that it's going to be position four is the best place that we could get.
We can use that same category, we can use that same categorization formula to say, well, position four looks like it's informational. So as we're identifying our opportunities, we can quite quickly say when we go to do a content brief for this, for example, this needs to be a blog post. It shouldn't be an update to a product page.
What's the goal?
Now, the aim for any of this isn't to make people's decisions for them. We're never going to just send this sheet, for example, off to someone and not have an SEO professional look at it. But it means that instead of spending lots of time having to reverse engineer, having to think really hard about all these different things and pull information into one place, we have a starting point for people to go from.
So when we have someone who's an expert at SEO looking at this, they've got all of the information in front of them to begin with. That's actually the approach that we tend to take in general in Aira. So when we do this kind of work, we actually tend to use a Python script, and that script pulls in all of the top 20 results. It also categorizes those search results, the individual results rather than the search term itself, based on whether they seem informational or transactional.
It finds that opportunity. It finds that highest place that we can currently get and subtracts where we're ranking at the moment. That means that we end up with a sheet where we can order things quite nicely based on highest opportunity to lowest opportunity and categorize them based on what kind of results they are.
We also pull in some other things like authority, which is one thing that you could also use to filter down your results if you're starting to dig into this. We also use the search results to see how similar different searches are as a way of clustering them. So those are some other things that you can dig into once you get familiar with these kinds of concepts and really start to accelerate. Now, you don't have to go that far.
You could do any step along this route and get a little closer to a nuanced understanding of what this search result can get you, and that's going to be a really positive advancement because the more that we can bring in this nuance, the more quickly we're able to identify these different things. All of these are decisions that you're going to be making anyway. You're already a smart SEO professional.
You're already going to know all this information. It's about speeding up your path to that answer. Anyway, thanks very much for listening to me. I really enjoyed chatting this through with you. I hope you've enjoyed it as well, and I'll look forward to hearing your thoughts. Thanks a lot.
Link research is an essential pillar of an SEO strategy, but competitive link research can help you get a leg up. It’s vital for websites to not only know about their own link profile, but to also have an effective strategy in place to stay relevant against competitors.
Hopefully at this point, you know who your competitors are, and hey, that’s half the battle. If you still aren’t sure, check out our Competitive Research tool in Moz Pro. This tool can help you find out exactly who your competitors are, the keywords they rank for and what their top performing content is.
If you would like to understand our Competitive Research tool more, and learn how it can be used to your advantage, feel free to book a Moz Pro Kick Off Call with a member of Moz’s Onboarding Team below.
So, why do we want to conduct "competitive link research"?
Learning how others are performing can help guide your own linking strategy, and you may discover tactics that you haven’t considered before.
There may be opportunities and gaps in your competitor’s link profile, which you can identify and slot yourself into.
You will know what types of content perform well, and from there can make your content 10x better than your competitors!
Your analysis will help you understand more about the audience you are trying to speak to.
A comprehensive backlink strategy can aid you in ranking higher on the SERP.
If you're seeking guidance on how to build an SEO competitive analysis framework, check out Moz Academy's SEO Competitive Analysis Certification. This coursework covers everything you need to know to confidently implement an effective strategy, and you'll earn your Moz Certification, which you can display on your LinkedIn profile!
In the following videos, the Moz team will show you workflows and other tips and tricks within the Moz Pro tool set that will help you with your competitive link research analysis.
Link Gap Analysis: Link Intersect
Link gap analysis is a popular tactic amongst SEOs. It involves comparing your own link profile to that of your competitors, and finding the gaps that exist. They could be getting backlinks from several websites that you aren’t receiving any from — this could be a golden opportunity — another way to compete with your top competitors.
In this video, Emilie will show you how to use Moz Pro’s Link Intersect tool to find out this information.
Discover Linking Domains with SERP Analysis
In the Moz Pro Keyword Research tool, there is a functionality where you can search a keyword, and the top ranking pages for that keyword will show. But, there is so much more to this function.
In this video, Varad will show you those ranking pages, as well as the domains that are linking to that particular page. Get ready to soar from there!
Use Page Optimization to Find Content Suggestions
Moz’s Page Optimization tool is primarily used to see what improvements may need to be made to a page, as well as keyword placement on a page. When you dive a bit deeper into this particular tool, you’ll find that Moz offers content suggestions to you, including URLs that are ranking for the keyword you first queried. Identifying these top ranking URLs is a great way to see what kind of content you should also be creating.
In this video, Rachel will show you what you can do with this new found information and how it can help your link research.
Find Backlinks to Competitor’s Broken Pages
Analyzing the backlinks on a competitor’s broken page is another tactic that SEOs are using, that you may not have been aware of. There are hidden opportunities within these broken pages that are just waiting to be discovered.
In this video, Arian will show you exactly how you can find those broken pages within Moz Pro’s Link Research tool.
Discovered & Lost Backlinks
Another gem within the Moz Pro Link Research tools is the ‘Discovered & Lost’ section. This section will show you all of the new backlinks that Moz has found linking to your competitor in the last 60 days, as well as backlinks that have been lost. This can be insightful information when working on your own backlink building.
