In today’s video we’re going to have a look at Google analytics 4 standard reporting interface.

To start with let’s have a look at Universal analytics versus ga4 and how the reporting interfaces differ.

On the left you’ll see Universal analytics 4 and on the right we have ga4. Now, straight off the bat they probably look very similar but as we dig into the reports you’ll start to see the differences. Both of them have this home screen which is just an overview of what’s happening in some real-time reporting but then we can dig deeper into the reports section.

In Universal analytics we have reports sorted by real-time audience acquisition behavior and conversions and in GA4 we need to click into the reports tab and then we’ll see lifecycle reports sorted by acquisition engagement monetisation and retention somewhat modeled on marketing lifecycle flow. Then we’ve got our user reports which is demographic and tech reports.

Now you’ll notice when I expand each of these there’s basically only three to four reports in each section, if we have a look at Universal Analytics the age-old problem was that basically there were too many reports and you have multiple levels of reports and people would just jump in here and get so confused and scared and not know where anything was. That had just become a nightmare to find exactly what they were looking for so we can see there’s dozens and dozens of reports under each tab whereas GA4 standard reports are quite basic and limited, but the idea is that you create your own ports either by customising these or creating Explorations or even look at Studio reports.

Let’s go through the reporting interface and go through the standard reports one by one. When you first log into GA4 you’ll get the snapshots overview which is basically a series of tabs that Google thinks are probably the most important things that are happening on your website at the moment. It’s an overview of reports that you can find deeper within the reporting structure and you’ll also see some insights type of reports here which are AI based or AI generated. So, you can see some kind of insights that are happening, user spikes, sources changing, and all these kind of insights that may or may not be useful.

The next report is the real-time report now you might be familiar with the real-time report from Universal analytics. The main change is that the real-time report in GA4 for 30 minutes whereas the real-time report in Universal analytics only covered the last five minutes. We also get this nice graphical upgrade we’ve got the interface an overlay like a geographical map overlay so you can see where traffic is coming from and blue blipping in real time. Then we can see it broken down by user source audiences and content and conversions. Now you can change some of these reports you see little arrows where the dimensions are changeable but you are still quite limited in what’s presented.

One thing that’s kind of cool maybe a little bit creepy that’s new in the real-time reports in ga4 is something called view user snapshot. Now what this is is the actual activity of an individual on your website right now. So I’ve got someone from Bangalore in India and they’re browsing around the website quite a lot they’ve looked at 23 pages they’re viewed their cart seven times they’ve added four items to their cart they’ve viewed the cart seven times and they’ve actually removed an item for the cart.  If we click here we can see an actual timeline of how they’ve progressed through the website as well. So in this session I can only go as far back as half an hour they’ve added to a cart they’ve viewed their cart they’ve viewed some more items they’ve viewed their card again, they’re looking at promotions scrolling through the website adding to cart again, viewing more items. Now if this was your website and you’re an e-commerce store hopefully you’d see this person checking out finalising that purchase. So that’s something new and quite interesting if you’ve got the time you might be able to eke out some interesting insights by looking through individual users, but I suspect that there’s probably a lot more work involved in that than will actually lead to any meaningful insights, but still kind of cool especially if you start seeing things in here that you weren’t expecting. If you’ve got any kind of error event checking or things like that that may be interesting.

The next series of report to the life cycle reports and they each follow a very similar structure or you have an overview report and then some detailed reports so let’s start with acquisition and have a look at the acquisition overview report. Now we’re looking at data from the Google merchandise store account. It’s real time and live and this is the store that the data is coming from so it’s their actual merchandise store and they give us access to this account for learning and education. So we can see all the data is coming from that website and we can see on the acquisition overview, users versus new users, users in the last 30 minutes, and the top countries. The default channel grouping which we can change to source platform, source medium, campaign, whatever you like and sessions versus engaged sessions. So you can see it’s pretty high level it’s not really that deep and meaningful but it’s just an overview.

The next two reports in the acquisition section are the user acquisition first user and traffic acquisition. So basically what the difference is this user acquisition report shows only data whereas the user is a first-time user to the website and how they got there. So this is first-time visitors to the website and what are their means of getting to the website. So the default Channel grouping is Google’s categorisation. You can change this to source/medium if you prefer which is something you might be more familiar with. So we can see here the top driving source and medium for the Google merchandise store is Google itself organic search traffic. In here we see a breakdown of new users, engaged sessions, event count, conversions, and even revenue. So we can see that even though organic is driving a lot of new users and engaged sessions it’s stroke it’s driven fifty five thousand dollars in revenue, whereas direct as driven 144k.

