More sales might be happening exclusively online this year. And retailers might be creating their own "sales day" events. But one thing that hasn’t changed with COVID-19 is the surge in Black Friday Cyber Monday (BFCM) events around the globe. Black Friday might have started in the USA, but it’s now a popular shopping event in other countries too, especially the UK (where Littledata started). Shopify now supports multi-currency “stores” (one for each currency). In fact, Shopify Payments now supports over 120 currencies, and brands selling in multiple countries are promoting BFCM deals across all of them. [subscribe heading="Free ebook: Top 5 BFCM Benchmarks" background_color="grey" button_text="Get Your Copy" button_link="https://www.littledata.io/app/top-5-holiday-benchmarks"] Our Shopify Plus customers started preparing for these sales earlier than ever, some launching holiday promotions as early as October! Not only that, but the sales are seemingly endless. Glossy recently reported that 37% of brands will run holiday promotions for at least 8 weeks this year, and Littledata's Shopify benchmarks are already showing the signs of increased promotions: lower conversion rates but a lot more traffic, especially from social channels. (We also found last year that holiday promotions increased next season purchasing -- and I expect this trend to continue). Resources for Shopify stores doing multi-currency BFCM promotions With multiple country stores and a longer sales period, accurate data becomes even more important. These free resources will help you answer the questions in the back of your mind: are you tracking multi-currency sales correctly? 4 tips for Shopify Plus merchants selling internationally A common mistake of many companies is quickly jumping into international ecommerce without taking time to develop a proper strategy. Read these 4 tips to help your Shopify Plus business sell in a more cost-effective way. How Shopify Plus stores can set up multi-currency reporting in Google Analytics Our recommendations for what to track and how to track it. In this detailed post, Littledata’s CEO looks at the differences in analytics for single store and multi-store international setups.  Multi-currency tracking for Shopify Payments Many Shopify Plus merchants rely on Shopify Payments to manage multi-currency. For those stores, Littledata's multi-currency tracking is an out-of-the-box solution to get accurate sales and marketing data. This article outlines how Littledata’s multi-currency support works for different parts of the data processing. We use Shopify’s definition of presentment currency and shop currency. Overview of automated multi-currency tracking Are you selling internationally? If you're already selling internationally, it’s important to get tracking set up correctly before BFCM. Learn how to track sales in multiple currencies directly in Google Analytics, so you can scale the smart way during the busiest shopping season. [subscribe]

Subscription ecommerce has continued to scale throughout the pandemic, with consumables like beverages and meal kits rising particularly fast in North America. Shopify sites selling by subscription have always been a core part of our customer base at Littledata, and with even traditionally brick-and-mortar retailers moving online and trying out subscription ideas, we've got our hands full with new subscription sites these days. It might be easier than ever to start a subscription box (companies like Bulu have transformed the market), but getting accurate data about marketing attribution and customer lifetime value is difficult without the right data setup. So with Black Friday Cyber Monday coming up, we thought it would be useful to share some of our top posts this year about subscription analytics. Here are our top three posts this year. Enjoy! 