In this video, Eoin shows you how you can use this functionality to up your Link Research game.
If you’d like to continue learning about Competitive Research, check out our previous Daily SEO Fix on Competitive Keyword Research for some great insights into a competitive keyword research strategy.
Other additional resources for learning continuation:
Whether speaking to senior management or just trying to figure out what direction our SEO strategy should take next, as SEOs we often find ourselves asking the same question: “but what could I get from this?”
Particularly when we’re prioritizing work across different keywords, it can be hard to know:
What rank we can expect to achieve (rather than just assuming position 1 for everything).
What we could get from that ranking in terms of traffic/conversions.
What that means in terms of additional traffic or revenue
It can really trip us up if any of our predictions are based on wild rankings we could never achieve, or if we accidentally include traffic we’re already getting anyway!
So, what’s the solution to solve all of that, and ensure we focus on getting the biggest bang for our buck? Introducing Aira’s Keyword Opportunity Estimation Tool.
What is Aira’s Keyword Opportunity Estimation Tool?
Built in Google Sheets, the focus of the tool is to:
Identify the highest probable ranking position for different keywords.
Estimate what that could achieve in terms of traffic, conversions, and revenue, etc.
Highlight the best opportunities so you can prioritize your efforts. This is done by subtracting current estimated traffic, conversions, and revenue from the estimations if you were to rank in the highest possible position.
The sheet takes a top-20 report from a rank tracking tool and:
Allows you to enter a list of domains you determine you are unable to outrank.
Removes any ranking positions for domains you’ve listed as those you are unable to outrank.
Allows you to toggle on/off a list of commonly hard-to-beat domains so you can quickly cut down the list.
Removes instances where you might be trying to compete with competitors on their own branded terms.
Automatically picks out where you’re ranking currently to see how much more traffic/conversions you might be able to get on a given keyword.
Here’s an example output:
Let’s dive into an example
Imagine you’re doing SEO for a new flight site. Let’s call it BrainAir.
You know that you can probably rank for quite a few “flights” terms, unless there’s a comparison site like expedia.com already ranking. So, you add expedia.com as a domain to remove and now the sheet will find the best possible ranking you could get for each keyword except for positions where Expedia is already appearing.
In the example below, skyscanner.net and expedia.co.uk are both listed as domains to remove. In this case, position 2 is the highest potential ranking position, as this sheet only removes the specific ranking positions for the domains listed. This means you can still get a better position if that is available.
When doing keyword analysis, you may also realize there are some terms in your list like “Easyjet iceland flights”. If you don’t think you could beat Easyjet for “Easyjet iceland flights”, you can tick a box and the sheet automatically ignores any time Easyjet is ranking for a search that includes the word “Easyjet”.
Why use this tool?
This sheet can be used to see:
How much more traffic you could get from an SEO project in general.
How much more traffic you could get from specific keywords.
Where you should prioritize your efforts first.
While no estimate is going to be bang on the money, many other approaches will likely wildly overestimate how much traffic you could get in total, as they usually assume a highest position of 1, which is not always attainable.
On top of that, other approaches tend to not look at current traffic estimates, so don’t factor in additional traffic, instead just focusing on total traffic. This leads to situations where you’re focusing primarily on keywords with the highest search volume, as opposed to focusing on the keywords capable of driving the highest amount of potential traffic to the site.
This can help with developing SEO strategies, such as:
Prioritizing new page creation/re-optimization based on potential traffic opportunity. For example, if this sheet highlights an opportunity to drive a significant level of additional traffic for specific keywords, you may decide to prioritize building out new landing pages, or re-optimizing your existing content to target those keywords more effectively.
Prioritizing technical fixes based on potential opportunity. For example, if a tool such as Little Warden highlights technical issues , then this sheet can help you see the highest potential rank for specific keywords, should those issues be fixed.
Seeing which competitors are having the biggest impact on ranking positions for specific keywords/keyword groups. For example, if you see that the same domain consistently appears as one you need to replace in the rankings, then it will be worth investing time looking at their strategies and approaches.
Import your top 20 report into the tab named [Input] Top 20 Ranking Report, pasting into cell A1. You should delete/override the existing dummy data. The top 20 ranking report can come from any rank tracking tool, for example STAT, Rank Ranger, Accuranker, Data For SEO, etc.
At this stage, the order of the columns does not matter.
Stage 2: Selecting which columns to include
Navigate to [Input] Column Selection.
Here you need to use the dropdowns to select which columns relate to:
The keyword column
The search volume column
The rank column
The URL column
The table on the right-hand side will automatically update as these different dropdowns are updated with the first six rows.
Please check if the data aligns with the correct columns (or the rest of the outputs are going to look really odd).
Stage 3: Defining which domains you’re unable to compete with
Navigate to [Input] Domain Selection.
The first step is to enter your domain. The example in this case is booking.com
Next, add the domains you feel you’re unable to compete with. These can either contain the protocol or subdomain, or not.
