Six reasons to start using Meta’s Conversions API now

One of the biggest marketing areas hit by iOS14 updates, and tracking prevention in general, is social ads. As Meta’s main moneymaker, the company of course wasn’t going to stand by and have their best feature for brands become unusable. Enter Facebook's Conversions API (CAPI), a solution that complies with new tracking and privacy laws by letting Facebook and Instagram Ads users share customer actions from the servers directly to Facebook. Facebook Ads via Conversions API work alongside Facebook Pixel to help you improve the performance, measurement, and data collection of your campaigns for Facebook Ads and Instagram Ads. But Facebook CAPI isn’t a replacement for Facebook Pixel. Instead, it’s an enhancement that enables deeper first-party data to help you understand performance in more detail and run more effective ads. Using Littledata to set up CAPI on your store makes this data more accurate and reliable so that your campaigns reach the right shoppers at the right time. When using Littledata and Facebook CAPI together, you can: Automatically improve Event Match Quality Score Run dynamic product ads based on accurate shopping data Make revenue data in Shopify match revenue data in Facebook In this post, we’ll share six reasons why you need to add this powerful advertising tool to your toolbelt ASAP. Why use Facebook CAPI? 1. Facebook CAPI solves for VPNs and ad blockers Originally, Facebook Pixel provided us with all the information we needed to build powerful audiences for our ads. Then, VPNs, ad blockers, and other privacy software began causing some discrepancies in the data. This is where the Facebook Conversions API came in. Facebook CAPI sends events “server-side” instead of “client-side” through the third-party browser a customer is using to access your site. That means they aren’t interrupted by the web browsing and privacy trends mentioned above. Even better, you can share almost 100% of purchases from your store with Facebook via CAPI. [tip]Learn how to use Facebook CAPI to run dynamic Facebook ads and target your top buyers.[/tip] 2. Facebook CAPI is iOS14-friendly With iOS 14 privacy changes, we’re not just dealing with discrepancies in the data, but gaps. Those gaps negatively impact Facebook ad targeting because iOS 14 limits what data advertisers can collect through client-side (pixel) tracking and allows users to turn tracking off entirely through app tracking transparency (ATT). Facebook CAPI sends user data directly from your server (not the user’s device) to Facebook instead of relying on the cookie and browser data the Facebook Pixel collects. Even if the customer has opted out of marketing cookies — meaning the purchase cannot be attributed via Facebook’s Pixel ID — Facebook CAPI can send some extra user identifiers like email address, physical address, and phone number. These give Facebook a better chance of linking the purchase to a user, and from there to the ad the user clicked on. We’ll talk more about user data below. 3. Facebook CAPI captures important lower-funnel activity Facebook CAPI allows you to send more than just website behavior to Facebook. Not all server-side events happen and/or are recorded directly on your site. They may happen on your app, a free tool, a third-party payment tool, a support hub, or offline (like through phone calls). If you record this data in your CRM, you can send additional data to Facebook through Facebook CAPI. Events in payment and shopping cart tools are often lower-funnel, making them particularly important to track. 4. Facebook CAPI will be necessary when cookies are gone Perhaps most importantly, when third-party cookies are gone, Conversions API will be our only source for conversion tracking and ad performance data. Google has already announced the phase-out of third-party cookies, and as the market leader, every other service using them will almost surely follow suit. Enabling Facebook CAPI on your store now protects the accuracy of your data, even after third-party cookies have been thrown out. 5. Get a complete picture of your conversion data Facebook Conversions API helps you to see information that the Facebook Pixel can’t see as a result of ad blockers, iOS 14, ATT, and cookies. This includes website events, offline events, and ad CRM data. On the other hand, Facebook Pixel helps you to see information that Facebook CAPI can’t, such as demographic, psychographic, and other behavioral data from around the web. That’s how they work together and why each covers gaps the other has. 6. Get more out of your budget With both Facebook Pixel and Facebook CAPI working together to give you the most accurate data possible, you can: Understand exactly who is interacting with your ads Better understand the customer journey Build strong audiences and generate leads on Facebook, even with iOS 14 Make data-driven optimizations and allocate the budget accordingly Now that you know why you need Facebook CAPI, it's time to get it set up on your store. Get in touch with our data experts and they’ll help you set it Facebook CAPI, show you how to track events, and ensure you get accurate data on your ads in the new age of first-party data. [subscribe]