Now in each of these reports it’s important to know that you can change date ranges, so let’s look at the last 30 days of data for example. You can compare date ranges so month over month, year over year, and you can also compare different segments of traffic. We can build a comparison here. Let’s say we want to compare how different countries perform. So let’s include a dimension country and let’s look at United States and let’s apply that to the report. Now we’ll be able to see how new users from the United States compare to users from all countries. Now you’ll see the table is broken down so we can see all new users, there’s twenty thousand and seven thousand six hundred and fifty seven of them came from the United States now we can build upon that as well. Let’s add the second highest country which is in this case India and apply that to the report and to simplify it let’s take out all users and just compare United States versus India. So we can see the blue line is United States the orange line is India and we can see that there’s a lot more traffic coming from the United States and it’s a lot more volatile. What might be also interesting to see is how those countries compare in terms of revenue. Let’s have a look at the organic traffic how organic compares the United States. Organic traffic from Google Search has driven 7,657 new users whereas India we have 4,001. However, let’s have a look at the differences in revenue. Those seven thousand six hundred fifty seven users from United States resulted in fifty four thousand dollars almost fifty five thousand dollars in revenue, whereas the 4,000 new users from India drove 172 dollars in revenue. Now there may be different reasons for that, maybe more people from India are using the merchandise store in terms of education because they do provide this demo analytics account, or perhaps it’s just that United States is is more likely to buy Google merchandise.

Now it’s important to know that unless we clear these comparison segments they will stay there for each report that we go to.

So let’s continue to all traffic acquisition not just new users and you’ll see that again we’ve loaded in those two segments. Let’s get rid of those and then it’ll default back to all users so again, similar data is presented in a table. We can add a secondary dimension so we can have a look at perhaps organic search and country. This way you can see here the top two the top channels are coming through there.

Another secondary dimension you might find it interesting is something like device. Imagine we just wanted to filter for organic traffic we can actually just type that in here, and now we can see for organic search, organic social, organic video. If we wanted to further refine that we can type in organic search. Here we can see that we have now just organic search in this table and our device categories. So now we can have a look at how traffic from organic search performs depending on which device they’re using, and in this case desktop is driving the highest amount of revenue.

Next up are the engagement reports. Now this is how people are interacting with your website or your app. Again we see engagement overview we can see engagement time, engaged sessions per user, and average engagement time. We can see total views and event count and we see our top events and our top views. This will show us the top events tracked on our website, and if you recall everything a user can do in GA4 is tracked. In this event you can see in the case of the Google merchandise store the top event appears to be view promotion. Now I think the reason for that is they have this scrolling carousel of promotions on the home page and perhaps it’s triggering an event each time that goes through. Next view item list, and page views, user engagement, page scrolls, viewed items, session starts etc. etc.

The next report is conversions, so again the conversions are the events that we’ve marked as being most important for our website, and in this case the top performing conversions for the Google merchandise store are predicted top spenders, first visits, add payment info, begin checkout, and purchase. Being an e-commerce store things like beginning checkout, adding to cart, adding payment, and purchasing are very critically important to monitor.

The next report is pages and screens. So what are the most viewed pages or screens? If you’re in an app now because of the way this report works it can be difficult to review, the reason for that is because it uses page titles as the dimension. Now, not every website uses page title as well, so you can change this to page path and screen class. Page path is probably the one you want to use if you’re looking for the URL and you’re more familiar with Universal Analytics. It’ll show you the actual URL there on the website. So, as usual the forward slash is your home page, and then you can see the URL of each page.

The next reporting section is monetisation and this is primarily for e-commerce websites and websites that sell ad space. Now because the Google merchandise store is an e-commerce site we can see data in the monetisation overview report. We’ve got total revenue, e-commerce revenue. The only way this website is driving revenue is from e-commerce, and then we can see things like top products and average revenue per user. We can see total purchases versus first time purchases, and then if we dig into the e-commerce purchases report, this is a more in-depth e-commerce report. We can filter by item name, item category, item brand, Item ID, and we can see how each is performing. So we can see the new items are performing best, followed by men’s unisex sale. We can see revenue for each, total number of purchases for each. So these reports are quite useful for e-commerce stores.

The retention reports show new versus returning users. There is some debate on how accurate and useful these are, with issues around cookies and certain browsers and apps not allowing for reliable tracking. But it’s there and if it’s useful to you then great.

The last two reports are breakdowns of our user demographics and technology. So we can see the demographics overview geography a deeper dive into users. You can do new users versus returning users, breakdown by gender, their interests, their ages and languages. If we go into demographic details report we’ll get that familiar graph and table layout where we can start manipulating the data to see exactly what we want to see. So we can start getting a breakdown of potentially age, plus gender, and then we can see if we want to do some very targeted advertising buys. We could probably sort this by total revenue, so we can see for the last 30 days female users aged 18 to 24 have resulted in the highest total revenue.

Lastly, in the standard reports overview are the tech reports. This is the technology people are using to access the site. Now this first report here uses by platform, you can see it’s 100 web, and the reason for that is the Google merchandise store is 100 web-based, it’s not an app. Whereas if you’re in a Google analytics 4 account that has both web and app data streams you’ll see the breakdown of users by platform across your platforms that you are tracking. Again, we go into the tech details and we’ll get the chart and table based data that we can manipulate, and then we can see a breakdown of revenue by browser, by OS, by device model, by device category.