You can find your competing domains by using a tool such as Moz’s Free Domain SEO Analysis Tool. Alternatively you can go to [Output 4] Current Traffic/ SOV Per Domain, which displays all of the domains ordered by total estimated traffic and share of voice.
We would recommend revising this list once you have seen the results, to include any additional domains you hadn’t previously included.
On the right side of the page, you can choose to include pre-defined domains in the list. This includes standard, hard-to-beat domains such as Google and Amazon, or social media domains such as Facebook and Twitter.
Finally, you can decide whether you want to exclude domains that contain target keywords in the domain name. For example, if you don’t think you could beat Easyjet for “Easyjet flights”, tick this box and the sheet automatically ignores any time Easyjet is ranking for a search that includes the word “Easyjet”.
Stage 4: Entering CTR, conversion rates, and average order values
Navigate to [Input] CTR, Conv Rate and AOV.
This section is designed for you to enter an estimated CTR for each position, average conversion rate, and average order value (AOV).
You can access the CTR position data yourself by using Google Search Console. It would make sense to focus on non-branded keywords, as branded keywords would skew these figures.
Advanced Web Ranking also provides an average CTR for each position for different industries based on a sample of sites. This can be found by navigating to the categories tab on this page.
Note: If you leave this column blank, traffic estimates will use the Average Non Branded CTR from Advanced Web Rankings.
The Conversion rate and AOV data can be found using Google Analytics, though it’s worth noting that these figures will vary depending on the type of page. For example, a blog is likely to have a much lower conversion rate than a product page, so it’s worth bearing that in mind during your analysis.
Stage 5: Output 1 — Keyword Breakdown
Navigate to [Output 1] Keyword Breakdown.
Here you can see the top 20 report with just the four columns that were previously selected: Keyword, Search Volume, Rank, and Ranking URL.
There are a number of additional columns:
Domain: The domain of the ranking URL.
Can our site outrank this domain?: This column tells you whether you “Can Compete” or “Cannot Compete” with each of the domains for their ranking position, depending on whether they are included in the domain list in [Input] Domain Selection.
Is it our domain?: This signifies whether it is the domain you have inputted in the [Input] Domain Selection tab.
Highest Potential Ranking Position for your site?: This column shows whether the column is the highest potential ranking position for that keyword.
Domain Name Mentioned in the Keyword?: This column tells you whether the domain name is mentioned in the keyword.
Stage 6: Output 2 — Keyword Highest Rank
Navigate to [Output 2] Keyword Highest Rank.
Here you can see a summary for each keyword showing you the highest potential rank, estimated traffic, and conversions/revenue, as well as which domain/URL you could conceivably outrank.
There is also data related to your current rankings and potential increase in traffic, conversions, and revenue should you reach the highest potential ranking position.
These figures are based on your previous inputs, so go back and check what you have entered if you feel that any of the figures are noticeably different to what you would expect.
Stage 7: Output 3 — Keyword Highest Rank
Navigate to [Output 3] Keyword Opportunities.
This output provides the top-level summary focusing on the keyword, search volume, and which domain/URL you could seek to replace. The metrics in this output are focused on potential additional traffic, conversions, and revenue.
These figures are calculated by working out estimated current traffic, conversions and revenue based on current rank, search volume, conversion rate, and average order value and subtracting this from these figures should the domain rank in the highest potential position.
Stage 8: Output 4 — Predicted Traffic/SOV Per Domain
Navigate to [Output 4] Predicted Traffic/SOV Per Domain.
This output provides an overview of the total estimated traffic per domain from the top 20 report, which allows you to see which domains are driving the highest amount of traffic across your keywords.
There is also a Share of Voice column, which pulls in the share of voice for each of these domains. The calculation is total traffic per domain/total traffic across all domains.
On the right side of the page, your own domain's current estimated traffic will be pulled through, alongside Share of Voice.
You can then enter competitor domains into the boxes below, which will provide total estimated traffic and share of voice with a comparison to your own domain.
How does this Google Sheet work?
This tool is designed to allow you to import a top 20 rankings report for your priority keywords, select which domains you feel you aren’t able to outrank within your niche, and optionally enter in CTR figures by position, average conversion rate, and Average Order Value (AOV), if you have access to this data.
Then, in the [Output 3] Keyword Opportunities tab you'll get a list of the best potential rankings you could get for each keyword, ordered by total additional traffic and revenue you could get from on top of what you are currently getting.
In order to make all this magic happen there is a fair amount of Google Sheets spice happening in the background, so if you’re a Google Sheets enthusiast, you may enjoy taking a look under the hood to see how we’ve pulled it together.
The main formula used is the QUERY function in order to pull specific data from one sheet to another, which automatically updates based on the user's selection on the [Input] Column Selection tab. This logic is used in all the main outputs.
The domain selection uses REGEX in order to combine together a list of different domains which are used in the different outputs to determine whether a site can rank for a specific domain or not.
Whenever working with rows, we use ARRAYFORMULAs in order to ensure that the formulas are applied to the whole column.
In the example below, we are using the regex above in order to determine whether a domain can or cannot compete for different ranking positions.
