While the move from UA to GA4 appears to be imminent as far as the Google roadmap is concerned, we felt that there were likely to be sufficient numbers of sites operating on UA to require a thorough resource dealing with the platform.
In this article, we’ll be trying to cover everything you need to master the art of Google’s Universal Analytics. However, we’re always happy to fill in the blanks should a reader encounter a situation they can’t work their way through. Let us know!
What is Google’s Universal Analytics?
Google Analytics is a platform that allows its users to track interactions with web properties, track goal completions, user and session level metrics, eCommerce performance and more through the addition of a code snippet in the head code of their site.
Following Google’s acquisition of Urchin (now remembered only as part of the Urchin Tracking Module, UTM), in November of 2005, Google launched Google Analytics which, as of 2019, is the most used analytics service online. Google’s Universal Analytics is its third iteration and is running in parallel with its fourth iteration (known as GA4).
How to add Google Analytics to your site
Note: – We’re going to go with WordPress here as it’s the most common platform, but the process is much the same.
First of all, you’ll need to sign up for a Google Analytics account by clicking on the ‘Start for free’ button on the site. Select the ‘Admin’ option (the cog icon) and then click ‘Create Account’.
You’ll then need to name the account and choose the level of data you share with Google.
You’ll then need to create a property (using the ‘Create Property’ button), add some business information (time zone and local currency).
Click the ‘Show advanced options’ below the property set-up and then set the slider for ‘Create a Universal Analytics property’ to on (blue highlight). Below the slider, you’ll then need to add your website address and choose whether to create both a GA4 and UA property, or just the UA property.
You’ll then need to add some further business information (industry and business size), before accepting the platform’s Terms of Service and Data Processing Amendment. This will then generate your tracking ID (which will begin with ‘UA’).
Hopefully, your web developer will have added a section to your site options that will allow you paste your tracking code into, but if not, you can add a plugin like ‘Header Footer Code Manager’ for free and add a site-wide header snippet there:
Once this is done, it will take approximately 30 minutes to begin data collection.
How Google’s Universal Analytics collects data
Google begins the tracking process (provided you have the tracking code on your site) with something they refer to as a ‘hit’ – this is a URL string filled with useful information encoded in parameters unique to your user.
These parameters contain information such as:
- Browser language
- Device type
- Screen resolution
- Traffic source
- An Analytics ID (to associate the hit with the right account)
- The name of the page they’re viewing
- Much more
These hits are broken up into several different categories – the three most common being:
- Page views: – triggered when a user loads a page containing the tracking code. Each time a user loads a page, a new pageview hit will be sent.
- Events: – allows you to track when a user interacts with particular elements of your site. This includes things like a click to play a video, a specified URL, or a product carousel. These pass four parameters in the URL: event action, category, label, and value. You can then use these parameters to categorise interactions when reportreporting
- Transactions: – also called an “ecommerce” hit, these pass data to Analytics about any eCommerce purchase including the product, transaction IDs and SKUs. If you’ve set up Enhanced Ecommerce, you can also pass data such as product category, whether items have been added or removed from a basket, and how many times users viewed a product on a website, all of which hold potential for the creation of remarketing segments.
How Google’s Universal Analytics processes data
Once Google Analytics receives the ‘hit’, it will begin to process and categorise the data. It does this (on a basic level) in the following way:
- Initially, Analytics identifies whether the hit is from new or returning users (based on unique cookie IDs).
- It then categorises the hits into sessions – periods during which the user engaged with the site.
- Analytics will then join this tracking code data with those from other data sources.
Creating a measurement plan
One of the key considerations when looking to master your Google Universal Analytics account is knowing what you need to be measuring and why. This is referred to as a ‘measurement plan’ and will help you to determine whether your online activities are succeeding.
This will include what Google refers to as ‘macro-conversions’, representing the top-level goals of your business (we’ll provide some more granular KPIs for SEO in the next section) and ‘micro-conversions’ which can be thought of as stepping stones toward a macro-conversion (downloading a brochure, or signing up to a mailing list, for example).
Google itself provides the following examples:
- eCommerce sites: – a macro-conversion could be a purchase, while a micro-conversion may be subscribing to a newsletter.
- Lead generation sites: – a macro-conversion might be a contact form, while a micro-conversion may include following the site on social media.
- Content publishers: – macro-conversions may be engaging with a particular amount of content, while micro-conversions could be clicking into an article.
- Online information and support sites: – macro-conversions might be navigating a guided support flow to solve an issue, a micro-conversion may be rating a support article.
The most important SEO KPIs to track and report on
There is a reason that there are so many articles on vanity metrics – there is a tendency, and not just in marketing, to report on the metrics that are improving, even if those metrics have little or no impact on the brand’s overall objectives. The proliferation of ‘line-goes-up’ social media posts say little about the success of SEO projects without context – but with a little help, you can know what to look out for, regardless of your experience levels.
What is an SEO KPI?
