Category : Analytics Setup
Is Google Analytics accurate? 6 common issues and how to resolve them
Our customers come from a range of industries, but when they first come to the Littledata app for help with fixing their analytics, they share a lot of common questions. First of all, is Google Analytics accurate? How do you know if your Google Analytics setup is giving you reliable data? In this blog post we look at common problems and explain what can be done to make your tracking more accurate. Google Analytics is used by tens of millions of websites and apps around the world to measure web visitor engagement. It won’t measure 100% of visitors – due to some users opting out of being tracked, or blocking cookies – but set up correctly, it should be measuring over 95% of genuine visitors (as opposed to web scrapers and bots). What are the common things that go wrong? The six most common issues with Google Analytics -- and how to resolve them 1. Your tracking script is wrongly implemented There are two common issues with the actual tracking script setup: 1) when it is implemented twice on some pages, and 2) when it is missing completely from some pages. The effect of duplicating the script is that you’ll see an artificially low bounce rate (usually below 5%), since every page view is sending twice to Google Analytics. The effect of the tracking script missing from pages is that you’ll see self-referrals from your own website. Our recommendation is to use Google Tag Manager across the whole site to ensure the tracking script is loaded with the right web property identifier, at the right time during the page load. 2. Your account has lots of spam When it comes to web traffic and analytics setup, spam is a serious issue. Spammers send 'ghost' referrals to get your attention as a website owner. This means that the traffic you see in Google Analytics may not come from real people, even if you have selected to exclude bots. Littledata’s app filters out all future spammers and Pro Reporting users benefit from having those filters updated weekly. 3. Your own company traffic is not excluded Your web developers, content writers and marketers will be heavy users of your own site, and you need to filter this traffic from your Google Analytics to get a view of genuine customers or prospects. You can do this based on location (e.g. IP address) or pages they visit (e.g. admin pages). [subscribe] 4. One person shows up as two or more users Fight Club aside (spoiler alert), when the same person re-visits our site we expect them to look the same each time. Web analytics is more complicated. What Google Analytics is tracking when it talks of ‘users’ is a visit from a particular device or browser instance. So if I have a smartphone and a laptop computer and visit your site from both devices (without cross-device linking) I’ll appear as two users. Even more confusingly, if I visit your site from the Facebook app on my phone and then from the Twitter app, I’ll appear as two users – because those two apps use two different internet browser instances. There's not a lot which can be done to fix that right now, although Google is looking at ways to use it's accounts system (Gmail, Chrome etc) to track across many devices. 5. Marketing campaigns are not attributed to revenue or conversions If the journey of visitors on your site proceeds via another payment processor or gateway, you could be losing the link between the sale (or goal conversion) and the original marketing campaigns. You will see sales attributed to Direct or Referral traffic, when they actually came from somewhere else. This is a remarkably common issue with Shopify stores, and that’s why we built a popular Shopify reporting app that solves the issue automatically. For other kinds of sites, the issue can often be resolved by setting up cross-domain tracking. 6. You aren't capturing key events (like purchases or button clicks) Google Analytics only tracks views of a page by default, which may not be meaningful if you have a highly interactive website or app. Sending custom events is the key to ensuring that your tracking is both accurate and relevant. Doing so is made easier with Google Tag Manager makes this easier than it would be otherwise, but you may need to speak to a qualified analytics consultant to decide what to track. If you want more certainty that your analytics is fully accurate, try Littledata's free Google Analytics audit or get in touch for a quick consultation. We <3 analytics and we're always here to help.
Why are all my transactions coming from Direct or Referral in Google Analytics, with no marketing attribution?