2022-09-02

5 things that change in Google Analytics when you install Littledata

In the modern ecommerce landscape, data is power. Making sure that your data is as accurate as possible, though, can give you the ultimate leg up on your competitors. As a Shopify store owner, ecommerce, or marketing manager using both Shopify analytics and Google Analytics, you're surely aware of the numerous benefits of using Shopify as your ecommerce platform and GA as your analytics platform. However, you’re also probably aware of the fact that these two platforms don’t really play well together, and that Shopify’s native connection with GA has quite a few shortcomings. This disconnect is what inspired us to create Littledata. We built a tool that resolves data dilemmas, restores your trust in the data from GA, and offers accurate ecommerce and marketing insights — no questions asked. Even better, many of the most critical fixes and enhancements that come with Littledata’s tracking are available right out of the box. In this post, we’ll show you five such fixes and detail how they will improve in your Shopify store’s analytics. 5 benefits you’ll get from Littledata right after install 1. Accurate attribution metrics When checking referrals to your store, you might have noticed a lot of your traffic coming with “direct/(none)” listed as the source/medium. Oftentimes, this number is a lot higher than expected (over 30%), and paid traffic channels are underrepresented. That means you have a marketing attribution problem. As soon as Littledata starts tracking sessions and events on your Shopify store, accuracy for these metrics instantly improves. That’s because the app uses a combination of two different kinds of tracking to capture full customer behaviour data: Client-side tracking, or customer data gathered from web browsers and mobile devicesServer-side tracking, or customer data gathered from web pages that fulfil clients’ requests on browsers/mobile devices Tracking both together ensures data coverage across clients’ sessions without interruption. Plus, UTM parameters alongside the GA ClientID are always passed into Google Analytics, giving you an accurate source for each visit along with previous interactions visitors may have had with your store. If you’re spending significantly on social ads and marketing campaigns, this data fix will have an immediate positive effect for calculating your return on ad spend (ROAS) and overall return on investment (ROI). Even if you’re just starting out and need to learn more about attribution to find your most valuable leads, accurate attribution stats will pay dividends for your store. 2. Revenue, transactions, and refunds One of the more well-known shortcomings of GA for Shopify stores is that it does not capture all transactions happening in Shopify, and Shopify doesn’t send refund data to GA. This creates a big revenue discrepancy between platforms and leaves you unable to trust GA’s accuracy for data about your store. To bridge this gap, Littledata relies on Shopify’s webhooks to create all transactional events server-side, making this particular problem a thing of the past. What will change in GA specifically, you ask? All purchases will show up in your GA reports with the correct order and revenue details, refunds will be tracked, and most importantly revenue in GA will match with Shopify. 3. Checkout funnel One of the biggest features of GA’s Enhanced Ecommerce is support for checkout steps. GA uses a funnel navigation path to follow your website users from the time they initiate the checkout up to the final purchase. Shopify does not track these interactions natively in GA, so it’s hard to tell where customers drop-off before buying — or even include them in a retargeting campaign. Thanks to Littledata’s server-side tracking using Shopify’s checkout webhooks, you can see those interactions and understand your customers’ behaviour in the checkout. After you install Littledata on your Shopify store, you’ll see GA’s Checkout Behaviour report now displays the correct number of users who navigated through the funnel, at each step, with the corresponding drop-offs. 4. Order affiliation There are times when seeing an ecommerce transaction event alone in Google Analytics isn’t enough. That’s especially true when you’re trying to measure the performance of third-party apps you use to manage subscriptions, upsells, product exchanges, and affiliate marketing. In these cases, you need to get more granular when analyzing a transaction using a metric like order type. Littledata shows this additional transaction data by collecting Shopify’s order tags, then making use of GA’s Affiliate Code report and Ecommerce Affiliation dimension. This is especially useful when you’re trying to count new subscribers and manage subscription analytics, measure LTV, identify product upsells, and track affiliate referrals. 5. Product List performance Many stores typically use GA’s ecommerce reporting to measure checkout performance or product revenue. However, with Littledata installed on your Shopify store, there are many more insights to be unlocked around product list performance than those basic metrics. By analyzing events at the top of the funnel, Littledata lets you identify which products need better images, descriptions, or pricing to improve conversions. Space on product listing pages is a valuable commodity, and products that get users to click on them – but don’t then result in conversion – need to be removed or amended. Equally, products that never get clicked within the list may need tweaking. Littledata tracks product list impressions on any Shopify storefront, using Google’s standard product list event properties. How to get Littledata set up for your Shopify store Littledata’s platform makes a significant positive impact on your metrics reporting right from the first time you use it. Having correct attribution, a clear picture of revenue sources from different order types, and full view of checkout funnels and product performance can make a major difference in your ROI right away. Perhaps best of all, you can see the benefits Littledata can bring to your store for 30 days without paying a cent. Plus, when you sign up for the Littledata 30 day free trial, you’ll also get custom benchmarks to target based on leaders in your industry. Sign up for Littledata to fix your analytics reporting in a snap and set your store up for the most successful year yet.