An SEO KPI (key performance indicator) is an agreed upon measurement that offers insight into the performance of specific SEO tasks or projects; typically, KPIs are agreed on in advance of a project and used as pass/fail goals for the work.
5 of the best technical SEO KPIs
Technical SEO is the group of processes and techniques that deal with predominately unseen content and practices – the information we pass to algorithms, the way that visible content is organised. While there are dozens of projects that fall under the umbrella of technical SEO, most of them can be monitored using a crawler (Deep Crawl, Screaming Frog etc.), Google Search Console (GSC) and Analytics. The following are five of the best to track and report on to monitor a site’s progress:
- Coverage: – This refers to how much of your site is indexed as a percentage, as well as metrics like ‘crawled currently not indexed’, ‘discovered currently not indexed’ and ‘duplicate, submitted URL not selected as canonical’. These can be found in Google Search Console and reveal how well your site is performing in the overall index and allows you to draw inferences as to how important Google perceives your site as being.
- Core Web Vitals: – Not because of the upcoming CWV update or because of any specific ranking benefit (though it doesn’t hurt), monitoring your performance here reveals how well your site performs technically across a number of different metrics. You can find pretty good reporting options on this by connecting a crawler with an API, or using CWV manually.
- Active pages: – This report should show which of your pages are receiving traffic as a percentage of the whole. While we’re not too worried about crawl budget outside of massive eCommerce sites, the pages on your site which receive no traffic should be redirected, rewritten or, if they are completely irrelevant, return a 404. As such, this is one of the metrics it is nice to see dropping each month.
- Response codes: – 404s are a cost of good SEO – there will be a proportion of your pages which are no longer relevant. The problem here is going to be high proportions of non-200 codes, lengthy redirect chains and loops. Again, you can get reports on these from most good SEO tools and from all of the crawlers I’m aware of.
- Metadata: – Metadata is the data you use to describe your data, and covers things like page titles and descriptions, your schema, alt attributes and any other metadata your site may use (a lot of it, like meta-keywords, tend not to be used anymore, but if it is: make sure it’s right or removed).
5 of the best SEO KPIs
By ‘best’ here, I just mean these are some of the metrics that even the most basic SEO service should be reporting on – whether it’s just tweaking your meta-descriptions or a full overhaul, you should be tracking and reporting on the following:
- Organic sessions: – simply put, this shows how effectively you’re winning traffic in the SERPs, so should feature in any reporting you make or receive. While it doesn’t give you the full picture, it does provide a top-level indication of how well your overall SEO is going. You’ll find this information in Google Analytics.
- Total impressions (unbranded): – ‘total impressions’ tends to be one of the most popular metrics for the ‘line-goes-up’ charts mentioned previously that are shared without context – but without a brand filter, it says little about your overall SEO performance which, for the most part, is focused on winning new business rather than appearing for searches already likely to win a click. You can find this information in Google Search Console.
- Click through rate (unbranded): – just as it’s important to know that new customers are seeing your site in search, it’s also important to know how many of these are clicking on your website and this can, again, be seen in GSC. While the organic click through rate is never huge, there are likely issues if your site is only earning one click for every 10,000 impressions.
- Average position: – it’s not conclusive evidence, but your site’s average position for key terms (which you can find in GSC or any of a number of SEO tools including Semrush, Ahrefs, AWR and more) is a good indicator of how your SEO is performing.
- Session duration: – this, along with other timed metrics (time on page, for example) provide an indication of how engaged your users are – and, therefore, offers some insight into how effective your conversion process is. This and other timed metrics can be found in Google Analytics.
3 of the best off-page SEO KPIs
Off page SEO metrics are things which are slightly more difficult to control, but while you might not set overly ambitious targets (unless you’re specifically undertaking a relevant project), they should always feature in your reporting to give you an indication of your website’s overall profile.
- Referral sessions: – whether you’re tracking social referrals or sessions from third party websites, you can see – using Google Analytics – the importance of various publishers, monitor the performance of earned links and different platforms to your site’s performance.
- Quality of backlinks: – while things are changing, links are still a primary indicator of performance in search, so the quality of links (discoverable in many SEO tools, including GSC) is a good metric to measure over time.
- Link churn: – following on from the importance of links, the churn of links is also a valuable source of insight – this is also not a passive measure; by keeping a track of link churn you can look to try to recoup lost links and, in the process, improve relationships with publishers, working in a similar way to monitoring for unlinked mentions.
Why track SEO KPIs?
There are a number of reasons to track SEO metrics and set KPIs, but the most important is that it allows for improvement. It shouldn’t be a matter of too much consternation to miss one or two KPI targets – the tracking of them alone provides the necessary information to help you achieve your goals in the future. Tracking the ten here as a start, for example, will provide insight into the technical and overall SEO performance of your site and keep you honest as you progress.