1. How to calculate LTV for ecommerce subscriptions Lifetime value is a core metric for many online companies these days. This is especially important for ecommerce sites, because whether you're focusing on repeat purchases or actual subscriptions, marketing to (and product alignment with) the highest LTV customers can make or break a DTC brand today. In this post, our founder breaks down the basics of LTV calculations for ecommerce, focused on Shopify stores using ReCharge for subscriptions. https://blog.littledata.io/2020/01/14/how-to-calculate-lifetime-value-ltv-for-subscription-ecommerce-in-google-analytics/ 2. How to use Custom Dimensions in Google Analytics to increase subscription sales Custom Dimensions are a remarkably powerful feature in Google Analytics, often overlooked because they can be complicated to set up manually (also, they "sound complicated"). But the truth is that with a little background research, custom dimensions are easy to understand, and -- more importantly -- to apply to your daily, weekly and monthly reports in order to get a clear view of different order types, repeat purchasing behavior, and more. https://blog.littledata.io/2019/09/19/quick-tips-for-subscription-stores-using-custom-dimensions-in-google-analytics/ In this detailed post, our lead analyst dives into the complications of modern DTC brands selling a mix of product types and subscriptions. He focuses on how to reconcile differences in different reporting tools, and how to create segments and reports to fit your unique business model. After all, talk is cheap. How can you put LTV calculations to work for your business? [note]Did you know? Littledata automatically tracks first-time and recurring purchases and ties them back to the original marketing source.[/note] 3. The ultimate guide to LTV tracking In this popular guest post on the Shogun blog, we take a look at everything you need to know about LTV. When you know your LTV, you can: Know which kinds of products your high-LTV customers want more of Know how much to spend to acquire a “similar” customer and still make a profit based on their projected buying habits Promote the products with the highest profitability Increase your marketing budget and inbound efforts to attract your most profitable types of customers [subscribe]

You may have noticed a new referral source appearing in your Google Analytics, or an increase in sales from the 'Referral' channel. This is a change Shopify made with the launch of the new Shop app, and can be easily fixed. What is Shop.app? SHOP by Shopify is a consumer mobile app, aggregating products and experiences from many Shopify merchants. It is heavily integrated with ShopPay, and so Shopify is now directing one-click checkout traffic to the shop.app domain instead of pay.shopify.com. How would SHOP fit into the user journey? There are two scenarios: 1. Customer is using Shop.app for checkout and payment Example journey: User clicks on Facebook Ad Lands on myshop.myshopify.com?utm_source=facebook Selects a product Logged in, and directed to shop.app for checkout Returns to myshop.myshopify.com for order confirmation In this scenario we should exclude shop.app as a referrer, as the original source of the order is really Facebook 2. End customer is using Shop.app for browsing / product discovery Example journey: User discovers product on shop.app Clicks product link to myshop.myshopify.com?utm_source=shop_app Logged in, and directed to shop.app for checkout Returns to myshop.myshopify.com for order confirmation Here, shop.app is the referrer but it will show up with UTM source How do I see the true source of the referral in Google Analytics? Firstly, you need to exclude shop.app as a referral source. Only in scenario 2 is SHOP genuinely a source of customers, and there the UTM source tag will ensure it appears as a referrer. Littledata's latest tracking script sets this up automatically. The second fix is harder. Unfortunately, at the time of writing, Shopify only sets utm_source=shop_app in the URL query parameters in scenario 2, and Google Analytics won't consider this a referral unless utm_medium is also set. So it appears under the (not set) channel. [tip] Littledata now supports conversion tracking in Google Analytics 4 (GA4): Learn More [/tip] I've written a patch for our tracking script so that we set utm_medium as referral if only the source is specified, but you can also edit the default channel grouping in GA so that shop_app is grouped as a referral. Thirdly, you want to differentiate orders going through shop.app from the normal Shopify checkout. Littledata's Shopify app does this by translating the order tag shop_app into the transaction affiliation in Google Analytics, so the affiliation is Shopify, Shop App. Conclusion So if you're a Littledata customer: our app has got you covered. And if not there's a few changes you'll need to make in Google Analytics settings to make sure shop.app traffic is treated correctly.