So these are the top level reports that are available in Google Analytics 4 standard reporting. Now again I want to make it absolutely clear that these are very top level reports, especially in comparison to some of the deeper dive reports that you could get in Universal Analytics, but the whole idea with GA4 is that you create your own reports based on what’s important to you. There’s basically three ways to do that. The first way you can customise this report is by editing them, effectively make a copy of them and change what is included, you can change the graphs at the top, you can add filters, and you can save them into this menu list. So you can have a report customised the way you want it and saved in here. The second way is by using exploration reports, which we’ll look at in the next video. And the third way is by exporting your data into looker Studio, where you can create 100s of custom reports from multiple data sources such as Google Ads, Facebook Ads, Google Analytics or pretty much any other data source you can think, of even static Google Sheets.

if you have any questions or comments about this video feel free to ask.

This video is your introduction to Google Analytics 4. In this video we’ll cover a brief introduction to GA4, the differences between GA4 and Universal analytics, and in separate videos in the future we’ll look at the GA4 standard reports interface, as well as custom reports, and exploration reports. Then we’ll have a look at the next steps and takeaways.

Before we get started perhaps it’ll be interesting to understand how we’ve got today, and the history of Google Analytics. So Google Analytic classic came out in 2008 and Google purchased a company called Urchin rebranded it Google Analytics. In 2013 we got Universal Analytics and in 2016 we got a mobile analytics in the form of Google analytics for Firebase. In 2019 we got Google Analytics web plus app which is basically an alpha of Google analytics 4, because Google Analytics 4 makes it possible to collate web and app data in one analytics profile. GA4 officially launched in 2020. it was very alpha at the time wasn’t as fully featured as it is now.

So what’s next? Well our countdown is on to July 1, 2023, and that’s when Universal analytics properties will no longer process data effectively what that means is before then you want to make sure you have GA4 set up. As far as we know six months after this date Universal Analytics will no longer be accessible. One question many people have is, why do I need to upgrade to GA4? Put simply, if you want to continue using Google Analytics as your analytics platform then you need to upgrade to GA4, because as stated earlier on July 1, 2023, your standard Universal analytics properties will no longer collect and process data. So it’s important to back up Universal Analytics data if you want to be able to compare historic data to the new data collected in GA4.  So that’s things like year-over-year reports, or multiple year reports.

The next thing to know is that ga4 is a completely new analytics platform and it is not backwards compatible with universal Analytics. That means you cannot export your data from Universal analytics and import it into GA4, GA4 is a fresh start. So the sooner you install GA4 and start collecting data there, the more useful it will become. So GA4 requires its own installation and customisation, it’s a brand new setup. Now it’s important to know that GA4 is a more powerful and robust analytics platform, it’s been built from the ground up with new functionality in mind that improves data collection, analysis, and privacy requirements. One of the most important new features is the ability to collect web and app data in one profile. A bit of a bonus GA4 makes previously paid features available to us for free, these include a BigQuery export and exploration reports. BigQuery is Google’s cloud data warehouse platform. Exploration reports were something previously only available to Google analytics 360 customers and they allow you to create custom reports based on your own unique requirements. Upgrading to GA4 presents a fresh start and a new opportunity to review our current tracking and reporting requirements, and make sure we have everything we need going forward.

So what’s new in ga4? Well we’ve touched on some of these, but let’s have a look. It’s an entirely new analytics platform and as we saw in the historic overview Universal analytics is around 10 years old now, so it is about time for an upgrade! GA4 is an events-based measurement model whereas Universal analytics was page view, I’ll go into that a bit deeper on the next slides. GA4 unifies web and mobile analytics, it improves cross-device and cross-platform tracking. GA4 has advanced user identification, it includes multiple methods to identify and de-duplicate unique users, and it includes some degree of cookieless tracking. So there are three ways now that ga4 can identify users, and I’ll touch on those in the following slides.

GA4 enables roll-up and sub properties, so one scenario for roll-up reporting may be a company that has country level websites and you would install analytics on each of those uniquely and then have an overarching property above those where all the data could be rolled up for the head office to review. Now sub properties are kind of the opposite of that and a scenario for sub properties maybe a website that has different business units and wants to filter out data for each of the business units into their own properties. So we may have a Communications type company and they may have very separate business units where one sells mobile phones and one sells internet data, and they may want to be able to report on that in one property, but then also have sub properties that different business units can access. So there might be one property for the mobile side of the business, and there may be one property for the internet side of the business, and they can each see their respective data, but in the top level property that can all be reviewed.

There is some machine learning and predictive capabilities in ga4 and that comes about in a number of ways. One of those is in predictive audiences where Google analytics can create audiences based on how it predicts groups of people to behave. For example, it may create an audience that is predicted to be a higher converting audience, or inversely it may create audiences that may be people that are more likely to churn. Additionally, some insights it’ll provide on some reports based on machine learning insights, and we can have a look at some examples of those now.

One thing that a lot of businesses may take advantage of is enhanced measurement, which is basically automatic tracking of common events think of things like PDF downloads, and now even form completions. Historically we may have needed the assistance of a web developer to help implement those as events or at least they needed to be implemented separately through Google Tag Manager. Now these common event types are able to be tracked automatically simply by turning on enhanced measurement.