The estimated traffic, conversions, and revenue positions take the inputs from the [Input] CTR, Conv Rate and AOV tab.In the example below, we are working out the estimated traffic by multiplying the highest potential rank (in column C), looking up the CTR for that position and then multiplying it by the Search Volume (in column B). The same logic applies to the conversions and revenue figures.
Working out the difference in potential vs. current position is done by subtracting the estimated traffic from the current estimated traffic. There is some additional logic in there to catch whether the current traffic is higher than the potential traffic (as we obviously wouldn’t want the potential rank to be lower than the current rank).
These are the fundamentals, but if you are interested further, do make a copy, unhide the hidden cells, and have a good look under the hood.
Final thoughts
Within SEO, it’s critical to focus on impact when delivering results.
When you have a list of keywords, it’s often tricky to know where you could potentially rank, what levels of traffic you can earn, and how this relates to conversions and revenue. Aira’s Keyword Opportunity Estimation Tool tries to answer these questions.
Please reach out on Twitter to let us know how you get on with it!
You know GA4 is coming, and last week Dana took you through some of the top things to be aware of before making the transition to it. In this week’s episode, Ruth Burr Reedy discusses what a lot of marketers may not be thinking about enough: the people besides us who use Analytics data, and what they need to know about Google Analytics 4 in order to continue using Analytics data.
Click on the whiteboard image above to open a high resolution version in a new tab!
Video Transcription
Howdy, Moz fans. I'm Ruth Burr Reedy. I am the CEO of UpBuild. We are a boutique digital marketing agency specializing in technical SEO, advanced web analytics, and whole-funnel digital marketing strategy. And today, I want to talk a little bit about Google Analytics 4.
GA4 is here
So as, hopefully, all of you by now know, Google Analytics 4 is here. It is the next generation of Google's Analytics tracking software. And what I think at this point, hopefully, most marketers at least know that it's coming.
The most important thing to know is that on July 1st, 2023, which is less than a year from now, Google Analytics 4 will be the only Google Analytics product that will be continuing to collect data. Universal Analytics, which has been the analytics standard for several years now, will be completely sunset in less than a year.
A lot of people are talking about this. A lot of people are talking about Google Analytics 4, what it is, how to use it. I'm hopeful that the Whiteboard Friday audience already knows a lot of these things.
But one thing I think a lot of us marketers are not thinking enough about are the people besides us who use Analytics data and what they need to know about Google Analytics 4 in order to continue using Analytics data for the things that they use it for.
Stop! Get GA4 running
So, before we get into that, let's just stop for a minute. Do you have GA4 collecting data on your web properties, on all of them? Do you? Are you sure? If you don't, if there's a website that you own or are involved with in any way that does not have GA4 collecting data, just pause this video. Just pause it real quick and just get GA4 running on that site. It only takes a second. It's actually very, very easy to implement. And all you need to do, at this point, you don't need to configure it, you don't need to do anything else, just get it collecting data. I'll wait.
Who needs this data?
Okay. Ready? All right, great. Here we go. So one thing that we need to think about, as people who use marketing analytics data, is that there are other people besides us who need that data and see that data and use that data to understand what's happening and make decisions accordingly.
So who are these people? It might be team leadership. It might be your CEO. CEOs the worst, I know. It might be your boss. It might be your boss' boss. Your board of directors, if you're a publicly-traded or a venture capital-funded company or any other kind of company that has a board, chances are you are compiling at least a quarterly report for your board on how the website is doing using Analytics data.
You might also, if you are like me, an agency marketer, you have clients, you have client points of contact. Hopefully, you've already been in close communication with your client point of contact about Google Analytics 4. You've already got it set up for them.
But chances are your client point of contact has these same people in their work life. So if you are working with a director of marketing, a marketing manager, a CMO, someone in the marketing seat, you need to make sure that that person, your client point of contact has this same information to message to the people above them and the other consumers of Analytics data within their organization who may not be as familiar with how Analytics data is collected but still know enough to be using it and at least know enough to be receiving reports containing this data. All of these people need to understand what is happening with Google Analytics 4.
Implement it now
The time to do that is now. The time to do that is not July 2023. We need to start right now. We have less than a year to get everybody on board with what GA4 is, how it's different, and what that means for the data that they consume and use to make decisions, because it is different. It's going to be different.
I've talked to people who have seen that little alert pop up in Universal Analytics, that strikes a little fear into all of our hearts, Universal Analytics is going away on July 1st, 2023. Some people seem to think of this as when your phone says, "I'm going to install an operating system update overnight." Like cool, great. Phone, you do you. Turn it on the morning. It's not that different. It's fine. That is not the case with Google Analytics 4. And we need to make sure that everyone who uses Analytics data, with whom we interact, understands that so that they are not taken aback when that change happens.
We can also start making that change now gently, iteratively over time, while UA is still collecting data in order to illustrate to our data consumers what the differences are.
Have a plan for historical data
So the first thing that we need to do, when it comes to GA4 and the upcoming transition, is have a plan for historical data. One of the big things about this transition is that historical data in Universal Analytics will not be available via the GA interface after July 1st, 2023.