Analytics and Content Marketing
To those outside of the search and digital marketing industry, or those that are new to it, content marketing can appear a little woolly – a practice big on ideas, but short of facts – but proof of concept is there for those who look for it, and there should be an immediate distrust of anyone who simply answers ‘it’s hard to measure’ when asked for results.
The following should provide the basics to track the success of your brand’s content, allowing you to build on the data gathered for future campaigns. While there are more metrics you could use and more methods, this should give you enough to set up your campaigns for success in the short term.
Landing page analytics
Accessed by selecting the following menu path: Behaviour>Site Content>Landing Pages, the below image shows some of the best metrics for measuring the success of your content (and is included in the standard view).
- Sessions: – Sessions is total number of visits to the specified subsection of the site (here reached by searching ‘/blog’ to give a view of blog traffic). It details the overall number of visits, including returning visitors. It has the obvious benefit of indicating your overall traffic – and if tracked in the graph commonly found above this table, it can show how much your traffic improves alongside a content strategy.
- % New Sessions: – As above, but this metric excludes returning visitors and so is able to give you an indication as to the new consumers your content is attracting. Clearly it is desirable to retain some repeat traffic as it indicates that your content is developing a following, but this metric can offer a fantastic insight into how your content is developing your traffic.
- New Users: – This is the number of new visitors, rather than as a percentage. Easier to parse at a glance as a simple figure, this metric shows how attractive to new audiences your content is – perhaps revealing how well a piece of ‘How to’ or instructional content is answering the search query it is aimed at for example.
- Bounce rate: – This is a great metric for measuring how well your content feeds in to other pieces – showing the percentage of users that visit only one page of your site before exiting. It can also show you how well your ‘similar content’ lists or CTAs are working, as these are the main tools you will use to draw consumers on through the site as part of your path to conversion.
- Pages per session (PPS): – This offers an insight into what consumers are doing on your site and potentially how well you’re capturing their attention. PPS will generally be much higher for eCommerce sites, but equally a site looking to measure the success of a content strategy will want a high average as it indicates that they are continuing to read/watch/listen past the point of finishing what originally drew them to your site.
- Avg Session Duration: – The ideal length of this will depend upon how long your individual pieces of content are and how many pages per visit your consumers are visiting, but again the best result is always longer. If a piece of long form content is only receiving a minute of attention, for example, it may be worth revisiting the page to see if you address any issues with the content or layout.
- Goal Conversion Rate & Goal Conversions: – Again, these will depend on what goals you have in place, how you’re using CTAs in your blog and other things, but essentially these metrics allow you to assess at a glance how well your content is performing against specific goals – which can, again, be tracked over time to measure progress and identify areas for improvement.
Though we would recommend a more thorough method of attribution modelling, as a quick overview the standard first and last interaction attribution can give you a good idea of how your content is performing on various platforms.
First interaction attribution shows which platform is serving your present content strategy best with a view to reaching new users, and allow you to rethinking approaches for platforms which are underperforming.
First interaction is indicative of a conversion which began with a specific referral from another site and, though there may have been many interactions since, the cookie was placed during this initial visit, while the conversion took place within a set range of time (which can be amended to suit your brand’s buying cycle).
Similarly, last interaction shows the number of conversions and their value from a visit’s last interaction before conversion with various platforms. Though the value of these conversions is obviously important, the main use in this instance is to monitor the performance of your content strategy. You can then infer from various metrics which content and channel has proven a success and look to improve underperforming channels and campaigns.
How to achieve a clean view
Another important aspect of mastering analytics is ensuring that your data collection (and therefore your decision making) is not hampered by bad data. For that reason, you’ll need to address spam data as soon as you can after setting your KPIs.
What is GA spam?
GA spam appears in a number of forms, but the end result will generally be the addition of fake sessions which artificially inflate your reports, make conversion rates look lower and, more generally, making a mess of things.
In this example, fake sessions show up within your ‘Language’ report (found under the ‘Geo’ dropdown in the ‘Audience’ reports section of your GA account).
In a healthy view, you’d ordinarily see a variety of language types in the ISO 639-1 format (i.e. “en-gb” & “en-us”).
When affected by language spam, you will typically see a message has been injected such as the following example which plagued accounts during the 2016 US Presidential campaign:
As you can see in the above example, this spam language label registered 526 fake sessions, which will give your reports an artificial traffic increase (and for smaller sites could completely ruin the integrity of its data). Failing to deal with this can result in artificial seasonality, and make subsequent months seem poor on a month-on-month basis.
Fake landing pages spam
In this example, fake landing page URL’s will show up in the ‘Landing Pages’ report (found under the ‘Site Content’ dropdown in the ‘Behaviour’ reports section of your GA account).
This is usually an easy one to spot, as they stick out like a sore thumb – as in the example below:
As with the language spam example, this will add fake sessions to your ‘Landing Pages’ report, skewing your reporting numbers, conversion and bounce rates, etc.
In this example, when looking at your ‘Referral’ report (found under the ‘All Traffic’ dropdown in the ‘Acquisition’ reports section of your GA account) you’ll see the offending domains listed. The good news is, they’re easy to spot.