Cross-domain tracking makes it possible for Google Analytics to track sessions on two related sites (e.g. an ecommerce site and a separate shopping cart site) as one single session. This is also known as site linking. In other words, with cross-domain tracking, you can see a user in a single Google Analytics account throughout their journey across multiple domains you control (e.g. mysite.com and myshoppingcart.com). It’s a seamless shopping and checkout experience for your online shoppers, so shouldn’t you track it seamlessly? Why you need to set up cross-domain tracking Here’s what it looks like with a standard configuration of the Google Analytics script on your site:  Every time a user loads a page on a different domain, a new session is generated even if the branding looks seamless to the user and the previous session has ended.  Even if the customer is still active and continues to generate events and page views on the other domain, the sessions are still interrupted.  Until you implement the cross domain tracking on your site, you won’t have an accurate customer journey. For example, let’s take a standard website, www.siteA.com, and its blog, www.blogB.com. To track sessions, Google Analytics collects a Client ID value at every hit. Client ID values are stored in 1st party cookies, and these cookies are only available to web pages on the same domain.  When tracking sessions across multiple domains, the Client ID value has to be transferred from one domain to the other. To do this, the Google Analytics tracking code has linking features that allow the source domain to place the Client ID in the link URL, where the destination domain can access it.  First, the source domain needs to ensure all URLs pointing to the destination domain contain the Client ID of the source domain. Second, the destination domain needs to know to check for the presence of a Client ID in the URL once a user navigates there. If you're using gtag.js, cross domain tracking can be done by adding a linker parameter containing the Client ID (as well as the current timestamp and browser metadata encoded within it) to URLs pointing to the destination domain.  When a value is configured for the domains property of the linker parameter, gtag.js will check for linker parameters in the URL. If the linker parameter is found and is valid, gtag.js extracts the client ID from the parameter and stores it. By enabling cross domain tracking with gtag.js, you have the option to add the linker parameters either automatically or manually to URLs in links and forms on the page. Setting up cross-domain tracking by modifying the tracking code To set up cross domain tracking for multiple top-level domains, you need to modify the Google Analytics tracking code on each domain. You should also have basic HTML and JavaScript knowledge (or work with a developer) to set up cross domain tracking. The examples in this article use the Global Site Tag (gtag.js) framework. To get started, within the source domain you’ll need to configure the Domains property of the Linker parameter in your property's config for URLs pointing to the destination domain.  After that, gtag.js will listen for selections on links that point to the destination domain(s), and it will automatically add the linker parameter to those links before the navigation starts. You can also set the optional decorate_forms property of the linker parameter to true if you have forms on your site pointing to the destination domain. For example, this code will append the linker parameter to any links on the page that point to the target domain 'siteA.com': [dm_code_snippet background="yes" background-mobile="yes" bg-color="#0fa69d" theme="dark" language="javascript" wrapped="no"] gtag('config', 'GA_Property_ID', {   'linker': {     'domains': ['siteA.com']   } }); [/dm_code_snippet] If the destination domain is not configured to automatically link domains, you can instruct the destination page to look for linker parameters by setting the accept_incoming property of the linker parameter to true on the destination property's config: [dm_code_snippet background="yes" background-mobile="yes" bg-color="#0fa69d" theme="dark" language="javascript" wrapped="no"] gtag('config', 'GA_Property_ID', {   'linker': {     'accept_incoming': true   } }); [/dm_code_snippet] Bear in mind, there are sometimes cases where it is unclear which domain your users will see fist.  In such cases, there is also the option to implement "bi-directional cross domain tracking". With this config, each domain is configured to work as either the source or the destination.  To implement bi-directional cross-domain measurement, enable auto linking on both domains and configure them both to accept linker parameters and automatically link domains. To keep the same code snippet on every domain, you can add all possible domains you want to track in the domains property of the linker parameter. [dm_code_snippet background="yes" background-mobile="yes" bg-color="#0fa69d" theme="dark" language="javascript" wrapped="no"] gtag('config', 'GA_Property_ID', {   'linker': {     'domains': ['example-1.com', 'example-2.com']   } }); [/dm_code_snippet] Setting up cross-domain tracking with Littledata's Shopify app If you use Shopify or Shopify Plus and have already installed one of Littledata's Shopify apps to fix your analytics tracking, then the cross-domain linker implementation will be even easier. We offer versions for Google Analytics and Segment, but they work in basically the same way. When you install Littledata, the app replaces Shopify's integration with Google Analytics with its own improved tracking script (LittledataLayer). This script contains the extraLinkerDomains property where you can add extra sites for domain linking, keeping everything very robust: [dm_code_snippet background="yes" background-mobile="yes" bg-color="#0fa69d" theme="dark" language="javascript" wrapped="no"] LittledataLayer = { transactionWatcherURL: 'https://transactions.littledata.io', referralExclusion: /(paypal|visa|MasterCard|clicksafe|arcot\.com|geschuetzteinkaufen|checkout\.shopify\.com|checkout\.rechargeapps\.com|portal\.afterpay\.com|payfort)/, googleSignals: true, anonymizeIp: true, productClicks: true, extraLinkerDomains: ["domain1.com", "domain2.com"], persistentUserId: true, googleAdsConversionIds: ['AW-12345'], hideBranding: false, ecommerce: { currencyCode: '{{shop.currency}}', impressions: [] } }; [/dm_code_snippet] How to test your cross-domain tracking setup One of the easiest ways to test if the new cross-domain tracking is set up properly, is to check if the same client ID (cid) is tracked on all available page sessions using Tag Assistant Recordings.   