Connecting marketing data with sales data is an age-old problem, and the crowded digital landscape has made this even more complicated. Google Analytics is supposed to give you the power to attribute sales (or purchase transactions) back to marketing campaigns, but this doesn't happen automatically. The good news is that it's entirely possible to get the right marketing channel attribution for sales activities. Accurate marketing attribution starts with the right Google Analytics (GA) setup. Start by asking yourself the following troubleshooting questions. These steps will help you figure out if your GA setup is correct, and how to use GA to get a complete view of user behaviour. Trustworthy GA setup takes a bit of work, but with a smart analytics dashboard like Littledata, much of that work can be automated. In fact, steps 1 through 4 can be checked automatically with our free Google Analytics audit tool. First of all, are you checking the right report? The best way to see the attribution is in the 'Channels' report in Google Analytics, under the 'Acquisition' section: 1. Have you got a large enough sample to compare? Firstly, can you be sure the sales are representative? If you only have two sales, and both are ‘Direct’, that could be a fluke. We recommend selecting a long enough time period to look at more than 50 transactions before judging, as with this example: 2. Is the tracking script on your purchase confirmation page setup? It you are getting some transactions recorded, but not 100%, then it may be possible to optimise the actual tracking script setup. See our technical guide to ecommerce tracking. This can be a particular problem if many of your sales are on mobile, since slower page load speeds on mobile may be blocking the tracking script more often. 3. Have you got a cross-domain problem? If you see many of your sales under Referral, and when you click through the list of referrers it includes payment gateways (e.g. mybank.com or shopify.com), that is a tell-tale sign you have a cross-domain problem. This means that when the buyer is referred back from the payment domain (e.g. paypal.com), their payment is not linked with the original session. This is almost always a problem for Shopify stores, which is why our Shopify app is essential for accurate tracking. [subscribe] 4. Is your marketing campaign tagging complete? For many types of campaign (Facebook, email etc), unless you tag the link with correct ‘UTM’ parameters, the source of the purchaser will not be tracked. So if a user clicks on an untagged Facebook Ad link on their Facebook mobile app (which is where 80 – 90% of Facebook users engage) then the source of their visit will be ‘Direct’ (not Social). Untagged email campaigns are a particular issue if you run abandoned cart / basket emails, as these untagged links will be 'stealing' the sales which should be attributed to whatever got the buyer to add to cart. Tagging is a real problem for Instagram, since currently the profile link is shown in full - and looks really messy if you include all the UTM parameters. We recommend using a service like Bitly to redirect to your homepage (or an Instagram landing page). i.e. The link redirects to yoursite.com?utm_medium=social&utm_source=instragram&utm_campaign=profile_link. Read Caitlin Brehm's guide to Instagram links. 5. (only for subscription businesses using Littledata) Are you looking at only the first time payments? Tracking the source of recurring payments is impossible, if the tracking setup was incorrect at the time of the first payment. You can’t change Google Analytics retrospectively I’m afraid. So if you are using our ReCharge integration, and you want to track lifetime value, you will have to be patient for a few months as data from the correct tracking builds up. 6. Is a lot of your marketing via offline campaigns, word of mouth or mobile apps? It could be that your sales really are ‘direct’: If a buyer types in the URL from a business card or flyer, that is ‘Direct’. The only way to change this is to use a link shortener to redirect to a tagged-up link (see point 4 above). If a user pastes a link to your product in WhatsApp, that is ‘Direct’. If a user sees your product on Instagram and clicks on the profile link, that is ‘Direct’. Please let us know if there are any further issues you've seen which cause the marketing attribution to be incorrect.
How to add account edit permissions for Google Analytics
Being able to edit the Google Analytics account is the 2nd highest permission level. You need this if you want to create a new web property in Google Analytics. To grant permissions to another user you will need the highest permission level yourself: being able to manage users on the account. [subscribe] Step 1: Go to account user settings page First click the admin cog in any view under the account in GA you want to change, and then in the left hand list go to User Settings EITHER Select an existing user from the list and click the 'edit' checkbox OR Add a new user's email (must be a Google account) and check the 'edit' checkbox. Step 3: Check it's working Your colleague should now be able to see 'Create new property' under the list of properties in the middle of the Admin page.