Typical examples in the past have included: “abcdefgi.xyz”, “social-buttons.xyz” and “rank-check.online” but there are an infinite number of variations that tend to give themselves away by looking spammy from the word go. You can also sort by ‘Bounce Rate’ to show referral sources with a 100% bounce rate; this will typically contain your spam referrers.
As well as adding fake sessions to your report, this type of spam is designed with the intention of getting you to visit the offending sites where you’ll be presented with products for sale and display ads. With this in mind: Don’t visit that site!
How is it added to my account?
The spam to be found lurking in that dark corner of your GA account is usually injected in one of 2 key ways. These methods are responsible for the 3 types of spam we have listed above.
So-called because there is no genuine visit to your website with this one. This method is responsible for the majority of GA spam attacks, and simply sends data directly to Google through the use of the “Measurement Protocol” which was intended for developers to send raw user interaction data to GA’s servers.
With this one, your website is crawled by a spambot impersonating a user (in a similar way to how major search engines crawl your website to index your data). The spambot exits your site, and leaves a record that will appear to be a genuine visit in your reports, even adding fake session times and bounce rates in its wake.
It is important to note that these spambot’s typically tend to ignore exclusions you may have added to your robots.txt file to try and counter this problem.
How can I remove it?
All of the fake data in your GA account caused by the spam types discussed in this article can be removed with the addition of filters to your default reporting view.
Don’t worry, it’s not as complicated as it sounds and we’ve run through each option in a step-by-step format below.
It’s important to add any new filters in a new reporting view to allow you time to test them out and ensure they don’t strip out data they shouldn’t be. Once you add a filter to a view within your analytics account, the data it strips out going forward will be lost.
Valid hostnames filter
One way of removing fake referral traffic from a GA account is to set up a “Valid Hostnames” filter. This will allow only genuine referral traffic through to your reports and eliminate ‘Ghost visits’. Genuine referrals should record the hostname as your own domain rather than a spammy domain name or “(not set)”.
Navigate to the ‘Network’ report (found under the ‘Technology’ dropdown in the ‘Audience’ reports section of your GA account).
Set a date range which covers a long period of time (say the last 6 – 12 months) to ensure you uncover all variations of fake hostnames).
Change the ‘Primary Dimension’ to ‘Hostname’ to get a list of all of the hostnames that have your referral traffic claims to have arrived at.
You will now have a list of all hostnames, valid and fake alike. You should see your primary domain listed as one of these hostnames and other properties where your GA tracking code has been added.
This could include subdomains, IP addresses which you know to be yours, payment services and shopping carts, caching services, Google translation services and content delivery networks.
Make a list of all of the valid hostnames that you want to record GA data for.
Be careful to investigate any hostnames you are unsure of fully before adding them to an exclude list.
Your list should now look something like this:
Combine the valid hostnames into a regular expression filter (REGEX) that can be used to set up an “Include” filter.
We will be using the “|” (pipe) symbol to separate each hostname and will need to utilise a “” (backslash) between each full stop and hyphen (-).
The resulting REGEX filter pattern from the hostname list above would therefore appear as follows:
Set up a new reporting view to allow testing of this filter for 2 – 4 weeks, then go to the ‘Admin’ settings for your view and select the ‘Filters’ option in the ‘View’ column. Now click on the ‘Add Filter’ button:
Choose the ‘Create New Filter’ radio button and give your filter a meaningful name which explains what it excludes at a quick glance.
- Choose the ‘Custom filter’ type and the ‘Include’ radio button.
- Under the ‘Filter Field’ dropdown, search for ‘Hostname’ and select it.
- Now, enter your ‘Hostname’ regular expression pattern in the ‘Filter Pattern’ field.
- Do not select the ‘Case-sensitive’ box or any of the additional radio buttons below.
- To get a view of how the filter would affect your data over the last 7 days, click on the ‘Verify this filter’ hyperlink at the bottom of the page (this may return no result if the numbers are small).
- If you get a result, check the list of hostnames this filter will exclude to ensure that nothing is being stripped out in error.
Your new filter should look like the below:
Once you have successfully created your new filter you should monitor its success over the next 2 – 4 week period before making the decision to copy it over to your default reporting view.
Spam crawlers filters
To tackle targeted spam visits made by bots and to capture spam from those who have figured out your hostname, you will need to set up ‘Spam Crawler’ filters which contain a REGEX filter pattern featuring the list of persistent offenders.
This will need to be periodically updated to ensure it continues to include all domains that are actively spamming your GA account, but combined with the ‘Valid Hostnames’ and ‘Language Spam’ filters, will give you a clean dataset.
Make a list of the offending domains currently clogging up your referral reports and add any typical examples being reported by SEOs to use as your filter pattern. Check out great posts which feature the latest filter patterns you can utilise such as this one from Analyticsedge.com.
There is a character limit in relation to the filter pattern box, but we’ve been able to add up to 800 characters before hitting it.