Get help from Littledata enterprise If you’re an enterprise customer, just ask your account manager to help add the secondary domains and audit your set up. This is the easiest way to do it and one of the time-saving benefits enterprise customers enjoy.  Using filters to report on cross-domain tracking By default, Google Analytics only includes the page path and page title in page reports - not the domains name. For example, you might see one page appear in the Site Content report like this: /contactUs.html Because the domain names aren’t listed, it might be hard to tell whether this is www.siteA.com/contactUs.html or www.blogB.com/contactUs.html. To get the domain names to appear in your reports you need to do two things: Create a copy of your reporting view that includes data from all your domains in it Add an advanced filter to that new view. The filter will tell Google Analytics to display domain names in your reports. Follow this example to set up a view filter that displays domain names in your reports when you have cross-domain tracking set up. For some fields, you need to select an item from the dropdown menu. For others, you need to input the characters here: Filter Type: Custom filter > Advanced Field A: Hostname Extract A: (.*) Field B: Request URI Extract: (.*) Output To: Request URI Constructor: $A1$B1 Click Save to create the filter. You can validate that filters are working as you expect using Google Tag Assistant Recordings. Tag Assistant Recordings can show you exactly how your filters change your traffic. In your Google Analytics reports, you should start seeing the domain names populated alongside the page path.  Want to double check to ensure it's working? When you sign up for a trial, you can check your full setup with our  smart analytics audit. Get started today with a 14-day free trial! [subscribe heading="Get my smart analytics audit" background_color="green" button_text="audit my site" button_link="https://www.littledata.io/features/audit"]

Google Analytics is used by tens of millions of websites and apps around the world to measure web visitor engagement. Due to some users choosing not to be tracked or blocking cookies, Google Analytics can't measure 100% of visitors. But when set up correctly, GA measures over 95% of genuine visitors (as opposed to web scrapers and bots). At Littledata, our customers come from a range of industries. But when they first come to the Littledata app for help fixing their analytics, we hear many of the same questions: Is Google Analytics accurate? How do I know if my Google Analytics setup is giving me reliable data? In this blog post, we dissect some common issues with Google Analytics before providing a solution to help your ecommerce tracking be as accurate as possible. 6 common issues with Google Analytics 1) Your tracking script is not implemented correctly There are two common issues with the actual tracking script setup: It's implemented twice on some pages It's missing completely from some pages When the script is duplicated, you’ll see an artificially low bounce rate (usually below 5%), since every page view is sending twice to Google Analytics. When the script is missing from pages, you’ll see self-referrals from your own website. How to fix it Our recommendation is to use Google Tag Manager across your 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. How to fix it 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. How to fix it 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 are more complicated. When Google Analytics speaks of 'users', what it's really tracking is a visit from a particular device or browser instance. For example, 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 —  the two apps use two different internet browser instances. How to fix it While Google is looking at ways to use its accounts system (Gmail, Chrome, etc.), there's not a lot which can be done to fix this at the moment. 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. How to fix it This is a remarkably common issue with Shopify stores. That’s why we built a popular Shopify reporting app that solves the issue automatically. [subscribe heading="Get the Littledata Shopify reporting app" background_color="grey" button_text="get the app" button_link="https://www.littledata.io/shopify"] 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. How to fix it Sending custom events is the key to ensuring your tracking is both accurate and relevant. Google Tag Manager makes this easier than it would be otherwise. However, you may need to speak to a qualified Google Analytics consultant to decide what to track. Wrapping up For better certainty that your analytics are fully accurate, try our free Google Analytics audit or get in touch with our Google Analytics consulting team for a quick consultation. If you're ready to give it a shot, go ahead and try Littledata free for 30 days — we'll even walk you through the app! We ❤️ analytics and we're always here to help.   Quick links How to get extra support from our team of Google Analytics experts Enterprise plans to help you scale your store faster EBOOK: Why does my data in Google Analytics not match what I see in Shopify?