There are enhanced privacy controls, there is country level privacy controls to manage things like GDPR and any other country level requirements, and there is easier data deletion.

Being a new analytics platform there are new dimensions, there are new metrics, for example we have engagement metrics such as engage sessions, engagement rate, and engagement time, and these are basically the inverse of what we would look at in terms of bounce rate previously.

I touched on previously that we have access to previously paid features now such automatic export for data backup to BigQuery, and we have our exploration reports which can be quite powerful. They include things like funnel reports, path reports, and even path reports that can start at an endpoint.

Let’s talk about data streams. In GA4 data streams are the way we get our data into Google analytics. In Universal analytics we basically had a tag and we would put that on a website and it would send hit-based metrics to Universal Analytics. In GA4 we have data streams and they are basically similar in the way that they are set up as tags on websites but in GA4 we can send web and mobile data streams into one profile. As you can see in this screenshot I have here we have an example of Google’s flooded app and website, so we can see here the Android app the IOS app, and the website data all flowing into one analytics profile.

A big change between Universal Analytics and GA4 is that Universal analytics was pretty much a hit-based measurement model where there were multiple different types of hits that were sent into Google analytics and processed and turned into reports whereas everything in GA4 is an event. It’s kind of important to get your head around that and we’ll do a deeper dive on that soon. So for example in Universal analytics there were different hit types we had page view hit types, we had event hit types, we had social, e-commerce, user timing etc. etc. In GA4 everything somebody does on a website is an event and those events are grouped into reports for analysis.

So let’s take a deeper dive on events and the event types in ga4. This is basically a flowchart of the events and the event needs you may have for your website, and you basically start from the top and work your way down. So let’s have a look at an example of that. The first layer of events in GA4 are automatically collected events, so as soon as you have GA4 implemented on your website it’s going to start collecting event types such as first visit, session start, user engagement.

Now the next level of events that GA4 can collect are those that are turned on when you enable enhanced measurements. So enhanced measurement is that feature I talked about previously where you simply turn it on and then Google analytics will start collecting more advanced event types that previously required additional work to implement. Some examples of enhanced measurements events are page views, scroll, so when somebody Scrolls to about 90% of the page, outbound link clicks, so those are links offer your website to external websites, site search, this is for collecting the search terms that people are actively searching for on your own website if you have a search bar, video engagement, people engaging with YouTube videos embedded on your own website, file downloads such as PDF downloads or any type of file, and form completion tracking.

The next layer down is recommended events. Basically what we mean when we say recommended events is that there’s an existing schema that Google recommends around what to name each of these events when you send them to Google Analytics. So, if you have an e-commerce website and you want to track when somebody views their cart there is a recommended event name that Google will suggest you use for that event setup.

Now let’s imagine an example where you’ve gone through these three layers and you still don’t see the event that you want to track maybe something very custom to your website. Then the fourth layer of GA4 event types are custom events. These are any events that do not appear in those previous three layers that you want to track in Google analytics. The naming convention is up to you. There is a little bit of work you need to do to enable these to start showing in reports in Google analytics.

Now when we talk about event tracking in GA4 a lot of people think about event tracking and Universal analytics now most people will recall that event tracking in Universal analytics had a very rigid structure where we could use category, action, label, and optionally a value. So we would have to shoehorn any type of event that we wanted to track in Google analytics Universal in this format category. For example a PDF download the category may be PDF, the action may be download, and the label may be the document title that you want to track. In Google analytics 4 there is no notion of category action and label, everything is an event and you can have up to 25 additional parameters tracked to each event. So in the case of a PDF download the event name is file download and the parameters can be anything you want. So the parameters in this example, a file name, file extension, file author, file category, and file version.

The next change when it comes to GA4 versus universal analytics is the way conversions are handled. Now anyone familiar with universal analytics will remember this multi-step scenario that you’d have to run through every time you wanted to set up a conversion. First you’d have to select what type of conversion it was. An example of a destination conversion would be the URL where the conversion takes place, duration would be time based, you could do Pages, or screens per session, or tie it back to an event. Then you’d have to correctly and accurately match up the category, action, and label that you’d previously defined to track that as a conversion. So, it was pretty complicated, there were quite a few steps involved. GA4 has simplified conversion tracking immensely. All you simply need to do is go to the events you want to turn into a conversion in gGA4 and toggle on ‘mark as conversion’. In this example you can see a contact form is a conversion, it’s as simple as that. Any event can be a conversion so you just need to identify which of these are the most important for you and turn them on as conversions.

So let’s have a look at some of the concepts we discussed in an actual Google analytics 4 profile. When you first log in you’ll be on the Home tab. Now let’s have a look at admin and have a look at data streams. Under the property column you’ll notice in GA4 there are only two columns, there’s no view columns like there are in Universal analytics.

Let’s have a look at data streams, it’s one of the first Concepts we explored and we can see here just like in that screenshot I provided earlier. We’ve got the Android app the IOS app and the web data all coming into the one profile. Now when we click into one of these data streams we’ll be able to see more details about the data stream, its name, its URL that it’s tracking, it’s Apple website the ID, and the measurement ID. Here is where you also find the enhanced measurement options that we discussed earlier in the video, so we can see that enhanced measurement is turned on for this profile, and the enhance measurement options is taking advantage of a page views, scrolls, outbound clicks, and file downloads.

