How to choose your Google Analytics Metrics
Google Analytics offers dozens of reports, each containing a multitude of metrics. This enables you to measure and analyze just about any aspect of your site’s traffic and performance that you can think of… Or just get mired in too much information. How do you separate the signal from the noise and pick out what you really need to know about?
What relevant metrics can be measured in Google Analytics
The key to using Google Analytics effectively is deciding upfront what your key business objectives and desired outcomes are, and how you can measure these. Then, instead of trying to measure everything possible, create a simple framework aligned with your desired outcomes and objectives. In other words, match your metrics to your business needs and measure what matters.
So, if you run an e-commerce site, the most valuable information will be such things as which traffic sources lead to the most conversions (or the most profitable conversions) and whether there’s any step in the sales funnel at which you’re frequently losing customers. For information or help sites, you’ll want to measure engagement in terms of how long visitors spend on the site, how many pages they visit and whether they talk about the site on social networks. For brand-building and promotional sites, you’ll want to know how visitors found the site, so you can decide where best to invest further efforts – social marketing, paid search or organic search?
Measuring which pages draw the most traffic can help you assess whether you’re providing enough of what your users are looking for. And so on. It’s clear that some metrics can be applied across industries, but your final choice of metrics will depend on your goals: consider what you need your website to do for your business and then craft your reporting to deliver the information you need.
Here we’ll focus on a few of the key performance indicators likely to be relevant to a range of business types and briefly discuss how they could help you.
Users and Sessions
These are the fundamental measures of activity on your website or app: how many people use it, and how often they do so. In web-only terms, you’d be talking about visitors and visits, and those are the terms Google Analytics used until April 2014, when it adopted the terms users and sessions respectively in order to cover apps as well as sites. You can find out a great deal about your users in the various Audience reports, including their age and gender, their geographic location and many aspects of their activity on the site.
Learning who is coming to your site, where they’re located and what their interests are, among other things, can help you assess your site’s strengths and weaknesses in attracting new visitors, evaluate whether your content is appealing to those visitors, and develop strategies to convert them into customers.
New to Return Visitor Ratio
The first time a device loads your site’s content and a hit is recorded, Google Analytics creates a random, unique ID that is associated with the device. (In practical terms, a cookie is set in the visitor’s browser, which persists for two years.) This unique ID is sent to Google Analytics in each hit, and if Analytics recognizes it as an existing ID, it counts a Returning User. If it’s a new ID, it counts a New User.
In some reports, it’s possible for the same user to be double-counted. If you set a date range of 30 days, say, and a user pays a first visit to the site and then returns later, both within the 30-day period, then Analytics will record two sessions, one with a new user and one with a returning user, even though both are the same person. In the same way, for some dimensions such as Source or Medium, it’s possible that the same unique user can be in multiple buckets – for example, if a user visits from both organic search and paid search within the same date range. For this reason, when you view Users over such a dimension, the sum of the rows won’t add up to the correct total. Conversely, if a user has cleared their cookies, they’ll be counted as a new user. The same applies if they visit again using a different device, unless you’ve implemented the User ID feature, which enables you to assign your own unique IDs to users to identify them across multiple sessions and devices – see chapter 7 of the ‘Key Account Features of Google Analytics’ playbook.
With these caveats, it’s very useful to know that you’re attracting new visitors and expanding your potential customer base. As a rule, however, returning visitors are much more likely to convert – they know your brand or site and they’ve chosen to return, so you’re probably providing something they like. They’re also more likely to promote your brand on their own social networks. They might not convert on their second or even third visit, but it’s important to remember that it can take several points of contact to make a sale.
The Real-Time reports in Google Analytics, but particularly the Acquisition reports, can tell you where your visitors are coming from. Are they finding you by organic search, paid search (your cost-per-click or CPC campaigns, such as Google AdWords) or referral from other sites or blogs? Are they coming from social networks such as Twitter or Facebook, as a result of your newsletter activity, or by typing in your URL directly? Knowing how visitors found your site is a valuable guide to what’s working for you and what you need to work on. Correlate source with conversions and you can gauge whether your investment in paid search or other forms of marketing is paying off by bringing in high-value customers.
If a visitor arrives on your site and then leaves from the same page without interacting with the site, this is a “bounce”. In addition to viewing the simple bounce rate in the Behavior reports in Google Analytics, you can analyses bounce rate in connection with many other dimensions to assess whether users are finding what they want on your site – correlate with geographic location, for example, and you might conclude that users from a specific country could need more localized information or content in their language. You can see which pages have the highest bounce rates in the Site Content > All Pages report: are there trouble spots? Or, correlate bounce rate with Site Speed: are there pages that load so slowly, your visitors can’t be bothered waiting for the content?
A high bounce rate may be an indication that your content isn’t engaging, or that your advertisements are misleading and visitors aren’t finding what they expected to find. Beware, though: a high bounce rate doesn’t always mean your visitors are dissatisfied. If a website is so well designed that a customer lands on the page, finds what they want, takes action, and then leaves without visiting any other part of the site, the bounce rate would be high. For a help site, for example, short visits could indicate that your content is doing its job perfectly. So always correlate with other metrics, and if necessary build in cross-checks such as feedback forms to verify whether your visitors are leaving because they’re unhappy or because they’re satisfied.