The latest version of Safari, and all browsers running on iOS for iPhones or iPads, limit the ability for Google Analytics (and any other marketing tags) to track users across domains, and between visits more than a day apart. Here’s how to get this fixed for your site. This article was updated January 2021 to include the changes for iOS 14 How does this affect my analytics? Safari's Intelligent Tracking Prevention (ITP) dramatically changes how you can attribute marketing on one of the web's most popular browsers, and ITP 2.3 makes this even more difficult. How will the changes affect your analytics? Currently your marketing attribution in Google Analytics (GA) relies on tracking users across different visits on the same browser with a first-party user cookie - set on your domain by the GA tracking code. GA assigns every visitor an anonymous ‘client ID’ so that the user browsing your website on Saturday can be linked to the same browser that comes back on Monday to purchase. In theory this user-tracking cookie can last up to 2 years from the date of the first visit (in practice, many users clear their cookies more frequently than that), but anything more than one month is good enough for most marketing attribution. ITP breaks that user tracking in major ways: Any cookie set by the browser, will be deleted after 7 days (ITP 2.1)Any cookie set by the browser, after the user has come from a cross-domain link, will be deleted after one day (ITP 2.2)Any local storage set when the user comes from a cross domain link is wiped after 7 days of inactivity (ITP 2.3)With Safari 14, any script known to send events about the user is blocked from accessing cookies or any way of identifying the userFrom iOS 14 onwards all browsers will implement these restrictions by default, unless the user opts in to 'allow cross-website tracking'. This will disrupt your marketing attribution. Let’s take two examples. Visitor A comes from an affiliate on Saturday, and then comes back the next Saturday to purchase: Before ITP: sale is attributed to AffiliateAfter ITP: sale is attributed to ‘Direct’Why: 2nd visit is more than one day after the 1st Visitor B comes from a Facebook Ad to your latest blog post on myblog.com, and goes on to purchase: Before ITP: sale is attribute to FacebookAfter ITP: sale is attributed to ‘Direct’Why: the visit to the blog is not linked to the visit on another domain The overall effect will be an apparent increase in users and sessions from Safari or iPhones, as the same number of user journeys are broken in down into more, shorter journeys. How big is the problem? This is a big problem! Depending on your traffic sources it is likely to affect half of all your visits. Apple released iOS 14 and Safari 14 on 16th September 2021, and at the time of writing around 20% of all web visits came from iOS 14, and another 20% of visits from Safari 12 or higher, on a sample of larger sites. The volume for your site may vary; you can apply this Google Analytics segment to see exactly how many iOS users you have. The affected traffic will be greater if you have high mobile use or more usage in the US (where iPhones are more popular). Why is Apple making these changes? Apple has made a strong point of user privacy over the last few years. Their billboard ad at the CES conference in Las Vegas earlier this year makes that point clearly! Although Google Chrome has overtaken Safari, Internet Explorer and Firefox in popularity on the desktop, Safari maintains a very dominant position in mobile browsing due to the ubiquitous iPhone. Apple develops Safari to provide a secure web interface for their users, and with Intelligent Tracking Prevention (ITP) they intended to reduce creepy retargeting ads following you around the web. Genuine web analytics has just been caught in the cross-fire. Unfortunately this is likely not to be the last attack on web analytics, and a permanent solution may not be around for some time. Our belief is that users expect companies to track them across ­their own branded websites and so the workarounds below are ethical and not violating the user privacy that Apple is trying to protect. How to fix this There is only one fix I would recommend. I’m grateful to Simo Ahava for his research on all the possible solutions. If you’re lucky enough to use Littledata's Shopify app then contact our support team if you'd like to test the private beta of our 'trusted cookie' solution. Server-side cookie service ITP limits