So how are you going to get that data? Because chances are you're not going to be okay with just saying, "All right, well, we installed GA4 when it first came out in the fall of 2020. So we've got a little more than a year or two of data, and that's our new data universe." There are companies who have just decided that that's what they're going to do, that's their new normal. KonMari your historical data, namaste, release it into the world. Most people are not going to do that. Most people are going to want to see historical data from farther back than fall 2020, which is the earliest that you could have been collecting this data.
So what is your plan for historical data? Hopefully, you have one. There are many blog posts and videos and articles out there on ways to preserve your historical data. I'm not going to go too deep into that. But whether you're using BigQuery and you're going to port it into some sort of database or data warehouse, maybe you have a small enough dataset that you're just going to export a bunch of spreadsheets and kind of store that, maybe you're going to build some kind of custom SQL database, whatever you're going to do with your historical data, it's none of my business, but you should have a plan to store that data.
Now, at this point, you may already have spoken to these people about the fact that historical data is going away, because that's something that they are probably feeling pretty amped up about. I'm feeling amped up about it. It's a lot, and we need to have a plan. But that's okay, that's what we're doing today.
Don't equate apples to oranges
The real thing that we need to keep in mind, as we're making a plan for historical data, is that the data in Google Analytics 4 and the data in Universal Analytics is collected differently. Even things that have the same name are going to be slightly different metrics behind the scenes. We're going to talk more about that in a minute. But it's important to know that comparing GA4 and Universal Analytics data is always going to be apples to oranges. They're not the same.
So even as you have a plan to make and store and use this historical database, however you're going to do that, you need to keep in mind that that data and the data you use going forward are not going to be one-to-one. And that's okay. I mean, it is what it is.
Some people, keeping that in mind, are changing what they're doing. Is the expense and effort of data warehousing your historical UA data worth all of the time and expense it's going to take, considering that it's apples to oranges? I can't make that decision for you, but it's something to consider. It's something to ask yourself and really think about what you're going to do with historical data going forward and how you're going to use it.
What's changing? Everything!
Because what's changing with Google Analytics 4? Everything. It's really different. And hopefully, by now, you've gone in there, gotten under the hood, you've played with some of the reports, you've looked at the UI. It's really different from Universal Analytics.
I've been doing SEO since 2006, and this is the biggest change in Google Analytics, especially the front end, the UI that I've ever seen. And also the backend is different. The method of data collection within GA4 is different, because a big part of why Google is making this push for GA4 is in an effort to be more in compliance with data privacy laws. So they're having to change some of the ways the data is collected and reported.
They're also looking at how to better do things like report on cross-domain traffic, cross-device traffic, traffic between websites and apps, when those are the same thing, they're the same and they're different. And now, in GA4, you can look at that data in a more holistic sense.
There's a lot of exciting, cool stuff happening in GA4. But the important thing to know is that things that are called the same thing in GA4 are still fundamentally different and collected at the very least slightly differently than they are in Universal Analytics. This is going to be hugely important when we're looking at this historical data.
A great example is sessions. The session, for many, many years, has been the core unit of Analytics data. GA4, you can tell from their reporting, is really trying to shift everyone's reporting from sessions to users. Both sessions and users are collected slightly differently. They are counted slightly differently. So your session numbers in GA4 and Universal Analytics for the same time period are going to be slightly different.
Now, the degree to which they are different is going to depend on a lot of things. Filtering options in Universal Analytics are a lot more advanced than they are right now in GA4. So if you have a lot of custom filters set up, if you're filtering out a giant known bot network, if you are filtering out data from specific countries, whatever you're filtering out, chances are you cannot implement that yet in GA4. That's going to affect it. But the session itself, how it's counted, when a session resets. So, for example, a session is resetting at midnight, having your time zone configured, hugely important in UA, less of a thing in GA4. So depending on the time period, depending on your filtering, depending on how you're counting sessions now, your sessions data may be a little different or a lot different.
All of this is also going to depend on the scope of your data. Tiny differences become big in bigger datasets. So if you've got hundreds of thousands or millions of sessions in a given time period that you're reporting on, the chances that those numbers are going to be different in GA4 to UA, they're probably going to be different by a bigger percentage.
And, at the same time, if you only have a very, very small number of users, because that sample size is smaller, you may also see bigger gaps. It really depends on your data.
The important thing is your data consumers don't need to know the ways in which data collection is different. You can tell them and they're not going to remember, and that's okay. They're busy and they don't need to know. What they do need to know is that it's different, it's not the same, and you have a year, at this point, to show them the degree to which it is different so that they can start to understand what the difference between the old dataset and the new dataset is, while you still have those same time periods of data collection to compare. Just to give them an idea of what's different.
