GA4: What Shopify stores should do TODAY to keep up with the new version of Google Analytics
Setting up Google Analytics 4 (GA4) on Shopify is easy with the right tools, but there is a lot of confusion in the marketplace right now. There are apps offering "GA4 setup" that can't actually help you with tracking (getting accurate data into Analytics), and there are agencies offering detailed GTM tag setup guides for GA4 without mentioning that there are automated solutions for GA4 conversion tracking. This is all very exciting...but also not necessary. The truth is that you don't need custom tagging or reporting, just the right Shopify tracking app for GA4. What is GA4? It's Google's answer to the modern data stack, in some ways a complement to it (eg. GA4's BigQuery connection, which used to be reserved for GA 360), and in others a replacement for multiple expensive tools that haven't always worked well together. The move toward GA4 started with Google's interest in offering better cross-device and cross-channel tracking, and has been refined with a focus on user privacy -- in other words a world without third-party cookies. As a result, using the right Shopify and GA4 connection now lets you start capturing data about your Shopify store performance that is by default more complex and dynamic than what you might be currently tracking in Universal Analytics (UA, the current version of GA). GA4 can save you time and money versus a complex analytics setup, while offering visibility into the entire customer lifecycle, from organic and paid channels through complex browsing behavior and -- essentially -- customer lifetime value (LTV) and purchase count. But at the very least you need to start capturing that data. [note]This doesn't only apply to Shopify stores! If you're on BigCommerce you can use our server-side BigCommerce to GA4 integration[/note] Google has also built in data-driven models for both comparative attribution reporting and predictive analytics, such as in-app purchase probability and overall purchase probability. But let's not get ahead of ourselves. First you need to capture the data. We expect some brands to just ignore GA4 until the last minute (I'm expecting some not-so-fun Memorial Day Weekend parties next year in NYC...), but we've also noticed that the top ecommerce managers and data scientists are all doing the same thing: tracking in parallel today, so they will have at least six months of data before making the full switch to GA4. Here's a quick guide to help you make the right moves too. 1. Stop procrastinating Is Google really getting rid of the old version of Google Analytics? The answer is a definitive yes. They are sunsetting the old version of Google Analytics in 2023. You need to be ready, but what does that mean exactly? Is there anything you can do today? Track in parallel today so you will have at least six months of data before making the full switch to GA4 Google formally announced the shift to a new version of Google Analytics back in November 2020, but many DTC brands are still putting off the shift to GA4. While moving to a different version of a tool most online marketers use weekly (if not daily) might sound a bit intimidating, there are two points to remember: Google is one of the most user-friendly companies on the planet and they have already added a bunch of functionality and default reporting templates in GA4 You need to capture data before you can analyze it! As our agency partner CXL writes in their ultimate guide to GA4: "Unlike previous upgrade iterations, GA4 is a brand-new product. This means starting afresh, with a new learning curve to navigate." But at the same time, as they say, "it promises to be the future of analytics, with cross-platform tracking, AI-driven data, and privacy-centric design." We couldn't agree more. Littledata's top 10 reasons to switch to GA4 include both custom funnels and predictive insights. This is especially important for ecommerce brands that want to building shopping funnel reports and LTV cohorts in GA4 that fit their particular business model and customer base. So what should you do today to take advantage of this powerful, free ecommerce reporting? First of all, create a GA4 property! 2. Create a GA4 property Google will not be allowing anybody to import historical data from UA into GA4, so you need to create a Google Analytics 4 (GA4) property today if you are serious about seeing performance over time. Luckily, adding a GA4 property is surprisingly easy. Current GA users (that's most of you) can just head to their Analytics accounts and use the setup assistant. You should add at least one data stream. (Don't worry, you can add more later.) Data Streams in GA4 replace Views in Universal Analytics, but they're a bit different . Data streams can be any website (or blog, microsite, country store, etc) or mobile app (iOS or Android), and they can be viewed in aggregate or individually. Adding a data stream might sound intimidating, but this can be as simple as adding the URL for your website (eg. "littledata.io"). [tip]Whether you're new to Google Analytics or a longtime user, we recommend turning on the Enhanced Measurement settings, which include useful defaults.