Now let’s have a look at events. So if we go to the configure tab we can see the first option is events, and here we’ll see all the events our website is collecting. Here are the options to mark a specific event as conversions. There’s a separate tab that we can look at just the events that are marked as conversions, there they are.

If we come back to the Home tab we can see some examples of insights that are driven by data learning and AI. Here are two cards on the home screen that have been created by machine learning. This one’s around an increase in users from Google Ads specific ad group, and this one is an increase in conversions. In the audience tab on this account we can see examples of audiences that we can use that have been created from machine learning and AI. Our first one here is called Asia top spenders and based on the name of that I would assume it’s a cohort of top spending users from Asian countries. We can also see an audience for predicted 28 day top spenders, and likely seven day purchases. So those audiences have been created by Google using artificial intelligence and machine learning, we can use those for reporting and remarketing campaigns in Google Ads.

Key Takeaways

• GA4 is a completely new analytics platform, it is not backwards compatible with Universal Analytics, and requires its own installation and customisation
• GA4 is a more powerful and robust analytics platform with new functionality that improves data collection, analysis, and privacy requirements
• GA4 makes previously paid features available for free, such as Big Query export, and Exploration reports
• Upgrading presents a fresh start and an opportunity to review tracking and reporting requirements
• Out-of-the-box reporting is somewhat limited but we can customise or use Explorations, or Looker Studio reports to build better reports
• Many new features / enhancements: web + mobile reporting, Enhanced Measurement, data controls, user identification etc.

So that’s everything I wanted to cover in this first video. In the next I will go over the standard reports.

I hope you found this useful if you have any questions let me know, thanks!

in this video I’m going to show you how to determine which version of Google analytics is currently running on your website.

The countdown is on to July 1st 2023 when Universal analytics will no longer be supported or collecting data and you may not be aware of which one you’re on because perhaps an agency or a developer is handling that for you but here are three simple ways to determine which version you currently have on your website.

the first option is using a website that can determine what apps and what technology is running in the background of your website one example is built with and I have two example websites that are run built with through to show you what it looks like when you’re running GA4 versus universal analytics. I’ve just chosen these two websites pretty much at random I just typed in Perth in Google search and we have the Perth tourist center and we have destination Perth. So what we do is copy the URL of the website or in this case probably your own website and you go to BuiltWith which is simply builtwith.com and you post your website URL in there and click look up and pretty quickly it’ll give you some results. In the top section we’ve got analytics and tracking and we can see here we’ve got Google Analytics and we can see Google Universal analytics. So there is one easy way to determine which version of analytics you’re running.

If we have a look at destinationperth.com.au for comparison now we see under analytics and tracking two instances of Google analytics the first one is universal and the second one is ga4 so this tells us that Destination Perth is running both Universal analytics and GA4 in parallel and that was a recommended setup back when GA4 was first launched.

Now there may be some instances where BuiltWith cannot determine which version of analytics you’re running and in that case the second option is to use Google’s tag assistant browser extension for Google Chrome. The version you want to find is the tag assistant Legacy version all you need to do is search for tag assistant Legacy and you’ll get this website chromewebstore.google.com tag your system it’ll take us to the Chrome Web Store all we need to do is click on add to Chrome. Add extension and now we can see it’s been added to our browser up here.

Now what may happen to you like it happened just then for me is that the extension pops up in the little shortcut section here and then disappears. The way we can pin it so that we can always see it in that selection there is just to click on this extensions icon and look for the little pin next to the Legacy and now it’s there for when we need it now the way we use this extension is basically going to the website we want to run it on we click on the extension icon now the first time you run it there will be some options that you need to confirm and then each time you want to run it on the website. All you do is go to the extension click on it click enable then you will need to reload the website that you want to run it on.

So let’s reload this website and now you’ll see on the browser extension icon there’s a number two and that means it’s detected two tags on this website, let’s simply click on the tag to extend it and find out what they are. Now we can see it’s detected the global site tag and Google analytics and in both cases we can see that that begins with UA which stands for Universal analytics so we’ve determined again this time using Google tag assistant that Perth Visitor Center website is using Universal Analytics.

Let’s repeat the process for Destination Perth click the icon enable it refresh the website and check the results in this instance it’s detected five tags again we can see the global site tag and the universal analytics site tag but this time the global site tag starts with a ‘G’ and that helps us recognise that it is using GA4.

On to the third option of how to determine which version of analytics is running on a website and this one might be the scariest for people who aren’t used to using the expect Tool in Google Chrome but it’s not that scary all you need to do is click pretty much anywhere on the website and click inspect and then you’ll see this console come up and what we need to do is go to network what we need to type in here is collect and then we want to refresh the website now after the website has completely loaded you should be able to find an instance of collect if the website is using Google analytics and very basically if you see V equals one that’s version one and that tells us that it’s using Universal analytics let’s repeat it for Destination Perth so we can right click pretty much anyway click inspect go to network type in collect refresh the website and now we will see after a moment it loaded there so we had to wait for the website to completely load that we can see V equals one version one that’s Universal analytics but we can also see V equals to which is GA4.