the ability of scripts to set cookies lasting for longer than 7 days (or 24 hours in some cases). But this limit is removed if a web server securely sets the HTTPS cookie, rather than via a browser script. This also has the advantage of making sure any cross-domain links tracked using GA's linker plugin can last more than one day after the click-through with ITP 2.3. The downside is this requires either adapting your servers, proxy servers or CDN to serve a cookie for GA and adapt the GA client-side libraries to work on a web server. If your company uses Node.js servers or a CDN like Amazon CloudFront or Cloudflare this may be significantly easier to achieve. If you don’t have direct control of your server infrastructure it’s a non-starter. Also, a caveat is that Apple recommends settings cookies as HttpOnly to be fully future proof - but those would then be inaccessible by the GA client tracking. Full technical details. What about other marketing tags working on Safari? All other marketing tags which track users across more than one session or one subdomain are going to experience the same problem. With Google Ads the best solution is to  link your Ad account to Google Analytics, since this enables Google to use the GA cookie to  better attribute conversion in Google Ads reporting. Facebook will no doubt provide a solution of their own, but in the meantime you can also attribute Facebook spend in GA using Littledata’s  connection for Facebook Ads. Are there any downsides of making these changes? As with any technical solution, there are upsides and downsides. The main downside here is again with user privacy. Legally, you might start over-tracking users. By resetting cookies from the local storage that the user previously requested to be deleted, this could be violating a user’s right to be forgotten under GDPR. The problem with ITP is it is actually overriding the user’s preference to keep the cookie in usual circumstances, so there is no way of knowing the cookie was deleted by the user … or by Safari supposed looking out for the user! Unfortunately as with any customisation to the tracking code it brings more complexity to maintain, but I feel this is well worth the effort to maintain marketing attribution on one of the world's most popular browsers.

The script that triggers/sends the tracking events to Google Analytics must be loaded once (and only once) on every page of your site. While you don't need a Google Analytics consultant or Google Analytics consulting group to help you set up tracking, you’ll usually need either your Analytics tracking ID or the entire Javascript tracking code snippet to complete the manual setup. This corresponds to your Google Analytics property. To find the tracking ID and code snippet: Sign in to your Google Analytics account. Select the Admin tab. Select an account from the drop-down menu in the ACCOUNT column. Select a property from the drop-down menu in the PROPERTY column. Under PROPERTY, click Tracking Info > Tracking Code. The snippet provided here must be implemented on every page, even the pages you're not interested in. If you chose to not include the code on every page then: You will not be able to see the full flow of a client on your website. You will have inaccurate data about the time spent on site and actions taken. Visits to untracked pages will appear as 'referrals' and so will skew the volume of sessions. Marketing campaigns to the untracked pages will be lost. The easy way for an established website to verify the tracking is complete is Google Analytics > Acquisition > Referrals and search in the report after the name of your website, as shown below. You can also use Littledata's audit tool (hint hint). [subscribe heading="Try Littledata free for 30 days" background_color="green" button_text="Start my free trial" button_link="https://www.littledata.io/app/get-free-trial"] Choose your method for tracking setup There are several ways to collect data in Google Analytics, depending on whether you want to track a website, an app or other internet-connected devices. To select the best installation method for what you wish to track, here is the complete guide from Google. Once you have successfully installed Google Analytics tracking, it may take up to 24 hours for data such as traffic referral information, user characteristics and browsing information to appear in your reports. Some of these metrics include buying behavior, average order value (AOV), customer lifetime