[/tip] When you add a data stream, you will have the option to enabled Enhanced Measurement settings. This is highly recommended. Here's more info on what Littledata lets you track automatically in GA4 -- examples include product views, product list views, checkout funnel events and purchases -- and which events are tracked with Enhanced Measurement, such as page views, site search and form interactions. Now that you have set up a GA4 property, it's time to set up your ecommerce tracking. [tip] Use our complementary instant order checker for GA4 to check your property [/tip] 3. Track in Parallel Tracking UA and GA4 in parallel means that you can send data to both destinations at the same time. This lets you capture browsing behavior and sales performance in both places, so you can analyze the data, build comparative attribution models and start to get a sense for how Universal Analytics and Google Analytics 4 are different -- as well as where they converge. The most accurate way to do this is to use an ecommerce data platform like Littledata to capture ecommerce events by default, including both sales/conversion tracking and marketing attribution (stitching sessions together). We send data directly to GA4. Because we have a pre-built GTM data layer, you don't need to add tags manually! Use a pre-built data layer for GA4 so you don't have to add tags manually Littledata's tracking schema works out of the box to capture both major and minor touch points in the ecommerce journey. When you install Littledata, we instantly start tracking all of the key ecommerce events for you in both UA and GA4, so you'll have the data you need when you're ready to dive into week-on-week and month-on-month analysis. Here's a quick video on tracking in parallel. To get something similar to Enhanced Ecommerce reporting, you'll need to build reports yourselves, so we've also put together a few videos on building ecommerce reports in GA4. These reports are more flexible and dynamic than anything available in UA. It's like having Google Data Studio within Google Analytics for complete reporting. There's even more free content available for subscribers in the app :) Wait, so GA4 is pretty different? GA4 is based on a different type of tracking called event-based tracking, which is is exactly what it sounds like: a more flexible and comprehensive way of tracking everything so you can build granular reports and predictive models based on the endless flow of events and attached parameters. The UA data model focused on sessions and pageviews. GA4 focuses on events, and sessions are no longer broken by a change in campaign "source" (GA4 continues tracking the same session as well as the change in source). But those sessions will not be stitched together automatically with purchase data and Shopify customer IDs. And many Google Tag Manager solutions for GA4 are missing out on the basics, like purchase events, revenue and conversion tracking. If you aren't capturing purchases, how are you supposed to know if your marketing is working? Using Littledata's solution is quick and easy, with both low-code and no-code options. Our ecommerce tracking is deep and comprehensive. When you start a free trial you can choose to send data to both UA and GA4 at no additional cost, with server-side tracking to guarantee accurate data. [subscribe heading="Top-rated GA4 tracking for $99 a month"] Want to know more? Book a free data audit with one of our Google Analytics experts today!
7 ways to reduce your bounce rate
Wondering why your bounce rate is so high and people are not sticking around? Here are some methods you should consider to improve user engagement with your content, conversion rates and sales. Bounce rate is the percentage of single page sessions or visits where the person didn’t engage further than the one page within your site. You shouldn't worry about the high bounce rate if your site visitors are meant to find what they were looking for on a single page. But if it's important for your site that users stick around for either reading more content or going through further pages that lead towards conversion, then you should review your options for reducing the bounce rate. By decreasing the bounce rate you can improve your ability to engage more users and eventually get them to convert. There are a few reasons why you would have a high bounce rate: Single page site or landing page Incorrect setup Wrong audience Design Usability User behaviour Low quality content You can identify your worst performing content by looking at the bounce rate in the Landing Pages report (under Behaviour > Site Content). If there is a high percentage of people leaving the pages without continuing their journey, then review those pages with the suggestions below. You should also check the average time spent on those pages. If users are leaving after a short amount of time, then you should look closely at what may be driving them away and if there are any improvements you can make to keep the visitor on the page for longer, or how to encourage them to visit other pages. Guide users through your website with additional links Users might leave your site after seeing a single page that contained the information they were looking for. If they got what they wanted and don’t care about actively exploring your website, then think about similar pages within your site that might be of interest to your users, and link to them within the content. You could link