So that’s three different ways that we’ve just confirmed that Perth tourist center needs to start thinking about upgrading to GA4 whereas Destination Perth is ahead of the game and they’ve already got GA4 installed.

I hope you find that helpful if you have any questions feel free to ask, cheers.

Welcome back to the keyword research done quickly series. If you haven’t seen video one in the series, I recommend you go check that out now. When we left off last time, we had collected and collated our data from Google Keyword Planner and Answer the Public properly into a spreadsheet and filtered them by estimated impressions and clicks, and we were left with a comprehensive list of search terms.

Now, since then, I’ve done a bit of filtering and theming. The first thing I did was filter out any irrelevant, unnecessary keywords. The first one I filtered out was “sourdough bakery,” obviously that’s relevant because the website is not a bakery, and somebody searching for a bakery is probably looking for a local bakery to visit. In that case, we filter that guy out; we can delete him. I just hid it so I’d have a good example to show you.

The other thing we have done since is starting to look at theming, typing, and targeting. By theming the keywords, we create thematic buckets of similar keywords based on intent or relevance, based on types of product versus informational search terms. In this example, we have a number of themes. So, “core keywords” are a critical base search term keyword that is going to always pretty much point at the home page. We have ingredient-based keywords; a couple of examples of those are “sourdough starters.” Another ingredient we can see here is the yeast.

Next, we have equipment, so this is equipment people will need to be able to make their own sourdough. The “sourdough machine” is obviously equipment; a “sourdough Dutch oven,” haha, yes, is equipment. Next, we have an artisan versus a generic type of bread, so people looking specifically for artisan sourdough. Then we have a really good differentiator in making versus buying. So, the “making” keyword is pretty obvious: making sourdough bread versus buying sourdough. Now, the reason why we might want to target both make and buy is because we could put together a content piece that makes a case for making it yourself rather than buying or buying the equipment you need to make it yourself.

So once we have a good five or six top-level categories that each of the keywords kind of fit into, we want to think about what type of content that theme and that keyword relate to. It can relate directly to an existing product page on the site, and that’s where this target comes in. So, the target column relates to, on the existing website, where are we going to target this keyword. Now, if there’s nowhere on the existing website where we can target, then we put “new,” and we might have an example of a new page, but we want to link to an existing page on the website.

So let’s walk through a couple of examples. “Sourdough starters,” we’ve put down as an ingredient theme. We think it’s going to be a product page, and there’s already a product page that fits this keyword to a T. Now, what we might want to do separately is optimise a content page and then link through to the product page as well. Another example is “sourdough machine.” Now, she doesn’t sell sourdough machines on the website, but what we could do is review sourdough machines and link to either selling them on your own site or affiliate linking to another site. So, there’s an example of a suggestion we could make.

The exercise is to make your way through each keyword, fit the keyword into one of the core keyword themes that you see popping up again and again, suggest a content type, and then review the website to see if there’s an existing page that fits well that could be optimised, or suggest creating a new page that may or may not link through to an existing page. Once we’ve got this information, it’s going to help us put together a bit of a content plan. We’ve got our keyword planner data that we’ve revised, themed, and created targets for. We have our Answer the Public data that gives us question-based content that we can write content for, and when we combine the two, we’ve got the makings of a content plan.

We’ve got our main content topics, which are made up of the keywords that we see appearing again and again for similar keywords. We’re not going to make a unique page for something like making sourdough bread as well as making sourdough; we’re going to take the key themes that we’re seeing and create new pages that target multiple keywords on one page, so we don’t need hundreds and hundreds of pages. We may need dozens that are highly optimised to relevant and related keywords.

Here’s an example: taking all of the Google Keyword Planner data, Answer the Public questions, we’ve put together a prioritised set of content topics, and to start with, we’ve got that down to 15, so it’s not crazy overwhelming. It’s something that the client can work towards or outsource and get done quite quickly. So, we take each of our content topics, and we start to put together a brief. The first one, for example, I’ll fill out so you can follow along. Can sourdough starter go bad? Our brief for this is going to be around writing a piece of content around how do we detect when it’s gone bad, what does it look like when it’s bad, can we salvage it, the way we find out how we structure this piece of content is by looking at the existing content that’s ranking. So, there are competitor sites and looking at how we can outdo them, how we can create better content.

Okay, so we only really need a really brief brief. I’ve got here a new content piece discussing if sourdough starter can go bad, how to know, and what to do, etc. Now, the next thing we want to look at is what content types would this content topic be suitable for, and in my opinion, it would be a great video and blog post or content piece to start with.

Now, references are where it gets interesting. This is where we find out what’s ranking already. I will go to Google and do a Google search for that exact phrase and look at the top three to five results, kind of compare them, and get a feel for what’s ranking already. Now, the first one, in my opinion, is the best, and it’s no wonder why it’s ranking number one. So, you see, this one was written in March 2018, so it’s pretty old. It’s got over a thousand comments, so it’s got a lot of authority and engagement, and it’s got lots of shares on this piece of content, so it is going to be a hard one to outdo or outrank. I can see already that doesn’t mean we shouldn’t try.