value (LTV) and more. However, you can immediately check your web tracking code setup. If you don’t think it's working correctly, you can check your Real-Time reports or use Google Tag Assistant to verify your setup. Enhanced Ecommerce tracking The main benefit of enabling Enhanced Ecommerce tracking (EEC) over standard tracking is the number of valuable reports you have access to with EEC. Not only that, but you can segment data based on ecommerce events — i.e. which users visited your product pages, where the customer journey hit a roadblock (e.g. a customer pondered a product but didn’t add to cart, etc.) or which steps of the checkout process a user abandoned their cart. This kind of data helps you zoom in on your sales funnel and change the parts of the process that don’t lead to conversions. At Littledata, we typically set up EEC with Google Tag Manager. Here's how to set up Enhanced Ecommerce tracking via GTM. Setting up Shopify tracking [tip]If you haven't already, check out our free Shopify connection guide[/tip] If you're on Shopify and using Google Analytics as your main tracking tool, you're in luck. Our new tracking code update for Shopify users is faster, more versatile and more efficient than ever before. We also have new features and updates in our Shopify app for Google Analytics. With the app, you'll only see fixed, accurate data in Google Analytics. This means you won't need to rely on the broken data in Shopify analytics or the incomplete tracking in GA's default view. Fixed marketing attribution and accurate shopper behavior are now at your fingertips. That means better, more informed marketing & sales decisions for your Shopify store. ?

If you're a Shopify store manager, one of your biggest questions should be 'which campaigns lead to sales?'. We looked at data from 10 Shopify Plus customers to see whether the sales by traffic source report can be trusted. Under the Shopify store admin, and Analytics > Reports tab, you can (in theory) see which sessions and sales came from which traffic sources. BUT this sales by traffic source report is broken. Looking at 180,000 orders for 10 stores in Q4 2018, here are the marketing channels which Shopify Analytics says brought the traffic: Direct 83.5%Social 9%Search 4.5%Unknown (other websites, not social or search) 3%Email ~0.1% And using comparative data from Google Analytics we know this is all wrong. Here's a comparison of Shopify's attribution to Google Analytics last-click attribution of sales for one of these customers: Marketing attribution comparison for 700 orders Shopify Google Analytics Direct 99% 43% Search (Paid + Organic) 0.6% 7% Social 0.4% 10% Email - 25% Affiliates - 15% Here's why it's broken 'Direct' traffic is when the source is unknown. But for Shopify's report this means where the source of the last session is unknown - the user most probably visited a search ad or product review previously. Having only 1% visibility on your marketing performance is just not acceptable!We know that tagged Facebook traffic alone represents 7% of traffic for the average store, so 10% of sales from Social is more normal. Social also brings more than the actual sales in terms of visibility and influencers.Google generates billions of pageviews a month for ecommerce stores. If your site gets only 1% of its traffic from search, we'd be very surprised! Including paid search this site is still well below the 40% average. (Check out our 6 essential benchmarks for Shopify stores.)Monthly emails and personalised retargeting emails are now a staple of online marketing, and we know all the customers in this analysis use email marketing of some form - including for new product launches, discounts and cart abandonment campaigns. The problem is, it's unlikely to be the only campaign which brought customers, so it gets drowned out by other 'last click' channels. The solution: multi-channel attribution.Affiliates are a really important channel to get right, as they are paid based on the sales attributed to them. Why should you rely solely on the report the affiliate marketer gives you, and not see the same numbers in Google Analytics? So don't leave your marketing analytics to guess-work! Try the Littledata app to connect Shopify with Google Analytics on a free trial today. All paid plans include unlimited connections, to ensure accurate marketing attribution for sales via ReCharge (subscriptions), CartHook (one-page checkout), Refersion (affiliates) and more.