to: Another blog post covering similar topic from a different angle A case study to increase the credibility of your work Related blog post that the reader might like Best practices of using your product Case studies on how others have achieved results with your product Your product demo or webinar This can be applied to any pages from product and features to blog and about your team. Blog posts on Moz Blog are a great example of providing additional links that are useful and relevant. Improve your page load Your page loading time has a major impact on how quickly people will leave your site, which should be obvious to everyone. Slow site speed can be very discouraging to your potential customers and drive them away. How long would you wait for a page to load, before going elsewhere to a quicker website? A study from WP Engine found 32% of online users will leave a site that takes more than 3 seconds to load. What's more, the study found websites that load in under 2 seconds convert at a rate three times higher than those which take 5-10 seconds to load. In cases where the page load takes 5 seconds or longer, bounce rates increase by 90%. Check Google PageSpeed Insights for more detail on why this matters and how to improve your page speed. Make content readable It is difficult to read large chunks of text that consists of long paragraphs, too much jargon and bad formatting. With our shorter attention span and higher impatience, the more user friendly you can make the text, the better for your site performance. There are a number of ways you can improve the readability of your content: Large headings Bold subheadings Bullets and lists Shorter sentences and paragraphs Less or no jargon Write like you talk Use images Bold keywords where appropriate Add a relevant call to action on the landing page If you have a landing page for converting visitors, whether it is for getting them to enquire or sign up, you need a relevant and prominent call to action (CTA). At Littledata we use CTA in two places on the landing page - top and bottom - to help the user enquire about our services much quicker. I also like Intercom product pages, which have some awesome animations and illustrations, and a call to action that fits the theme. Your CTA could be focussed on getting your users to: Call the company to talk about the product Fill out a form Sign up for a trial Click on banner ad Watch video Subscribe to a newsletter Visit another page within your site or external site Econsultancy has collected examples of some awesome calls to action so check them out for inspiration. Check your landing pages meet visitor expectations If people expect to sign up for a free trial of your software product, but are instead taken to a homepage without a visible way of doing so, then expect a lot of bounces. Invision uses Adwords to promote its free platform plan. Once you click through, you see immediately the content you expect and the option to sign up. If you purchase some of your traffic, make sure you check what information visitors see on your partners’ site before clicking on the link. When we recently ran a number of tests to improve the bounce rate for our client, we were baffled by some of the improvements not having much effect. After further investigation it came out that the visitors on the partner sites were getting the wrong information about what they were clicking on. No surprise then that they were leaving the site so soon. For search engine results, review your page titles and meta descriptions, and make sure they match what the person will see on the page when they click on it. Set external links to open in a new window By providing an external link that opens within the same window, you are forcing your users to leave your site. This will not only affect your bounce rate, but you will also be increasing your exit rate. Instead of interrupting their journey this way, set any external links to open in a new tab. Avoid distracting users from the content Whilst some popups can be relevant to the content of the page and important for your aims, a badly timed popup can be very off-putting for your site users. Your landing page is there to convince the visitor to stay so if your popup displays instantly, you're not letting them see your content that they came for in the first place. Test different timings to see what works best for your users, but I'd be surprised if quickly displaying popups reduce your bounce rate. Autoplaying random songs can also be highly annoying. Especially when it's not the kind of song you listen to, on full blast, and hidden somewhere so it takes you ages to find the music to pause it. Just no. There are no quick wins when it comes to improving your bounce rate. Keep making the improvements with your reader in mind and testing which changes work for you best. So I hope this has been helpful. If you have any experiences with methods mentioned above, do share in the comments below. Further reading: A win for the UK digital sector: UK sites perform better than US sites in benchmark 5 common Google Analytics setup problems to look out for How to accurately track time on site with Google Analytics or Google Tag Manager Stuck with reducing your bounce rate? Contact our certified Google Analytics specialists for help with your bounce rate or other advanced tracking.