Your filter pattern should look like a longer version of the below example:
Select the new reporting view you’ve just set up to test your ‘Valid Hostnames’ filter, then go to the ‘Admin’ settings for your view and select the ‘Filters’ option in the ‘View’ column. Now click on the ‘Add Filter’ button as you did for your ‘Valid Hostnames’ filter.
Again choose the ‘Create New Filter’ radio button and give your ‘Spam Crawler’ filter/s a name.
- Choose the ‘Custom filter’ type and the ‘Exclude’ radio button.
- Under the ‘Filter Field’ dropdown, search for ‘Campaign Source’ and select it.
- Now, enter your ‘Spam Filter’ REGEX pattern in the ‘Filter Pattern’ field.
- Do not select the ‘Case-sensitive’ box or any of the additional radio buttons below as before. Again you can get a view of how the filter would affect your data over the last 7 days with the ‘Verify this filter’ hyperlink.
- Check any results to ensure you are happy with what is being stripped out.
Your new filter should look like the below:
As was the process with your ‘Valid Hostnames’ filter, you should monitor its success over the next 2 – 4 week period, copying it over to your default reporting view once you are happy that it is effective.
Top tip Utilising GA’s built-in bot filtering function will exclude hits from a variety of known spiders and bots. To enable this, select the ‘Admin’ header nav item in your GA account, select the view you want to apply this to from the ‘View’ dropdown and click on ‘View Settings’. Tick the box under the ‘Bot Filtering’ heading and you’re done.
What about my historical data?
If you’ve set up the spam filters suggested above and found them to be effective, you might be wondering how you can also get a clean set of historical data.
Don’t worry, this is possible too and it’s really easy to do by setting up a new segment which your spam filters can be applied to.
Go to the ‘Reporting’ view in GA for your preferred view and select the ‘Add Segment’ option:
Select the ‘New Segment’ button:
Now select the field ‘Conditions’ under the ‘Advanced’ heading on the left-hand side of the form.
After you have done this, give your segment the same name you gave to your new language spam filter to make it easy to find and select going forward.
Make sure the drop-down options next to ‘Filter’ have ‘Sessions’ and ‘Exclude’ selected.
Change the drop down underneath that defaults to ‘Ad Content’ to ‘Language’ and the drop down that has defaulted to ‘contains’ to ‘matches regex’, then paste in the same filter pattern you used for your new filter (with a version you can copy & paste below it):
Check that the segment is working by clicking on the ‘Preview’ button and check the results that appear on the right-hand side of the page to make sure the percentage of sessions you’re seeing matches your expectations.
The filter should look like the below example:
Creating custom metrics and dimensions
Custom dimensions and metrics, like their defaults, allow you to report on specific characteristics of your users and their behaviour (within the Google Analytics data you’ve collected). However, custom dimensions and metrics allow you to collect data customised for your business.
Setting up custom dimensions
In your Admin section, select the property in which you want your dimension applied. Click ‘Custom Definitions’, then ‘Custom Dimension’, then ‘New Custom Dimension’.
You’ll need to name the Custom Dimension (make it as clear a description as possible), and then define its scope. Dimensions can have a scope of ‘hit’, ‘product’, ‘session’, or ‘user’.
Following this, you’ll see an overview screen where you can see all of the custom dimensions you have set up in that property. Similar to goals, custom dimensions are assigned an index (or slot number) which are assigned in the order you created them.
Setting up custom metrics
The process is similar to creating a dimension – again, from your Admin section:
In the PROPERTY column, select ‘Custom Definitions’ then ‘Custom Metrics’. Click the ‘New Custom Metric button’ and add a unique and descriptive name. From the ‘Formatting Type’ dropdown, select an Integer, Currency, or Time:
- An integer can be any number.
- The currency type will match the view settings (i.e. GBP, USD, Yen) and should be entered as a decimal.
- Time should be specified in seconds, but will be formatted as hh:mm:ss in your reports.
Once you’ve selected a formatting type, check the ‘Active’ box to start collecting data straight away, then click ‘Create’.
As with the creation of a custom dimension, you’ll need to update your tracking code to ensure data is collected.
Creating a custom dashboard
While the standard dashboard may be perfect for what your brand needs, the initial set up is audience focused – giving top level session information (total users, total sessions, page views etc.). However, the chances are you will want augment this view, or start from scratch, to ensure the information you want to see is immediately available at a single click. This is when you’ll need to look at creating a custom dashboard (or branching out to Google Data Studio).
In order to create your custom dashboard, first click on the ‘Customisation’ option (in the left hand menu):
Then select ‘Dashboards’ which will then give you the option to select ‘Create’:
After which you will see the following options:
The ‘Blank Canvas’ option has no widgets at all, as you would expect, while the ‘Starter Dashboard’ will have a default set of widgets which you can then add to or subtract from as your needs require. You should give your dashboard a descriptive name (this may not seem overly important at first, but as your needs and confidence grows with analytics, the number of dashboards will no doubt proliferate).