Now, let’s have a look at the content that Bob, sorry, has provided. She’s got a lot of written content, some really high-quality, high-res images, she’s got some good subheaders, the type of things that will kill it, how to detect if it’s gone bad, troubleshooting. It’s not overly long, but it’s well presented, it’s long enough, it’s got some good images, but what it doesn’t have is video, so that’s where we might be able to get a leg up.

Let’s have a look at the other two pieces of content. So, this one’s on Baking Needs, big old picture, a bit of content, quite a bit of written content on this one. And let’s have a look at ranking number three. This website, in my opinion, doesn’t present as well as the other two. It’s a very short piece of content. My gripe with the last two websites is that they’re highly plastered in ads. I can’t scroll without seeing five or six ads throughout the content. I think a really well-written piece of content with associated images and video would potentially rank quite high. So, let’s provide these three websites as our references because they are the ones that are ranking. Just for clarity, providing a reference just means I want the client to have a look at what’s already ranking and provide a better, more comprehensive piece of content. I don’t want them to copy that content; I don’t want to base their content on it; I just want to purely as a reference to see what they have to outdo.

Now, typically in a content plan, you have a due date, and the last column is our published URL, so when we’ve got that piece done, where does it live on the internet? Is it on your own site, is it a video on YouTube, is it both, is it a guest post on another site? I just want to know where it is because next up, I want to make sure it’s well SEO optimised. That is the process, and you repeat that for each of these core content topics all the way down, and each of them will have a slightly different brief, content types that are relevant, and you go through them one by one, slowly pump them out, and once you’ve completed this process, you’ll have a website that covers the core content that people are actively searching for. And if you do it properly, if it’s well written, if it’s well optimised, if it’s an awesome video, it will start ranking in Google search, and you will start seeing people come through to your website.

Now, it’s up to optimising your website after that to make sure it’s conversion-friendly, conversion-optimised, and that we’ll look at in another video.

A common problem: You’ve built a website, but nobody’s coming to it. How do you find out what search terms people are using to optimise your site to get those people to your site? Well, I’m going to show you how right now.

Backstory: I have a friend who has started a website during lockdown. She wants to know how to get people looking for sourdough to her website to sell them some sweet sourdough.

Step one: We find out what people are actually searching for. Now, the way we do that is by using Google’s very own Keyword Planner tool. It’s free, it’s available to anyone, all you need is a Google Ads account. You don’t have to run any ads, you don’t have to spend any money. As long as you have signed up for an account, you have access to this tool. I want to find out what search terms people are actually using when they’re looking for sourdough. All I do is put in my root keyword there, make sure I’m searching within Australia because that’s all I’m interested in at the moment, and I click “Get results”. The Keyword tool does its magic and comes back with a cool little list of keywords here, and each of them will tell you how many average monthly searches each keyword is receiving. By default, it’s going to be ordered by relevance. Now, what I really want to do is get all of the data for all of these and have a look at them myself and filter out which ones I think are actually great, which ones don’t apply, which ones are worth targeting.

What I’m going to do is download all of these keywords and then start filtering them. We’ll select all 523 keywords. Now that we’ve added all of these keywords to our plan, let’s go to the plan overview and see what we can expect per day for our plan overview. Over the next 30 days, we could expect to get 3,000 impressions, 37 clicks, at a cost of $62 if we were running Google Ads. But we’re not going to run Google Ads; we’re going to get this traffic for free. The forecast over the next year: they expect these keywords to get more search volume. Let’s go and download this information and start manipulating it.

What I like to do is download it to Google Sheets. Okay, so now we can open our sheet, and here is all the data that we saw in that really nice presentation before, just spat out as rows and rows of data. What I want to do with this is grab all the keywords. I know I don’t need this stuff; it’s just the summary of all keywords, so I’m going to delete that. I’m going to delete the empty columns because they provide no value, and what I’ll be left with is the data I need to start making decisions on which keywords I want to target for my website.

Now, basically, all we want to be left with is the estimated impressions in Google search and the estimated clicks. Now, we can take our keywords and our estimated clicks and impressions, all 523 of them, and then we can add them to another sheet I have prepared earlier, and we can start filtering. Let’s apply a filter to these guys and let’s order by impressions, highest to lowest, and then we’ll get a feel for what kind of keywords get the most volume in Google search. I just have to format these columns to be number format, and now I have ordered it by estimated impressions in Google search, and we can see the most popular keywords.

“Sourdough” by itself was going to be really hard to target by itself, but then we can get into more specific key phrases like “starters,” which is what you start with when you make sourdough. Obviously, the bread, “Sourdough machines,” “cultures” (I think that ties back into “starters”), “cooking it,” “buying it,” “buying it from Coles,” “buying more artisan versions,” “making it yourself” — so all of this is really great information, and these are the keywords we want to optimise our website for.