2021-12-14

Learn more about your ecommerce customers' behavior with advanced checkout funnel analysis [VIDEO]

Ecommerce analytics are tricky to begin with. Add tracking your subscription services on top of that and you’re dealing with a whole other animal! Do you use Google Analytics to report on your Shopify store’s one-off purchases AND recurring orders? Check out our video on Littledata’s advanced checkout funnel analysis to find out how we’ve made subscription analytics easy. https://www.youtube.com/watch?v=EU3Cj2Z6AII Traditional ecommerce stores typically track one checkout funnel per property. The benefit is that this makes it easy to analyze the drop-off at each point. But, if you have multiple checkouts to track one-time orders and subscription purchases, important insights might go unnoticed when GA aggregates your data. Littledata automatically differentiates between your checkout funnels to show whether they’re subscription or one-time purchases. That way you know exactly what each funnel’s checkout completion rate is for different order types. This gives you the power to tailor your remarketing strategies for specific checkouts or products, further increasing your ads’ relevance to possible customers. [note]Do you trust your subscription tracking? Get accurate subscription tracking with the ultimate ReCharge guide for Shopify[/note] Littledata integrates with the top subscription ecommerce apps—including ReCharge Payments, Bold Commerce, and Ordergroove—and automatically tracks both Shopify and subscription checkouts. “Littledata is a must-have if you’re running Recharge and Shopify; it helped us figure out what channels were getting us our future subscribers and what helped convert them.” —Better Way Health To access your checkout reports in Google Analytics, go to your ecommerce analysis reports. From there, you can view your checkout behavior reports to get a general understanding of when users are dropping off throughout the checkout process. Find out how to segment your data between Shopify and subscription checkouts to measure the exact drop-off rate at each stage of the checkout process for each checkout funnel in our latest learning video. Capture data at every turn In addition to tracking your checkout funnel completion rates for subscription checkouts, Littledata tracks crucial sales and marketing metrics, so you can:  Get accurate marketing attribution data for subscription revenue, including first-time payments and recurring chargesUse custom dimensions to measure customer lifetime value (LTV)Track performance by payment source, subscription plan type, and product categoryView complete sales and marketing data with combined server-side and client-side trackingMake better, informed decisions for your Shopify store Resources Watch a quick demo video on how Littledata worksFind out how to calculate LTV with Google AnalyticsDownload the ultimate guide to subscription trackingCheck out our ReCharge FAQSubscribe to our YouTube Channel for more videos about analytics

2021-06-08

Two ways to calculate customer lifetime value for ecommerce using Google Analytics data