Dashboards can have one or more of the following varieties of widget:
- Metric — a numeric representation of a single selected metric (sessions, bounce rate etc.).
- Timeline — a graph of the selected metric over time (comparable to a secondary metric).
- Geomap — a map of a selected region, with a specified metric plotted on the map.
- Table — up to two metrics describing a selected dimension in table format.
- Pie — a pie chart of a metric grouped by a dimension.
- Bar — a bar chart of a metric grouped by up to 2 dimensions.
Dimensions describe characteristics of your users, sessions and actions – such as geographic location, browser or device type for example.
Metrics are quantitative measurements, describing a characteristic of sessions – such as bounce rate, session duration, goal completion, to name a few.
It must be noted that not all dimensions and metrics are compatible. For a metric to work well against a dimension, each must have the same ‘scope’ – i.e. that they should deal with the same overarching concern – be that users, sessions or actions.
Choosing your widgets
In order to ensure your custom dashboard does what it needs to do, it is important that you know what you want to measure and against what. Determine what you want to learn from the figures collected, and then select the widgets which best represent these aims.
Configure the dimensions, metrics and other options to your taste and add any necessary filters to include or exclude any data as you see fit (excluding hits from your own or building’s IP address, for example) and name each widget. Again, be descriptive of the data it captures.
One thing to note here is that a filter added to a dashboard only alters the data displayed in that report or dashboard, rather than a ‘view filter’ which permanently changes all incoming data.
These widgets can, in future, be segmented to allow you to analyse subsets of your data. Dashboards can be edited at any time using the ‘customise dashboard’ option.
There are three major types of segmentation – by ‘users’, by ‘sessions’ and by ‘hit’ (interactions including page views, transactions etc.). Segments are filters which do not change the data they impact, remaining active only until you remove it.
Segmenting your data at this or later stages, will allow you to produce reports that focus on specific data subsets important to your brand – such as how many times a certain action is undertaken by specified user types within time or location ranges for example. You may only have a maximum of four segments applied to a single report.
Creating a custom goal
While it’s relatively easy to track actions such as purchases, there are some useful to know consumer interactions with your site that Google Analytics can’t track without you telling it to.
What are custom goals?
Custom goals are an admin option in Google Analytics allowing for the tracking and monitoring of user defined consumer interactions with a website. This has obvious implications for monitoring the progress of your SEO work, but here’s how to do it and why you should.
How do you set goals in Google Analytics
In order to set a goal in Google Analytics, from your chosen view (I’ll cover views a bit later), navigate to the ‘Admin’ section in the left-hand menu bar. The third column on the admin page is titled ‘view’ and the third option down in this column is titled ‘Goals’.
In the ‘Goals’ section you will see a red button (+NEW GOAL), clicking on this will take you to the ‘Goal set-up’ screen where you can begin defining your goal.
What are the custom goal ‘templates’?
The templates for Click Consult’s stated industry (these do change from industry to industry provided you have selected one, but remain mostly alike) are the following:
What do custom goals do?
Custom goals allow you to augment your analytics reporting with data regarding non-standard, brand important interactions with the website – thereby permitting a better ‘big picture’ analysis of online performance.
Unlike the revenue tracked through checkouts, revenue goals are set up to track conversions with a potential monetary value – such as a sign-up for a class or event. The revenue template defaults to a ‘destination’ type in the ‘Goal description’:
This ‘type’ of goal is registered when a consumer reaches a designated page – generally on completion of a form. By reaching this page, Google Analytics can safely assume that the desired action (the form completion) has been achieved and a conversion is recorded.
You can (as with all goals, though it is more relevant to this template) attribute both a value and a funnel to the goal (i.e. a monetary value that the goal represents and a predefined marketing funnel into which the action falls.
Acquisition goals are split into two sub-categories – ‘create an account’ and ‘submit content’, the former for signups and accounts; the latter for uploaded files. Both, however, allow you to track information added to your site.
The acquisition goal also defaults to the destination type, allowing any upload or form to register a conversion via the redirect page as per the revenue goal. While the value option is not really necessary in most cases for this goal, if there are calculations in place (such as an average lifetime value of an account or similar), the value can be added.
Made up of four further destination type goals, the enquiry template is predefined for a non-gated variety of page – the reviews page of your site, an events calendar or the printable version of a page.
While this type of interaction may not be easily attributed a value – it may be better served by causing the consumer to enter or progress through a marketing funnel (served tweaked or personalised content on their next visit to the site, for example).
The ‘engagement’ template is made up of a pair of both the event type and destination type goals: the ‘share/social connect’ and ‘contribute content’ types representing the former; the ‘get alerts’ and ‘sign up’ representing the latter.