7 quick wins to speed up your site analysis techniques in Google Analytics
Analysis and reporting are the most time-consuming aspects of site or app performance tracking in Google Analytics. If you ever wished or thought if only it was quicker, then this post is for you. There are a number of techniques you can implement to speed up your data analysis and number crunching. Here I’ll cover 6 of them. Schedule email reports Google Analytics dashboards are a great way to monitor metrics that are important for your business. But instead of logging in every day or week, or however often you tend to check them, schedule automated email reports instead. At Littledata, we have a select few metrics that we keep track of on a weekly and monthly basis. The whole team gets an email report on a specified day, allowing everyone to get the latest stats without someone on the team having to get those numbers manually every time. To set this up, go to the dashboard that you want emailed to others (or yourself), click ‘Email’ and fill in the details. If you're scheduling the email to go to your team on a regular basis, why not add a nice message in the email body. To edit the scheduled emails you've set up previously, go to Admin > View > Scheduled Emails (towards the bottom of the list). Access your reports quickly Shortcuts in Google Analytics allow you to quickly view the reports you use most often. Even better, they remember the settings you applied to any report. So if you apply an advanced segment or another customisation to the report, saving it as a shortcut will remember your preferences. Except for the date range - that won't be remembered. You can find the shortcut option just below the report title, and once added, you'll find your shortcut reports at the top of the reports list in the left panel. Search for reports you can’t find If you find yourself wondering where a particular report is, use the search found at the very top. Instead of having to go through an extensive report list trying to find something you vaguely remember seeing last month, you get suggestions of what you might be looking for as you type. So you only need to remember or guess part of the report title that you're looking for. Use keyboard shortcuts Did you know Google Analytics has keyboard shortcuts? They allow you to move around the report much quicker and the date range keyboards make a big difference to a workflow. Picking date ranges can be tedious and annoying so I've found these to be the best. If you're already using keyboard shortcuts on your devices, you won't need convincing of their usefulness. To view this complete list of shortcuts in Google Analytics at any time, use a shortcut: ? Set up goals to understand your website visitors Goals are valuable in understanding how well your site or app helps you achieve your objectives. Unfortunately, we see a lot of businesses who either find it too complicated to set up or have done it incorrectly. Speaking from personal experience, it only takes a little practice to get the hang of it, and once setup, you get essential conversion data in your reports. You'll be able to evaluate your marketing efforts and campaigns much more effectively. Check out Google's guidance on goals and my guide on how to set up a destination goal funnel. See trends quickly with Littledata reports We have a clever tool that looks through all of your Google Analytics data and finds the most interesting changes to report on. There are over hundred of GA reports so getting automated summaries that you can act upon will save you hours of work. Littledata tool doesn't require installation and it's quick to set up - all you need is an existing Google Analytics account to sign up with for free. The reports you'll get are also great for presenting to colleagues in meetings, as other users have said. To get your reports, go to Littledata homepage, enter your website into the box and click 'Get started.' We're also working on bringing you benchmarking information, customised tips on how to improve your Analytics setup and what you should be tracking. Pro tip: Manage complex data with query explorer tool Whilst, not the quickest to get used to, Google's query explorer tool can be powerful for those working with large and complex datasets. Some of our biggest clients' websites get millions of hits a month, which can cause discrepancies in data analysis (especially when data is sampled). So I use the query explorer tool to verify the data that clients ask for. To use this tool, you will need to know your metrics from dimensions and learn more about how to use segments, filters and query building. If you've got questions on any of the above, don't hesitate to comment below or get in touch!
How to track registered users with Google Analytics and Google Tag Manager V2