So, at this point, you probably have some of these data consumers who are in love with a report. They've got their one report, and they look at it every day or they look at it every week or they look at it every quarter, and you have spent the last, however long you've been reporting to them, refining that report. You show them the report. And then they say, "What about this piece of data?" And you put it in there, and then they never look at it again. You take it out and no one notices. Or you put it in there and it becomes the new normal. Or maybe you have been trying for a long time to get them to look at users, instead of at sessions, but they just love sessions so much as a metric. Whatever it is that your data consumers love about Universal Analytics, chances are it's going to be at least a little bit different in GA4. And it's highly likely, and I would go so far as to say advisable, that that report is going to have to change. So the time to show them that it's different and ease them into that change, like dipping a toe into the Jacuzzi, is now. Not July 2023, now.
Users are another really great example of what is different between Universal and GA4. So in Universal Analytics, we're all used to total users and new users. Those are the two breakdowns of users. In GA4, you have a metric called Active Users, which is the users that have been active on your site in the last 28 days. That is the default users metric that you're going to see in GA4 and in the reporting. Now, you may decide, because you've already been reporting on total users, that you want to report on total users in the future. You can do that, but I would encourage you to look at the ways in which GA4 is presenting and encouraging you to use the data.
It's very interesting to me, this is a little bit of a sidebar, the ways in which Google Analytics, over the years, has taught us what is important to measure based on what they surface up most prominently in reports. And for my career, that has chiefly been the session. Now, increasingly, we're looking at the user, which is great in a world in which most people's purchase journey involves more than one device and certainly more than one session. But it does change the way we fundamentally look at and think about data. And I would encourage you, rather than trying to swim upstream on that, to think about how you are going to change your data reporting in order to mesh up well with the reporting that GA4 is going to roll out, because they're still rolling out new features all the time. You can take a look at what they are surfacing up prominently now to get an idea of where those new features are most likely going to be rolling out, especially in the next year, but even beyond that so that you are reporting in ways that are going to get you the most new cool data soonest. But I digress.
Another thing I want to make really sure that everybody, especially these people, understand is that events mean something completely different in GA4 than it does in Universal Analytics. In Universal Analytics, events are a very specific thing. You collect a piece of data. You have four parameters that you can assign — category, action, label, value. We've all, at this point, used UTM parameters. We know what those are. We're familiar with it. It's comfortable.
In GA4, everything is an event. It's almost going back to like super, super old-school internet days and thinking about hits on your website. At this point, everything in GA4, if you boil it down to a fundamental piece of data collection, is called an event. Could they have called it something different and made this less confusing? Yes, but they didn't, and here we are.
So this is really important to make sure that your data consumers understand that event collection is going to be different. And that's important because of this apples-to-oranges comparison. As you're collecting events data in GA4, it's going to be really, really tempting to try to recreate, as much as you can, your Universal Analytics instance, how you're collecting data, how you're reporting on it. Resist the urge to do that.
When you're configuring custom events in GA4, resist the urge, and maybe even the pressure from these people, to replicate that category, action, label, value naming convention just because that's what you're used to. Instead, this is a fabulous time to really be rethinking your data collection and your reporting. And we, as marketers, have a huge opportunity here that I want to make sure we don't miss.
Now is the time for data governance
Many of us have come into whatever role we're in now and come into an existing Google Analytics instance. Filters have already been set up. Goals have already been configured. Events have already been set up and have been tracking data for however long before we got there. What this usually means is that things are not set up entirely to our liking. Many marketers, myself included, have come into an Analytics situation and found that the data is incorrect, inaccurately reported. It's double counting things. It's not counting things. We have an opportunity now, with GA4, to make sure that our data collection is complete, accurate, precise, and robust. And we need to seize that opportunity.
And the same thing goes with event collection. Now is the time, for everyone watching this video, to start thinking about data governance. Now is the time for us to seize control of the data and do what we can to not only make it complete, accurate, precise, robust, but also future-proof that data collection for ourselves, for the organizations that we work for, for our clients, and for our data consumers, because we may not be the only people using that data.
There are often other teams going into Analytics. If you work with a paid search team or a display team or you work with just a general marketing agency who maybe doesn't do anything with Analytics but they look at the data, maybe they don't do anything to the website but they need data about the website because it informs their campaigns, they probably have dashboards configured. They probably have events set up. They may have set up those events in ways that you don't like. Things like, oh, here the label is capitalized. There the label isn't capitalized. Guess what, those are two different events. That's still going to be true in GA4, as of right now at least. Capitalization is still going to make two different parameters. So we have an opportunity right now to enact some data governance, make some rules, and take control.
So when we think about events in GA4, yes, everything is an event. There are many things that are going to be collected automatically. You do not have to configure GA4 to collect things like page views. They're just going to do that. I don't think you can get them to not do that because it would break the tool. You could, but why would you?
In addition to that, there are enhanced measurement events that Google has available for you to configure. Almost all of those, they're very easy to set up and they're standardized.
The same is true for recommended events. So within GA4, the next level of complexity from automatic and enhanced measurement events are recommended events. And in the GA4 support documentation, there is a large and increasing list of different recommended events and the parameters that they collect that you can look at. I would say, at this point, any recommended event that applies to your site you might as well configure, because you could use that data.