These event types represent useful metrics to track for brands that seek consumer interaction (picture uploads, document uploads – if, for example, you’re running a crowd sourced blogging site for example) or are looking to measure the social shares of their content (even for those buttons that still report numbers, having them easily visible in an Analytics report is useful), while the destination goals fulfil essentially the same purpose as those in those other templates mentioned above.
The custom goal is the one that most brands will look to use (and the only one available if you do not declare an industry). By allowing you to select any ‘type’ for your goal and, therefore maximally customise the goal at the ‘goal details’ set up stage, it ensures you are building the right ones for your brand.
Goal types are fairly self-explanatory, falling into one of four varieties of tracking:
- Destination: – A goal will be considered to have achieved a ‘conversion’ when a consumer reaches a URL defined in the ‘Goal details’ section.
- Duration: – A goal will be considered to have achieved a ‘conversion’ when a consumer’s time on site reaches the time limit defined in the ‘Goal details’ section.
- Pages/Screens per session: – A goal will be considered to have achieved a ‘conversion’ when a consumer’s session includes a number of pages/screens defined in the ‘Goal details’ section.
- Event: – A goal will be considered to have achieved a ‘conversion’ when a consumer carries out an action defined in the ‘Goal details’ section.
What do the goal details mean?
Goal details are the tweaks you can make to customise your goals to meet your brand’s needs, with each of the goal types connected to a set of modifiable details to enable you to fully tailor the goal.
Destination goal variables
The main customisable option for destination type goals is the destination URL. This is the address of the page you wish to trigger a conversion for the goal you are building. It falls into three categories:
- Equal to: – these are the most common type of destination goal, relying on the website’s standard categorisations – as in: https://www.click.co.uk/insights/custom-goals-google-analytics/
The destination goal with a fixed URL modifier requires only the section of the URL following the domain name, however, so the red box above would be filled with either:
- Begins with: – This type of destination goal includes goals set for dynamically generated or variable URLs (such as those with UTM tracking or eCommerce checkout thank you pages typically augmented with variables denoting the basket) amongst others. If you cannot rely upon the page you want to track having the same URL every time from every device, then the ‘begins with’ option is probably your best choice.
- Regular expression: – If, for example, your site has multiple subdomains with the same checkout page, you can use the regular expression option to track your goal. Google gives the following example: If “/checkout.cgipage=1” is entered into the destination URL box, then it would track both of the below URLs as conversions when the consumer reaches them.
The above destination URLs can all be attributed a value and/or a funnel wherever appropriate for the brand.
Duration goal variables
A nice, easy goal to define – the only option to define this type of goal by is as ‘greater than’ a specific number of seconds, minutes or hours. Probably most useful for content heavy sites, bloggers and similar for whom a long time on site is desirable; the duration goal allows you to decide at what point you would define a consumer’s interaction with a site represents a conversion.
This can be attributed a value and, while it is difficult to think of an occasion it would be required, your sites own calculations of the value of consumer’s time will drive whether it is used and what value to you their time represents.
Pages/session goal variables
Working in a similar way to the ‘duration’ variable above, the pages/session variety of goal variable is limited to a ‘greater than’ expression and is useful in the same way – allowing site owners to determine how many pages represents a conversion.
Event goal variables
Event goals take some consideration when setting conditions, but are essentially useful for tracking consumer activity on a site that is not trackable any other way – such as the final part of a multipart form with a single URL, a video play or a social share.
Done properly, event tracking in this way can add some great depth to the knowledge you have about your consumer’s visits to your site as well as numbers of shares from certain sites that no longer provide numbers (yes, I am looking at you, Twitter).
There is a fantastically detailed description of ‘Anatomy of Events’ over on the Google support subdomain.
How many goals can I have?
In Google Analytics, an account is limited to 50 properties, these properties are each limited to 25 views and each view is limited to 20 goals. The total amount per account, therefore, would be 50x25x20 or a total of 25,000. However, as each property equals one website, the more appropriate answer would – for most people – be 25×20 or a total of 500 goals per website.
Which should keep you going for a while.
Identifying and understanding leads in Google Analytics
Understanding where your leads and conversions are coming from is nearly as important as getting them in the first place. If a business can learn from its output, and see what works, they can adjust their marketing to maximise results.
What we mean by lead
A lead, is not a sale. The two are different stages of the buyer’s journey that are often conflated. A lead is simply someone who has expressed an interest in your business. It’s your job to follow up on this interest, and turn that lead into a conversion. According to Hubspot, there are five stages between the two and this is referred to as the ‘customer lifecycle’.
The stages are:
- Lead– Leads are the first step in creating a customer. They’ve expressed more interest in your business than the average user, but aren’t anywhere near the purchase decision point.
- Marketing Qualified Lead – MQLs are the next stage of the sales funnel. These are the people who raise their hand and say, “This seems like a pretty sweet deal.” They’re interested and will likely purchase from you, but aren’t quite ready.
- Sales Qualified Lead – An SQL is an MQL that has demonstrated an advanced interest in purchasing – maybe by asking specific questions about what you offer. These are the people who need a one-on-one with your sales team.