Many of our customers come to us with a similar question: "how do I measure ecommerce lifetime value (LTV)?" The latest episode in our Learning Videos series shows you how to do just that for both your one-off purchasers and subscription customers. Our step-by-step tutorial covers two methods of calculating customer LTV using your Google Analytics (GA) data. You'll get to know Littledata’s custom dimensions in GA and learn how to visualize your calculations in Google Data Studio. https://www.youtube.com/watch?v=YOzHFN1ZjsA&t=21s During installation, Littledata automatically creates several custom dimensions in your connected Google Analytics property. These custom dimensions include: Lifetime Revenue, the sum total a customer has spent in your Shopify store (including one-time purchases and subscription orders)Shopify Customer ID, the unique identifier Shopify assigns to each customerLast Transaction DatePayment GatewayPurchase Count They offer better data to help you understand your customers' buying behavior, then calculate and visualize their LTV. To kick things off, you'll first need to export your data from GA to Google Sheets or another spreadsheet tool via CSV. Once you’ve enabled the GA add-on in Google Sheets, you're ready to get started. Method 1: Calculate LTV by Lifetime Revenue, Shopify Customer ID, and Transaction Count In the first method of calculating lifetime value, we’ll use Transactions as the metric. The dimensions we'll use—Shopify Customer ID and Lifetime Revenue—correspond with ga:dimension5 and ga:dimension3, respectively. Use the image below as a guide to set up your report: Next, set your Metrics Reference as Transactions and your Dimensions Reference as Custom Dimensions. After you run the report, Google Sheets should look something like this: Finally, use Google Sheets' built-in functions to calculate the average or median LTV of your customers. Method 2: Calculate LTV by Source/Medium, Transaction ID, Shopify Customer ID, and Transaction Revenue This second LTV calculation method helps you track which marketing channels bring in your most valuable customers: the ones who spend the most over time. In this method, use Transaction Revenue as the metric and Source/Medium, Transaction ID, and Shopify Customer ID as the metrics. These correspond with ga:sourceMedium, ga:transactionId, and ga:dimension1 respectively. This method requires the widest date range possible to capture the most transactional data possible—preferably since you started using Littledata. Before running the report, your Google Sheet should appear as follows: After exporting your data, your result will look like this—a list of transactions with source/medium and revenue data: Next, select all the data in your report to create a pivot table, aggregating by source/medium per customer. The result will reveal the total revenue per customer, per source. After completing the pivot table, you're ready to visualize your data in Data Studio. Build Reports in Google Data Studio Google Data Studio is one of our recommended reporting tools for ecommerce sites. Why? Because it's free, powerful, and works really well with Google Analytics. The first step in visualizing your data is to import your data into Google Data Studio by setting Google Sheets as your source. To do this, select your Google Sheets file followed by the pivot table you created in the previous method, and add it to your report in Google Data Studio. Change the data source by setting the aggregation to median so results yield the median lifetime revenue per traffic source. Your report dimension should be set to ga:sourceMedium and your metrics should be set to ga:transactionrevenue and ga:dimension1. Modify Shopify Customer ID from sum to count distinct to reveal the total unique customer IDs, which we'll use to sort our data. Sort by Shopify Customer ID to see the traffic source that brings the most customers to your site. The resulting report shows you the median lifetime revenue per traffic source, sorted by the total customers per source. References Quick Tips for Subscription Stores Using Custom Dimensions in GA 3 Deep Dives into Customer Lifetime Value for Ecommerce Sites LTV from GA vs LTV provided by Littledata How to Calculate Customer Lifetime Value in GA for Shopify Stores Custom Dimensions for Calculating Customer Lifetime Value Subscription Analytics Does Littledata work with my ecommerce reporting tool?

2021-05-27

Do you need a Google Analytics expert to help with your Shopify data?

At Littledata, we believe Google Analytics (GA) is one of the best free tools out there. Google Analytics is a great platform to access detailed data about your Shopify store’s user behaviour and sales performance. Regardless of your industry, as long as your Shopify store is in business, you need a platform where you can monitor your marketing performance and identify ways to increase your conversions.   Google Analytics is the one of the most popular analytics platforms for a few reasons: It’s free. It can show nearly any metric you want to track, straight out of the box. But with a lot of data comes a lot of complexity. Even for experienced analysts, Google Analytics can be a hurdle at times. Your Shopify data needs constant monitoring since it's the single biggest factor in your marketing and sales decisions. And who better to do that than proven Google Analytics consultants! [subscribe] What to expect from a GA expert A Google Analytics expert will (or should) always know what to look for and where to find it, even before opening GA.  Why? Because they’ve learned through experience to take the time and think through the data insights merchants need most. [tip]Here's what you should expect from a Google Analytics expert[/tip] On the other hand, if you’re taking the self-learning path and tackling GA by yourself, you’re really trying to achieve two things at the same time: become a web analyst and learn the GA platform. But are either of those time-efficient tasks to help grow your store? Probably not. Here's another thing: while a Google Analytics expert will help you make sense of your Shopify data, it's the digital implementation specialist who ensures you have the right Enhanced Ecommerce Conversion (EEC) data in your GA dashboard in the first place.  Whether your EEC tracking will be implemented via GTM or other tools, the end game is the same: Get me the correct data in GA. And for this, Shopify and Shopify Plus stores are in luck — Littledata automates the EEC tracking so you don’t have to. Why get an expert? If Littledata automates tracking, why is it necessary to hire an expert? For things like Day to day checks on basic metrics like revenue and transactions Basic campaign monitoring for Facebook Ads, Google Ads, etc. For the most part, you can do these on your own. But a tool like Littledata provides the raw data in Google Analytics for much more granular insights, and that’s where a GA expert will come in handy. Here's an example: With every transaction, Littledata accurately sends to Google Analytics a set of raw properties (e.g. Shopify CustomerID, TransactionID and campaign parameters).  For this data, a Google Analytics expert will be able to link the source or campaign path with customerID’s and transactionID’s in a custom report. This custom report will show the true return on ad spend (ROAS) based on different attribution models. Determining which conversions are linked to a first interaction or an assisted interaction will help you measure and optimize your marketing campaigns with more accuracy. [tip]Find out the real ROAS of your Facebook Ads for your Shopify store[/tip] Metrics that matter One of the main metrics marketers want to know is Customer Acquisition Cost (CAC) per channel. If you get that right, you’ll know exactly where to increase your marketing spend. And in doing so, you’ll probably acquire more customers for about the same fixed budget.  A GA expert will be able to gather your (true) marketing costs from all your marketing campaigns over a given time period, and calculate the amounts by channel. This sounds easy, but things can get a bit more complicated when you're trying to find the CAC based on each attribution model. By now you should know your ROAS and CAC, but what about customer lifetime value (LTV)? In other words, you should know how much $$$ your marketing leads are spending with you, what your acquisition cost is per customer, and where to find the highest converting leads. But do you know how much time they are spending with your brand? Which channels are bringing the stickiest clients? Which channels bring the most repeat purchases (or subscriptions)? LTV is one of the most coveted metrics for ecommerce managers. A GA expert will help you calculate LTV by summing up the gross profit from all historic transactions for each individual customer, then splitting those conversions by channel and calculating the median for each.  And if you want things laid out for you in plain english, at Littledata we provide the necessary custom dimensions you need to accurately calculate LTV.  So what's the verdict? For Shopify merchants, Littledata is one of the best solutions to ensure reliable data for accurate marketing attribution and buyer behaviour. And since your Shopify store already needs fixing when it comes to data collection, an enterprise plan (with full support and a dedicated team of Google Analytics consultants) just may be an answer to your prayers.  With Littledata enterprise, get all the analytics support you’ll ever need, for a fraction of the cost to hire an experienced Google Analytics consultant. Get in touch with our team today to see how an enterprise plan can accelerate your path to scale! ?