Wondering if Samsung Galaxy is more popular than iPhone when engaging with your content? Then set up the User-ID view to see your logged in users’ activity and evaluate behaviour by the device. With the activity data you collect in the registered users view, you can improve the analysis of your customers' behaviour by seeing which devices are used to sign up and access your website. To summarise the benefits: You get access to the Cross-Device reports, which allow you to analyse which devices your users use to engage with your content. See what the Cross-Device reports look like. You improve your understanding of logged in users who often engage with the site's content differently than those who aren't registered. You get a more accurate user count. In your standard analytics view, a new user is counted every time your site visitor switches to a new device or starts a new session. With the registered user view, you give each user a unique ID, which helps to stitch together various activities carried out by the user. You can find out which devices users prefer for different engagement activities across multiple sessions. This helps with tailoring your campaign and content to different devices and activities. To set this up, you need to have the user ID stored in the data layer. If you don't have it set up, scroll to the bottom for an advanced hack. Now let’s look at how to set up the tracking by using Google Analytics and Google Tag Manager V2. Looking to implement the User-ID in your tracking code? Check Google’s guidance. Enable the feature in Google Analytics Firstly, enable the User-ID feature by going to Admin > Property > Tracking info > User-ID. Read through the short policy on what you’re allowed to track and not. Google is very strict about tracking personally identifiable information so you are not allowed to send any personally identifiable information, such as names and email addresses. But numbered IDs or hashed emails are fine to use. To agree to the terms, follow the steps and click ‘create.’ Create the variable in Google Tag Manager Now go to GTM variables and click 'new'. Select Data Layer Variable type and use the name stored in your data layer, e.g. uid or user ID Add the variable to your pageview tag Go to edit your pageview tag and click on More settings > Fields to set. Click Add field, enter the field name as &uid and select the variable you’ve just created - eg {{uid}} or {{userID}}. Test you're seeing activity in the newly created registered users view with your login, or a test one if you have it. Don't forget to publish your GTM container for tracking to work. Advanced hack If for some reason you can't get your developer to store a user ID in the data layer, there is a way around it. We've created a javascript variable to get a username off the page and hash it prior to sending it to GA. For this, you need to pick a custom Javascript type variable and enter the script below into the custom javascript field. This javascript requires either your developer or you to customise it to work on your page (see the notes in the second and third lines). function() { //dependent on using Jquery selectors //replace '.menuTitle small a' with the selector for your username var name = $('.menuTitle small a').text(); var hash = 0, i, chr, len; if (name.length == 0) return hash; for (i = 0, len = name.length; i < len; i++) { chr = name.charCodeAt(i); hash = ((hash << 5) - hash) + chr; hash |= 0; // Convert to 32bit integer } return hash; }; If you need help with any of the above, don't hesitate to comment below or get in touch!
How to remove referral spam from historical data in Google Analytics
This is a quick follow-up to my guide on how to exclude referral spam from your Google Analytics data. Filters exclude or modify the data from the time you add them and don't have any effect on previous traffic. This is where segments are very useful. Not only can you use a segment to view a cleaner version of your historical data but you can also test the setup of your filters. I've also found the Google's filter verification option quite unreliable but with the segment, you can verify the results yourself and see results straight away. Here I am going to show how to add segments to include valid hostnames and exclude spam referrals from your data. Add a segment to include valid hostnames Creating a filter to include visits from valid hostnames only is the first step you need to take to exclude spam referrals from your Google Analytics data. Test your valid hostnames regex by firstly going to Audience > Technology > Network > Hostname. Create a filter by clicking on ‘Add segment’ and then ‘New Segment’. Now select the conditions tab on the left, under advanced. Set up your filter with the following conditions: Sessions Include Hostname Matches regex (and your regex, eg yoursite|googleusercontent, in our case it's littledata|googleusercontent) Click on ‘Preview’ button on at the top to check which hostnames you are left with. Your list should look much cleaner and only display domains you used in regex. Add a segment to exclude referral spam Like before, you want to test this trigger when viewing a relevant report so go to Acquisitions > All Traffic > Referrals. Create a segment with the following details: Sessions Exclude Medium exactly matches referral AND Source matches regex (and your regex) Whilst filters have a limit of 255 characters, the advanced segment has much more character space to use. I've bundled all spam referrals into one long regex of 900 characters. But as explained in the guide on removing spam traffic you might have to break it up into multiple expressions or filters to fit them all in. By adding those two segments you can not only test that your filter setup is accurate but also view your historical data without fake traffic. If you need help with any of the above, leave a comment below or get in touch!