But there’s one more source of data that I want to have a look at, and that is: What are the kind of questions people are asking around sourdough, more specifically than these kind of base search terms? And the way I do that is to use a different tool called Answer the Public. I’ll provide a link in the description, but this is it. With this creepy-looking guy kind of approaching us, we can see a report in his face, so let’s get rid of him ASAP and put “sourdough” in as our search term. I’m again looking in Australia and in English.

Now, this is an awesome tool. It gives us the questions, prepositions, kinds of search terms that people are using around the core phrase of sourdough. It gives us this cool kind of visualisation, but effectively that’s useless unless you want to print it out and put it on your wall or something like that. Let’s have a look at the data. “Is sourdough bread healthy?” So these are the “R” questions, these are the “Can” questions, these are the “How” questions: “How sourdough-powered bread is made,” “How sourdough starter works.” Now, these question-based results are super, super, super important for developing the content on your website that is going to support the key phrases that we want to rank for, and is going to drive lots and lots of people to your website because they are looking for specific things that you can write content on, that you can film videos for, that will drive traffic to your videos and to your website.

Let’s download the CSV; let’s just take the suggestions, that’s fine. Now we’ll put this in a separate tab. Now, an additional step you can take is to try to get volume for these, but when we filter volume in the Keyword Planner as well, at the country level, it’s super difficult to get actual results because you’re so far down the long tail of the keyword that Google is actually not going to give you search volume on those. But it can be interesting to see which ones do give you search volume. Just restart our planner tool and get volume and forecast for our keywords. So this time, a little bit different than last, we’re not putting one keyword in; we’re putting all of them in that we got from Answer the Public, and let’s see what it comes back with in terms of volumes.

We’ve got our keywords in there, but we can see very few of them actually have any data. Let’s change our location from Australia to most English-speaking countries with search volumes, so we’re looking at things like the United States, United Kingdom, Canada, Australia, New Zealand, and let’s see what kind of volume we get with that kind of targeting. So now, what I hope to find is some of the questions: “Is sourdough gluten-free?” There’s a big one. “Can sourdough starter go bad?” There’s a big one. So the questions that actually return search volume numbers in terms of impressions, they’re the ones that are going to be super important to go after. Our first day, low-hanging fruit that you can specifically target with well-written content and/or well-produced video.

So let’s open that up in Google Sheets. Okay, now I just have my keyword, which should be my question, my estimated clicks, and estimated impressions. In this case, you probably need impressions because there’s not going to be a super high amount of clicks at the question level. Let’s go back to our Answer the Public data and maybe make a new little couple of columns over here. Let’s filter these bad boys in order, so we’ve got to format this as a number again, and then put them in order, which is Z to A.

Alright, now we have a prioritised list of question-based keywords that we can start to build a content plan around. But what we want to do with our top search volume core keywords is start to put them into themed buckets and start to look at how we can optimise our existing website for the keywords, which keywords belong to be targeted on which pages, and which pages we’ll need to add to our existing website to take advantage of the available search terms, try to get those search rankings, and visitors to our site. We’ll have a look at that in the next video. Stay tuned and make sure to check it out.

I’m going to show you how to use Answer the Public, a free search engine that works as a question-based search engine, to generate hundreds of content ideas, all at zero cost.

Step 1: Navigate to Answer the Public.
Step 2: Put in your topic, whatever you are showing or niches that you want to generate content for.

I’ve had a really cool topical demonstration idea. Maybe you’re a health industry website, and you want to get information out to the people that are searching for it right now, and you want to know what people are actually asking about the C word right now. So, we run our little search in Answer the Public and we get a bunch of responses. We’ve got 78 questions, 54 prepositions, 37 comparisons, and overall, 208 queries that we can have a look at and see if we can write some content based on these questions people are actively searching for answers for. It’s a great way to optimize your site for Google search traffic.

So, by default, it shows it in really pretty little visual graphs, but we can break that down a little bit easier to look at in this table data format. This is why we can sort different types of questions. The top ones at the moment look like it’s like “Corona versus cases dropping,” “Can virus live in water,” “How has it started,” “Where does it come from,” “What does it mean for the global economy.” It’s against a whole range of different topics generated from just that one keyword there.

So, let’s have a look at the prepositions now, put them in the data format. “Can you get it twice,” “Can I visit my family,” “Info kids,” “The rate of infection and slowing down,” “When will it end,” “Is it near me,” all that kind of good stuff. Comparisons would be a really interesting one to have a look at. So, we’ve got an end kind of keyword contributor here: “C word and asthma,” “and diabetes,” “and pregnancy,” “and children.” So, some very specific kinds of assertions people are looking for information for.

And then, if you just go to alphabetical, it’ll give you pretty much everything it’s dug up based on that query and search term. So, again, super easy way to find topic and content ideas, all free. All you need to do is punch in your keyword, and then you get a bunch of replies and topic ideas that you can actually download to a CSV, and maybe sort out into categories, ranked by preference and writing order, and maybe even staged a funnel. You can pop them into just a shared doc or Trello board or something like that. But yeah, that’s one way to really quickly get some really great content ideas for queries that people are legitimately searching for answers for. So, go there and get writing.