2020-02-25

How to set up cross-domain tracking in Google Analytics

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"]

2019-11-19

New Klickly integration for Shopify stores

We're excited to announce a new integration with Klickly! Get ready for smarter analytics. Many Shopify stores know that their data isn't accurate, but they don't know where to start. Littledata tracks everything automatically. Our new Klickly integration offers full sales and marketing tracking, plus a free custom report to help you get higher ROI on Klickly campaigns. [note]*updated* Since dissolving the Klickly integration, we've enhanced our marketing attribution smart connections even more, including Google Ads and Facebook Ads.[/note] What’s Klickly? Klickly is an invite-only, commission-based advertising platform that enables ecommerce merchants to run unique buyable ads on thousands of well-known websites. With risk-free, commission-based pricing, you don't pay commission until Klickly gets you a sale. Setup takes less than 10 minutes, and there are no long-term agreements or fees. Stop paying for clicks + impressions that don’t lead to sales. Klickly lets you pay only when ads drive sales and set the commission that’s right for you. Benefits of Littledata's Klickly integration: Campaign reporting – Get automated reporting for sales from Klickly Ads Marketing attribution – Connect marketing channels and campaigns with shopping cart activity and buyer behaviour, with automated tracking for Shopify stores Optimisation – Make data-driven decisions with Littledata’s industry-leading analytics audit, smart connections and industry benchmarks Setup guide For the Littledata - Klickly integration to work, you need to have both apps installed for your store. Install Klickly and Littledata Ask the Littledata support team to activate the Klickly report for you Yes, it’s that easy! You can contact Littledata support from the Intercom widget in the app, or just reply to any of our onboarding emails :) Enterprise plans for larger Shopify stores and Shopify Plus If you run a larger Shopify store on Shopify or Shopify Plus, we’re here to help you scale. Littledata offers enterprise plans that include custom setup and a dedicated account manager. This can include anything from GTM setup to custom reporting. Larger stores looking for an enterprise plan are encouraged to sign up for a free trial of Littledata, then contact us for a free consultation so we can take an in-depth look at your setup. If you’re a digital agency with multiple customers on Shopify using Klickly, even better! Check out our agency partner program for Shopify experts. If you're looking for accurate, actionable analytics, Littledata's new Klickly integration will help you scale the smart way. Say hello to a better way! [note]*updated* Since dissolving the Klickly integration, we've enhanced our marketing attribution smart connections even more, including Google Ads and Facebook Ads.[/note]

2019-05-23

Why don't my transactions in Google Analytics match those in Shopify?