Tracking web forms in Google Tag Manager V2
Do you know how many people start completing forms on your website, but don't complete them? Do you know which fields cause them difficulties? This is a guide to field-by-field form tracking using GTM. By tracking each element of the form separately, you will see how many people start filling out the form but then decide not to submit it. Once you understand where people drop off you will be able to identify any parts of the form that may need improving. The enquiry form on our website has four elements that I am going to track: the name, email and subject fields, and the button to submit the query. In summary, the set up will work like this: Create a trigger that will act as the firing rule for the tag Create a tag to track clicks on the field Repeat for each field So to set up the tracking of form fields and submits in GTM V2, follow these steps. Enable built in variables Firstly, you will need to enable built in variables. You will need Form ID variable and if similarly to our site you have the same enquiry form placed on several pages, then Page Path variable as well. These variables will allow you to track clicks on the form and on which pages the form was clicked on. The page path variable returns the URL part that comes after your main domain, eg /blog. Create the trigger For your trigger, you will need to find out the field ID you want to track. To find out the ID, if you are using Chrome browser, right-click on the field and select ‘Inspect Element’ It will look something like id=”name” so name here is the unique ID that you need to use with the trigger. If you do not have a unique ID associated with the field you want to track, ask your developers to add it in. This will make the tracking much easier. Now in GTM, go to Triggers tab on the left and click 'New'. You are creating a 'click' trigger, which you want to fire on 'all elements'. Save the trigger. Create the tag Go to Tags tab and click 'New'. Select Google Analytics and tag type 'Universal Analytics'. I send the following event tracking parameters to GA: Category: Enquiry form Action: Click on name Label: {{Page Path}} Now select 'Click' to select the trigger ‘Click on name’ as your firing rule. If there are any pages where you don’t want this tracked, then you will need to create a separate blocking trigger. Here is an example of a trigger for a contact us page that I want to exclude from tracking here. You can create your blocking trigger in a pop up window without leaving the tag. Repeat Follow the steps above to create the trigger and tag for each following field, and amend form ID’s and event field values for each. Test your tags in GTM debug mode and GA real time to make sure the details sent through are what you want. Once tested, publish your container and if you need any further help with any of the above, leave a comment below. Further reading: How to track file downloads in Google Tag Manager V2 Tracking registered users with Google Analytics and GTM V2
How to remove referral spam from Google Analytics
The issue with the referral spam in Google Analytics exploded in May when we saw an average of 620 spam sessions per GA property and just the other week, I saw an account where spam accounted for 95% of the traffic! Spam referrals are greatly skewing your Google Analytics traffic and becoming a headache for a larger number of people. Why are these spam sessions appearing in your Google Analytics traffic? To get you click through to their site and ads (never ever do that, by the way). By targeting thousands of GA accounts like this, you can imagine how much traffic they get from those more curious about their new source of visits. There are two different types of spam referrals you are getting: Ghost referrals send fake traffic to your GA account by “attacking” random GA property IDs. Crawler referrals crawl your website to leave a mark in your traffic. The spam referrals are getting more persistent and clever by targeting other non-referral reports, like www.event-tracking.com appearing in events. How can you tell it's spam? By seeing unusual activity, odd referral sources, substantial changes in your metrics, and lots of (not set) values in various dimensions, eg hostname and language. So how do you remove spam referrals from your Google Analytics traffic? There are two filters you need to set up to remove both ghost and crawler spam referrals. Filters change your traffic permanently so if you don't have an unfiltered view of your data, then create one now. It's a good practice to have an unfiltered view that you don't modify and it allows you to check your filters are working correctly. We are also working on our own spam filter tool to help people get rid of pesky spam referrals with just a few clicks of a button. We have already released a beta version via our Littledata analytics reporting tool and are developing it further to make it more robust and comprehensive. But if you'd rather do it yourself, keep reading. Create a filter to include valid hostnames Since ghost referrals never actually visit the site, the best way to get rid of them is by creating a valid hostname filter. This filter will allow visits from “approved” websites that you consider valid. First, you will need to identify your valid hostnames by going to the report in Audience > Technology > Network > Hostname. Hostnames report shows domains where your GA tracking code was fired and helps to troubleshoot unusual traffic sources. Valid hostnames on the list will be the websites where you inserted the GA tracking code, use additional services, eg transactions, or reliable sites used by people to access your site, eg Google Translate. Your reliable hostnames could look like this: www.yoursite.com yoursite.com