With both enhanced measurement and recommended events, because they have built-in parameters, Google is going to be using those more to drive some of the ... I know they're wanting to do a lot more with automated analysis and machine learning on datasets. All of that's going to start from the data that is consistent across Google Analytics' broader dataset, which is these enhanced measurement and recommended events. All of the parameters will be named the same thing, so it's very easy for them to collect them and then apply machine learning to them.
You still, as you are setting these up, need to make sure that you're enacting some data governance. You need to make sure the parameters are named the same way, that the same parameter is collected in the same way across recommended events so that you are, going forward, no longer having apples to oranges. That's GA4 to UA. Everything in GA4 should be oranges. Now, get that on a T-shirt, no one will know what it means.
And then the next level up is custom events. Custom events in GA4 are really cool. You can collect data on just about anything. You can pass just about any piece of data that Google Analytics 4 can collect. You can collect as a parameter. There's a ton of functionality, especially if you are pushing things into the data later to collect that as event parameters. We're no longer limited to category, action, label, value. We are limited by the total number of parameters that we can collect per property, which makes sense because data storage is expensive and it's expensive for Google. But we have a lot more customizability when it comes to custom events.
This is very cool. And we really need to apply the Spider-Man principle here. With great power comes great responsibility. Resist the urge to get in there and start tracking everything, partying like it's, I guess, 2099 at this point. Resist that urge. Make a plan. Now is the time for data governance.
As you are thinking about the custom events that you were going to track and the parameters you are going to collect, you might start by just outlining what you know you want to track and how you want to collect those parameters. But then it's time to make some rules, some rules for what you're going to track, how you're going to track it, what parameters you're going to collect, and how those parameters are labeled. You shouldn't just do this for whatever you're going to configure, as you're setting up GA4 now. Think about how you can create and future-proof rules for data collection going forward so that, over time, you get promoted, somebody else is doing your job, you win the lottery and go off to an island and are having a beautiful time. Whoever has your job after you should still have rules so that, when they are setting this stuff up, it is still oranges to oranges and you are creating a dataset that is correct, that is also useful in comparison with itself. Parameters that are useful in comparison across events and event types. This is the time to be doing that. Create those rules, make them clear. Make sure that people on other teams, anybody else who might be setting up events, even outside of the inbound search team or the marketing team, or whatever team you're sitting on, make sure that they have that. If you have clients, make sure you're doing a whole training session with them on what the rules are and how to use those rules to configure events in the future. Make a video. Document it. Share it out. The more you can do now to set yourself up for success in the future, the more valuable your GA4 dataset is going to be from day one and going forward.
So if you get nothing else out of this video, take some time to think about data governance and how you're going to make sure your data is useful and consistent going forward.
Now that we have this beautiful dataset, we're collecting data, it's configured, we've got a year. At this point, I'm filming this at MozCon 2022, we've got a year left to talk to these people about the difference between our apples and oranges and help them fall in love with oranges. So your CEO, your board, whoever it is that loves that report, don't just recreate that report for them with GA4 data. Take some time to talk with them, to understand what it is about that information that they use to make decisions, what it is about that report that they look at that helps them do their job. Find out how to solve that same problem for them with GA4 data rather than just trying to make GA4 look as much like UA as possible, because, over time, it's going to be less and less the case and, over time, people are going to forget about Universal and now you just have a GA4 instance that looks like Universal Analytics for no reason.
Now is the time to not do that. Resist the pressure to do that and figure out what your GA4 install is going to look like in 2023 and 2025, maybe even 2030. Institute those rules now so that you can help your board, you can help your CEO, you can help your clients and their bosses and their bosses' bosses gall in love with your new reports. They're beautiful. They're oranges-to-oranges. They've got new, robust, actionable data that you're using in new, exciting, advanced ways. This is coming. It's happening. Right now is a really important moment in terms of making sure that everybody is on board with what the changes are, in terms of making sure that everybody is on board with how we're going to collect data in the future, and giving everyone a year to fall in love with this new report before they have no other options.
If you have questions about any of this or you just want to talk about Google Analytics 4 and geek out about data collection, please holler at me at Twitter anytime. I'm very friendly, and I love talking about this stuff.
That's my Whiteboard Friday. Thanks, everybody. Have a wonderful Friday.
Did Q1 and Q2 whip past you? They did for me, but the pace of life often seems to slow down a little in autumn, and I hope you’ll join me for a relaxed and studious look at interesting local search marketing developments from the third quarter of 2022.
1) A small harvest of review-related changes
I’m grouping four different review-related developments under this heading. First, Joy Hawkins spotted a change to Google’s guidelines on prohibited and restricted content. As I’ve covered here exhaustively in my Moz column, there are lots of things a business can do to rectify a complaint in hopes of seeing an unhappy customer update their negative review to reflect an improved experience, but outright incentivization of negative review removal has now been declared out-of-bounds by Google.
Second and rather related, Greg Gifford captured a good stat from Aaron Weiche’s LocalU presentation that I’d not heard before: over ⅓ of negative experiences referenced in reviews mention communication problems. This means that you not only need to have your local business listings up-to-snuff with ongoing management of the accuracy of your contact info, but that all of your communications technologies (texting, live chat, phone, etc.) must be responsive!