- Opportunity – Opportunities are the people who have become a real sales opportunity.
- Customer – Someone who gives you money for your product or service.
There are many different actions that could lead to a sale for your business and it is important to have a general idea about what the trigger points are. Many businesses use a scoring system that allocates points to a user when they perform one of the following actions:
- Fill in a contact form
- Open an email
- Request a call back
- Book an appointment
- Sign up to a newsletter
- Download your content
- View specific pages of your website
- Enter live chat
- Interact with your social media
- Phone in
If, as an example you were to allocate 1 point to each of these ten possible actions, (note: there are plenty more) and a user opens an email they will receive 1 point.
If the second user opens an email, visits the website, downloads a document and requests a call back they will have performed 4 actions and therefore have 4 points. It is fair to assume that they will be further along the sales funnel and are a more ‘engaged’ user.
According to Econsultancy: “Within a company you will know how much resource or budget you give to marketing each type of lead, but you’ll also want to find out how much you get out of each one, whether they give you a positive return and which might be more or less profitable than you think they are”.
What can you track?
It is possible to track anything on your website that has a dedicated URL, and this can be done very easily, all you need to do is use a confirmation page. This is done by setting up a goal in Analytics with the confirmation page as the URL Destination.
These goals should be set up for all pages that count as leads and given a value depending on what the average return per lead is (this can be adjusted once you have collected more data).
Check the goal ID
When it comes to where the leads are coming from, the first thing is to check the Google Analytics Goal ID.
By selecting the parent page or the goal set you can break the data down further and look at the actual live stats.
The first option you have is on the main dashboard:
Here you are able to look at four key metrics – Users, Sessions, Bounce Rate and Session Duration. These four things give you an opportunity to understand how many people are looking at you information and the time they are spending with you.
The Bounce Rate metric allows you to plan for more engaging and relevant content. If you can draw users in and keep them by answering their quires, the bounce rate will drop and the audience is far more likely to become a lead or a conversion.
Another thing to look at when it comes to understanding what is triggering the first stage of the customer lifecycle is the time of the day metric. This shows you the exact moment that your audience are engaging with you. If you look at the example below you can see that there is strong performance between Tues-Thurs especially between 4pm and 9pm.
However, it could be that the reason that these times are busy are not because of the audience but because these are the times that they are sent the information. Test various times or alter the sample size to look over a far greater time period and you will gain a greater insight.
The live users feature is a particularly good tool as you can track activity on the site straight after sending out any form of communication.
You can also look at the traffic channel to identify where the breakdown is. Looking at the image below, you can see that the traffic channels have been split first by day and then by sector.
You can then use these charts to see the percentages and volumes of different traffic sources including:
- Display advertising – Display advertising is an online form of advertising that the company’s promotional messages appear on third party sites or search engine results pages such as publishers or social networks. The main purpose of display advertising is to support brand awareness and it also helps to increase a purchase intention of consumers.
- Direct marketing – Direct marketing is a form of advertising where organisations communicate directly to customers through a variety of media including; text messaging, email, websites CTAs, online adverts, database marketing, fliers, catalogue distribution, promotional letters and targeted television, newspaper and magazine advertisements as well as outdoor advertising. It is also known as direct response.
- Organic search (SEO) – The data shown in the above graph in this instance would relate to your website being returned by a search engine to a query and the user clicking on it. In truth this is the best form of marketing as it shows without doubt that you are relevant and appearing in the correct location.
- Email – The term usually refers to sending email messages with the purpose of enhancing a merchant’s relationship with current or previous customers, encouraging customer loyalty and repeat business, acquiring new customers or convincing current customers to purchase something immediately, and sharing third-party ads.
- Other – This data could come from the likes of social media or any other channels that you are currently running
Geographical tools in analytics can help a business to develop their strategy as they can see which countries their leads are coming from. This allows them to consider new markets and the possibility of using other languages or URLs to target a wider audience.
In terms of top-level data, the last real metric businesses can use to look at where their leads are coming from is the device split. Whilst this only gives information based on where somebody is reading a communication it can also be very helpful.
If you have a large portion of your audience reading communications on mobile, then you may start to think about rolling out an app or some bespoke mobile content. It goes without saying that you should be ‘mobile friendly’ and have optimised your content and images for the devices, but have you considered the type of content?
There is a strong correlation between image led, short, sharp text on mobile as well as content that is easily digestible at lunch and traditional commuting periods. Think about how you can get your message over if you only have a short window of exposure.
With all this to consider, an important point to note is that you have to make sure you take the time to double check your Google Analytics Goals before you move on to reporting, or you’ll be making decisions based on incorrect data.
While Analytics can seem forbidding at first, it’s a surprisingly intuitive tool. The investment of time it takes to better understand both the platform and the data it provides can have real positive influence on every aspect of a business.
Need help getting your analytics account in order, training or consultancy? Why not contact us and see how we can help you further to master Google’s Universal Analytics?