blog.yoursite.com translate.googleusercontent.com (user accessing your site via Google Translate) ecommercepartnersite.com webcache.googleusercontent.com (user accessing translated cached version of your site) Any other website that you do not recognise or looks suspicious, you can safely assume to be a hostname you want to exclude. Beware of any domains that appear as “credible sources", eg Google, Amazon and HuffingtonPost. They are used to mask the spammers. If you see (not set) hostname on your list, this could be because you're sending events to GA that don't have pageviews, for example tracking email opens and clicks. If you are sure you are not sending any such events to GA, you can also exclude any (not set) hostnames. Now that you have got your valid hostnames, you need a regular expression for a filter that will include your valid hostnames (and thus, exclude all other fake ones). It'll look like this: yoursite|googleusercontent|ecommercepartnersite In the regex above, the vertical bar | separating each domain means OR. This will match any part of the string, so 'yoursite' will match 'blog.yoursite.com' as well as 'www.yoursite.com'. You can test your regex at http://regexpal.com/ by inserting your expression at the top and all the URLs at the bottom. All matches will be highlighted so you can see straightaway whether you have included all your valid hostnames correctly. Before adding the valid hostname filter in the settings, test it with an advanced segment. The results on the screen should now be only of your valid hostnames and without all the spammers. If all looks good, create a filter by going to Admin > View > Filters > New Filter. This will add a filter for that specific view only. If you want to add the same filter to more than one view, then check the details below. Select 'Include', pick a custom filter and select 'hostname' from the filter field menu. Now enter your regex into filter pattern field and click save. Want to apply a filter to multiple views? Then go to Admin > Account > All Filters > New Filter. The setup is exactly the same as above, except now you will see a section at the bottom titled 'Apply Filter to Views'. Select views you want to apply the filter to and move them to the right hand side box by clicking button 'add' in the middle. You're all set so click save. Add a filter to exclude campaign source Some of the known spam referrals are free-social-buttons, guardlink.org, 4webmasters.org and, most recently, the ironically named howtostopreferralspam.eu. Excluding spam referrals with campaign source filter is one of the most commonly mentioned methods online. This filter will exclude any referrer spam from the moment you add the filter (not from your historical data). The downside is that every time you have a new spam referral appear in your Google Analytics data you will have to add them to the existing filter, or create a new one if you’ve ran out of character space (allows only 255 characters). You can identify your spam referrals by going to referrals report found in Acquisition > All Traffic > Referrals. To save you some time, I have included the regex's we use below so you can copy them. Make sure you double check your referrals report against our list to see if there are any that haven't appeared in our reports yet. If you find a source not listed below, simply add it to the end and let us know in the comments. Similarly to setting up the filter to include valid hostnames only, now you need to add a filter to exclude spam referrals. We use the following regular expressions to filter out spam (yes, that's four filters): guardlink|event-tracking|vitaly rules|pornhub-forum|youporn-forum|theguardlan|hulfingtonpost|buy-cheap-online|Get-Free-Traffic-Now|adviceforum.com|aliexpress.com|ranksonic kabbalah-reg-bracelets|webmaster-tools|free-share-buttons|ilovevitaly|cenoval|bestwebsitesawards|o-o-6-o-o|humanorightswatch|best-seo-offer|4webmasters|forum69.info|webmaster-traffic|torture.ml|amanda-porn|generalporn depositfiles-porn|meendo-free-traffic|googlsucks|o-o-8-o-o|darodar|buttons-for-your-website|resellerclub|blackhatworth|iphone4simulator.com|sashagreyblog|buttons-for-website|best-seo-solution|searchgol|howtostopreferralspam 100dollars-seo|free-social-buttons|success-seo.com|videos-for-your-business.com The reason majority of the websites above do not have org/com/etc is that for these sites I have concluded that there are no other genuine sites with similar site names (or none that I could find) that would send our site traffic. So it is safe to exclude these sites by name only. For example, there are many sites with adviceforum in their name so to avoid excluding any potentially genuine sites that are called adviceforum, I only exclude the one spam referral I saw in my traffic - adviceforum.com. If you notice that you have referral traffic from addons.mozilla.org but don't actually have an addon on Mozilla, then you should add addons.mozilla.org (more commonly known as ilovevitaly) to the list above in this format - addons.mozilla.org Select Campaign Source in the filter field menu and enter your regex into the filter pattern field. Repeat the process until you have got all four (or more) filters created. This will help to clean up your Google Analytics data but you have to keep checking for any new spam referrals to add to the exclude filter. You can use advanced segments to view your historical reports without spam referrals. If you need help with any of the above or have further questions, don't hesitate to let me know in the comments. Further reading: 5 common Google Analytics setup problems How to remove referral spam from historical data
How to track file downloads in Google Tag Manager V2