Thirdly, Barry Schwartz spotted early testing of a Find Places Through Reviews feature in July, but as of September, I have still not been able to replicate this interesting result, which is a further indication of Google’s continuous experimentation in the review space.
Finally, another tip from the inimitable Hawkins as tweeted by Brandon Schmidt: longer reviews tend to remain higher up in your Google review corpus for a longer time. The problem with this is that lengthier reviews are commonly negative, with unhappy customers taking the time to wax poetic about their complaints. Take some time to consider whether you can finesse your review requests so that your delighted customers are inspired to leave more voluble reviews.
2) HCU near you
It’s my belief that local businesses which have already made a habit of publishing content that thoughtfully serves their specific customers should come out well in the much-talked-about Helpful Content Update, which finished rolling out on September 9th. While many SEOs are trying to ascertain which changes can rightfully be attributed to the update, our friends at NearMediaCo are having interesting discussions about whether the HCU is, in fact, part of Google’s response to the rise of TikTok as a vehicle for search. As Greg Sterling notes,
“Right now the most influential internet company is arguably TikTok. Google's HCU appears to be partly a response to the popularity of the site and its much-touted "authenticity."
Local SEOs and their clients cannot have failed to notice how many Google searches (including local searches) return low-quality results made up of optimized filler rather than human-worthy help. While the search engines and social sites play ball over who will win the authenticity trophy, my best advice to independent local businesses is to be sure that everything on your website is a proudly-published source of information for your community.
3) Beyond content: communication
There may be times when I’m willing to wander about in the Google maze or the morass of site search hoping for an answer to a complex query, but usually, I don’t have the patience and want to be able to ask a business directly, “Do you have size 8, man-made, furry boots, with fluffy linings, but not from this brand, and only from this brand, and can you deliver them to my house, and can you do that contactlessly, and is there a surcharge for that?” Local businesses can certainly publish content to cover all of these bases, but bless the brand that makes it easy for me to have a conversation with a human being.
Brandon Schmidt did us the favor of photographing Aaron Weiche’s recent presentation on this topic. Ahead of the holidays, be sure your texting, live chat, and phone staff is ready with all the answers via highly visible numbers and links (and my boots!).
4) Toggle to hide your address
Barry Schwartz highlighted Stefan Somborac’s screenshot of a new toggle feature in search and Maps that is meant to make it easier for business owners to hide the address on their Google Business Profile. The hidden address drama is one of the longest-running plots in the soap opera that is the Guidelines for representing your business on Google. I would personally like to see this character written out of the script in favor of businesses having the say in whether they want their exact location to be visible on their listings. I’ve never understood Google’s logic for requiring SABs to obscure their locations; living in an old house as I do, I’ve had too many opportunities of needing to know which 24-hour plumber is actually nearest to me.
5) Linked FAQs in Google Messaging
This might be one of the most exciting developments of the third quarter and we again have Stefan Somborac to thank for noticing it first. You can now populate Google Messaging with up to 10 FAQs with questions of up to 40 characters and answers of up to 500 characters and your answers can include links! While I’m not personally fond of automated consumer-brand communications, I can see a good use of this for answering really common questions about hours of operation, premise accessibility, or the availability of top brands in your inventory.
6) Filter local packs by days of the week
Google has long offered searchers the ability to filter packs by hours of the day, but Shameem Adhikarath realized that, at some point, the ability to filter results by specific days of the week was added. When a customer wants to know on Monday which are the best restaurants that are open on Saturday, a little feature like this makes sense. Word to the wise: be sure your hours of operation are always up-to-date on your listings!
7) Evaluate the role local SEO should play in property hunting
Elizabeth Rule brought us this screenshot of Andy Simpson’s LocalU presentation in which he reminded local SEOs that our concerns are not the only ones that should be involved when a client moves or opens a new branch. While I’m sorry to have missed Andy’s full presentation, I can see the sense of it, just from this slide. So many of the goodies of reputation and profit will flow naturally when other factors like the location, convenience, and size of a new locale are properly considered, so definitely weigh in with local SEO recommendations during times of change, but prepare to be in a queue of many priorities.
8) Maps Photo Pins exist, but have you seen them yet?
Our honored colleagues at BrightLocal captured a version of Maps-based photo pins in September that is different than the ones reported by Barry Schwartz back in July as spotted by Vishal Sharma. These latest examples are round instead of square. I have not been able to replicate this test with similar search terms from my location in the US, and so I have no way of sussing out what the source of these images is or how to nudge Google into giving a business pin like this. For now, keep adding photos and keep checking Maps for this intriguing feature.
9) Be the winner next-door next year?
Nextdoor users voted many local and ten national businesses as their favorites this past August, and the winners have received press, badges and $500 ad credits. It’s definitely a platform worth getting listed on, and home service providers came out especially well in the contest. Nextdoor highlighted how showing up on time for appointments, providing excellent service, offering specialty goods and services, and earning recommendations from neighbors all contributed to winners’ successes. Sounds like good advice to take with you into the fourth and final quarter of 2022!