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Shine a light on ‘dark’ Facebook traffic
If Facebook is a major channel for your marketing, whether sponsored posts or normal, then you’re underestimating the visits and sales it brings. The problem is that Facebook doesn’t play nicely with Google Analytics, so some of the traffic from Facebook mobile app comes as a DIRECT visit. That’s right – if a Facebook user clicks on your post on their native mobile app they won’t always appear as a Facebook social referral. This traffic is ‘dark Facebook’ traffic: it is from Facebook, but you just can’t see it. Since around 40% of Facebook activity is on a mobile app, that means the Facebook traffic you see could be up to 40% less than the total. Facebook hasn’t shown much interest in fixing the issue (Twitter fixed it, so it is possible), so you need to fix this in your own Google Analytics account. Here are three approaches: 1. Basic: use campaign tagging The simplest way to fix this, for your own posts or sponsored links on Facebook, is to attach UTM campaign tags to every link. Google provides a simple URL builder to help. The essential tags to add are “utm_source=facebook.com” and “utm_medium=referral”. This will override the ‘direct’ channel and put all clicks on that links into the Facebook referral bucket. Beyond that, you can add useful tags like “utm_campaign=events_page” so you can see how many click through from your Facebook events specifically. 2. Moderate: use a custom segment to see traffic What if much of your traffic is from enthusiastic brand advocates, sharing your pages or articles with their friends? You can’t expect them to all use an URL builder. But you can make a simple assumption that most users on a mobile device are not going to type in a long URL into their browser address bar. So if the user comes from a mobile device, and isn’t visiting your homepage (or a short URL you deliberately post), then they are probably coming from a mobile app. If your website is consumer facing, then the high probability is that that mobile app is Facebook. So we can create a custom segment in GA for traffic which (a) comes from a mobile device (b) does not have a referrer or campaign (i.e. direct) (c) does not land on the homepage To start you need to create a segment where source contains 'facebook'. Then add the 'Direct mobile, not to homepage' segment: Next, you can create a custom report to show sessions by hour: You should see a strong correlation, which on the two web properties I tested on resulted in doubling the traffic I had attributed to Facebook. 3. Advanced: attribute micro spikes to Facebook Caveat: you’ll need a large volume of traffic – in excess of 100 visits from Facebook a day – to try this at home The final trick has been proved to work at The Guardian newspaper for Facebook traffic to news articles. Most Facebook activity is very transitory – active users click on a trending newsfeed item, but it quickly fades in interest. So what you could do, using the Google Analytics API, is look for the ‘micro spikes’ in referrals that come from Facebook on a minute-by-minute basis, and then look at the direct mobile visits which came at the same time, and add these direct spikes to the total Facebook traffic. I've played around with this and it's difficult to get right, due to the sampling Google applies, but I did manage to spot spikes over around 5 minutes that had a strong correlation with the underlying direct mobile traffic. Could these approaches work for your site? I'm interested to hear. (Chart: Dark Social Dominates Online Sharing | Statista) Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.
6 reasons Facebook ads don’t match the data you see in Google Analytics
The referral exclusion list: what it is and how to update it?
The referral exclusion list is only available for properties using Universal Analytics ... so please make the jump and take advantage of the benefits! Let's find out how excluding referral traffic affects your data and how you can correct some of the wrong attributions of sales. By default, a referral automatically triggers a new session. When you exclude a referral source, traffic that arrives to your site from the excluded domain doesn’t trigger a new session. Because each referral triggers a new session, excluding referrals (or not excluding referrals) affects how sessions are calculated in your account. The same interaction can be counted as either one or two sessions, based on how you treat referrals. For example, a user on my-site.com goes to your-site.com and then returns to my-site.com. If you do not exclude your-site.com as a referring domain, two sessions are counted, one for each arrival at my-site.com. If, however, you exclude referrals from your-site.com, the second arrival to my-site.com does not trigger a new session, and only one session is counted. Common uses for referral exclusions list in Google Analytics: Third-party payment processors Cross-subdomain tracking If you add example.com to the list of referral exclusions, traffic from the domain example.com and the subdomain another.example.com are excluded. Traffic from another-example.com is not excluded. Only traffic from the domain entered in the referral exclusions list and any subdomains are excluded. Traffic from domains that only have substring matches are not excluded. How to add domains in the referral exclusion list: Sign in to your Gooogle Analytics account. Click admin in the menu bar at the top of any page. In the account column, use the drop-down to select the Google Analytics account that contains the property you want to work with. In the property column, use the drop-down to select a property. Click tracking info. Click referral exclusion list. To add a domain, click +add referral exclusion. Enter the domain name. Click create to save. The referral exclusion list used contains matching. For example, if you enter example.com, then traffic from sales.example.com is also excluded (because the domain name contains example.com). Need help with these steps? Get in touch with one of our experts and we'd be happy to assist you! Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.
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