Setting up tracking of file downloads in GTM V2 is much easier thanks to the new configuration wizard. It is more intuitive and takes you through the set up step-by-step. Let’s have a look at the basic configuration for sending tracking of file downloads from Google Tag Manager to Google Analytics as events. To set up this events tag you need to firstly create a trigger. Create a trigger This trigger will recognise every time someone clicks to download the file you want to track. In the given example I am using a simple regular expression to capture a number of file types I want to track -.(zip|exe|pdf|doc*|xls*|ppt*|mp3)$ Here the * means it will capture any repetitions of the file types it is next to, ie it will include file types doc and docx for Word documents, xls and xlsx for Excel spreadsheets, ppt and pptx for PowerPoint presentations. Save the trigger and create a new tag. Create a new tag Give your tag a meaningful name so you can easily recognise what the tag is for. We have previously created a variable (formerly known as macro) that stores our GA tracking code, which I use in the configuration settings. This way I do not have to re-enter the GA property ID every time I need it. This variable does all the work. Select your track type as 'Event' and insert your tracking parameters. Here I use the following but modify the fields based on what works for your business: Category is Download Action is Click Label is {{element url} Element url in the label field will store the URL of the file that was downloaded. Advanced tracking For advanced tracking, you can create a custom javascript variable with a code that will strip out the title of the downloaded file and store it in your GA. Have a look at Simo's example of returning file name. Set your tag to fire Last step is to add a firing rule, ie select a trigger that will fire your tag. Select the previously created trigger 'Click to Download' and you're all set. Test For extra care, test the tag both in GTM debug mode and GA real time. Publish Now publish the container with your newly created tag. If you need any further help, do leave a comment below. Further reading: Tracking registered users with Google Analytics and GTM V2 Tracking web forms in Google Tag Manager V2
5 myths of Google Analytics Spam
Google Analytics referral spam is a growing problem, and since Littledata has launched a feature to set up spam filters for you with one click, we’d like to correct a few myths circulating. 1. Google has got spam all under control Our research shows the problem exploded in May – and is likely to get worse as the tactics get copied. From January to April this year, there were only a handful of spammers, generally sending one or two hits to each web property, just to get on their reports. In May, this stepped up over one thousand-fold, and over a sample of 700 websites, we counted 430,000 spam referrals – an average of 620 sessions per web property, and enough to skew even a higher traffic website. The number of spammers using this tactic has also multiplied, with sites such as ‘4webmasters.org’ and ‘best-seo-offer.com’ especially prolific. Unfortunately, due to the inherently open nature of Google Analytics, where anyone can start sending tracking events without authentication, this is really hard for Google to fix. 2. Blocking the spam domains from your server will remove them from your reports A few articles have suggested changing your server settings to exclude certain referral sources or IP addresses will help clear us the problem. But this misunderstands how many of these ‘ghost referrals’ work: they are not actual hits on your website, but rather tracking events sent directly to Google’s servers via the Measurement Protocol. In this case, blocking the referrer from your own servers won’t do a thing – since the spammers can just go directly to Google Analytics. It's also dangerous to amend the htaccess file (or equivalent on other servers), as it could prevent a whole lot of genuine visitors seeing your site. 3. Adding a filter will remove all historic spam Filters in Google Analytics are applied at the point that the data is first received, so they only apply to hits received AFTER the filter is added. They are the right solution to preventing future spam, but won’t clean up your historic reports. To do that you also need to set up a custom segment, with the same source exclusions are the filter. You can set up an exclusion segment by clicking 'Add Segment' and then red 'New Segment' button on the reporting pages and setting up a list of filters similar to this screenshot. 4. Adding the spammers to the referral exclusion list will remove them from reports This is especially dangerous, as it will hide the problem, without actually removing the spam from your reports. The referral exclusion list was set up to prevent visitors who went to a different domain as part of a normal journey on your website being counted as a new session when they returned. e.g. If the visitor is directed to PayPal to pay, and then returns to your site for confirmation, then adding 'paypal.com' to the referral exclusion list would be correct. However, if you add a spam domain to that list then the visit will disappear from your referral reports... but still, be included under Direct traffic. 5. Selecting the exclude known bots and spiders in the view setting will fix it Google released a feature in 2014 to exclude known bots and spiders from reports. Unfortunately, this is mainly based on an IP address - and the spammers, in this case, are not using consistent IP addresses, because they don't want to be excluded. So we do recommend opting into the bot exclusion, but you shouldn't rely on it to fix your issue Need more help? Comment below or get in touch!
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