Time on site
Average Session Duration is a measure of how long visitors (of all types) spend on your site. Like a high bounce rate, a low time on your site doesn’t necessarily mean your visitors are dissatisfied; it could just mean they’ve found what they wanted quickly. This is ideal if your site is there to provide help or advice. It’s not so good, however, if the site offers in-depth content and visitors aren’t staying long enough to consume it, still less to convert (whether that means buying something or filling in a form). Do you need more engaging content? Implement Event Tracking (‘Key Account Features of Google Analytics’ playbook, page 39) to check whether visitors are interacting with your site at all. Correlate with other measures of engagement, such as return visits and social referrals: if they like what they’ve found, they’re likely to come back again and talk about the site on social networks.
You can’t always take high Average Session Duration at face value, either: sometimes people will leave the browser window open without interacting with the site. This will drive up the time spent on the site artificially. So once again, correlate with other measures of engagement, particularly appropriate Events such as clicking to activate content or moving to the next page.
This is a key metric for any type of site and no matter how you define “conversion”. As the ‘Key Account Features of Google Analytics’ playbook (section 3.4) reveals, you can define your site’s Goals in whichever terms are appropriate to the aims of the site, whether it’s sales, sign-ups or anything in between – even number of pages viewed. Once this is set up, you can evaluate almost every other metric in relation to conversion rate. The Acquisition reports in Google Analytics (‘Key Account Features of Google Analytics’ playbook, section 3.2), for example, might tell you that organic search is bringing in many times more users than paid search, but if the users who arrive via paid search go on to view more pages and have a far higher conversion rate, then your investment in paid search is actually doing its job. Goal conversions are the primary metric for measuring how well your site fulfils its business objectives, and this measure can be applied at every level to determine whether a single campaign or an entire traffic source, a specific page or a specific product line is delivering value and contributing to your bottom line.
Revenue Per Click
Paid marketing can be a substantial investment, and Google Analytics can help you assess how worthwhile it is. The Acquisition > Cost Analysis report shows session, cost and revenue performance data for your paid advertising campaigns, including any non-Google marketing channels for which you upload cost data, plus AdWords (labelled “google/cpc”) if you’ve linked your AdWords and Google Analytics accounts (‘Google Analytics for SEO, SEM, Website and CRM’, section 2.5) and imported AdWords cost data to the View you’re using. The report compares the cost of each campaign with its associated revenue (from your actual e-commerce performance or the fixed value you assigned to specific Goals) to calculate ROAS (Return on Ad Spend) and RPC (Revenue per Click).
Comparing your RPC with the Cost per Click is a quick-and-easy measure of whether your investment is bringing in a good return. Similarly, it’s quite straightforward to compare the ROAS from AdWords with that from other channels or simply with the average for the site, although this isn’t necessarily the only way of judging whether AdWords is sending the right leads to the site: if it (or any other channel) seems to be underperforming, you might need to look also at the wider picture – your campaigns might not be sending pay-per-click visitors to appropriate pages, or your ad text or site contents might need some attention.
Cost Per Conversion
Calculating the return on your ad spend (revenue per click minus cost per click) gives you a basic measure of the value of your paid marketing, but this is not likely to be the whole story. Cost per conversion has been dubbed “the only metric that matters” because you can find your actual profit and true return on investment only by comparing your actual revenues per conversion with the real cost of conversions. Neither of these, however, is as straightforward as the click-based measures we’ve just mentioned. Your revenues per conversion might be actual e-commerce revenues or nominal values you assign manually to specific types of conversions, in which case you need to give some consideration to ensuring those assigned values are realistic; and the cost of conversions ought to include your whole range of costs – not just the amount you spent on paid advertising, but the costs of implementing other forms of marketing, content creation and so on.
This is important because typically many factors contribute to a conversion. The path that a customer takes to reach a conversion might include several touchpoints, each of which contributes in some degree, so you’ll want to begin by looking at the Multi-Channel Funnel reports in Google Analytics (‘Key Account Features of Google Analytics’, page 46). In particular, the Assisted Conversions report shows how many sales and conversions each channel initiated, assisted and completed, along with the value of those conversions and sales. You then need to decide how much credit to give to each channel or type of touch point, and apply the appropriate attribution model to reflect the contribution of each. It’s only after you know this that you can calculate the corresponding cost distribution.
To take a simple example, if you’re spending the same amount on social marketing as on paid search but the latter contributes to twice as many conversions, then it’s actually costing you only half as much per conversion. The actual calculation is likely to be much more complex, of course, because there are so many variables including the value of different conversions and the amount of credit assigned to different channels.
Even in the simplest cost model, though, the other complicating factor is taking account of different costs, particularly those that Google Analytics doesn’t automatically know about. It can be a bit cumbersome to import cost data for non-Google search engines and campaigns such as email marketing campaigns and social media advertising, but you won’t get the full picture without it. Briefly, to track, upload and maintain non-Google click and cost data:
Maintain non-Google click and cost data
1. Implement custom campaign URLs – Google’s online URL builder tool makes this reasonably foolproof.
2. Create a custom data set to hold the data from these.
3. Generate the upload data as a CSV file, then import it into Analytics.
4. Report on your data.
You’ll want to establish a routine for updating the CSV file and importing the updates, but without click and cost data for any non-Google search engines and campaigns, Analytics isn’t telling you the whole story.Read previous article Read next article