The truth is that Google Analytics and Shopify need a little help to play nice together. Most marketers use Google Analytics to track performance, but having a good data collection setup -- even for basic essentials like transactions and revenue -- is harder than it looks. As a Partner Manager at Littledata, I work with a wide variety of apps and agencies, especially Shopify Plus Partners, who are in turn working with marketing managers and ecommerce directors. One of the most frequently asked questions I get from those marketers is “Why don’t my transactions in Google Analytics match those in Shopify?” [tip]Here's why your Shopify data doesn't match what you see in GA.[/tip] So in this article I’d like to take you on a journey, explaining what could cause this, how it can affect marketing and how to get accurate data that matches your actual money in the bank. Top 6 reasons for inaccuracy There are many reasons for differences in tracking results, but let’s take a look at the top 6 reasons. 1) Some orders are never recorded in Google Analytics Usually, this happens because your customer never sees the order confirmation page, and most commonly this is caused by payment gateways not sending users back to the order thank you page. 2) The Analytics / Tag Manager integration has some errors Shopify has an integration with Google Analytics but it is a pretty basic one, tracking just a few of all the possible ecommerce events and micro-moments required for a complete picture. Although Shopify’s integration is meant to work for most standard websites, there are those who build a more personalised theme. In which case they would require a custom integration with Google Analytics. (Here’s what you can track with Littledata’s Shopify app) 3) A script in the page prevents tracking to work on your order thank you page Many websites have various dynamics on the thank you page in order to improve user experience and increase retention. But these scripts can sometimes fail and create a domino effect preventing other modules to execute. Such errors can stop Google Analytics from tracking the event. 4) The user has opted out from Google Analytics tracking This instance is not encountered as often, but it’s worth mentioning that some users can opt out of Google Analytics tracking with the help of a simple browser add-on. Features like this work by adding bits of JavaScript code into every website the user visits which will prevent the Google Analytics tracking code from capturing user-related data. This also means that GA will not drop any cookie nor will send any data to its servers. [subscribe heading="Try Littledata free for 30 days" button_text="Free Trial" button_link="https://www.littledata.io/app/get-free-trial"] 5) Too many products included in one transaction Every time a page on your website loads, Google Analytics sends a hit-payload to its servers which contains by default a lot of user data starting from source, path, keywords etc. combined with the data for viewed or purchased products (name, brand, category, etc). This data query can get quite long if the user adds products with long names and descriptions. But there is a size limit for each hit-payload of 8kb, which can include approx. 8192 characters or information for about 20 products. Where this limit is reached, Google Analytics will not send the payload to its servers, resulting in lost purchase data. 6) Too many interactions have been tracked in one session This inconsistency is not encountered as often, but it needs to be taken into account when setting up Google Analytics tracking. One of Google Analytic’s limitations for standard tracking is that a session can contain only 500 hits. This means that interactions taking place after the hit limit is reached will be missed by Google Analytics. How a data mismatch damages your bottom line We have found that 8 out of 10 Shopify merchants have only a 70 - 80% accuracy rate for transactions and revenue in Google Analytics mostly due to the reasons mentioned above. In other words, 80% of Shopify merchants are missing at least 20% transaction data! Statistically, small or even medium-sized merchants dealing with four-figure monthly revenue can be very affected by the missing data because they are more likely to take bad marketing decisions based on segmented data. Hyper-segmentation is counterproductive if you’re working with bad data. And for larger business which rely heavily on Google Analytics to make data-driven decisions, accuracy is an absolute must. Imagine having a 20% inaccuracy margin when dealing with six or seven figure monthly revenue! It kind of puts things into a different perspective, right? It would be quite impossible to know how much to invest & re-invest in marketing without knowing the actual ROI. But wait! There’s an easy fix Littledata’s Shopify app can automatically fix most of the tracking inconsistencies mentioned above. Here’s how our app works, it's like magic. First, the app adds a DataLayer on your website containing all the Enhanced Ecommerce events. Then it inserts a tracking script on each layout which captures every fired event as soon as it occurs, and then using Server Side tracking, the app listens for all transactions to ensure 100% accuracy. In addition to the guaranteed transaction accuracy, Littledata’s tracker attributes each sale by source together with granular user and product data. The app also sends custom information in 4 custom dimensions to understand KPIs regarding lifetime value (LTV). Sound pretty geeky? It is. But the cool part is that the app uses automation and machine learning to do all the heavy lifting for you, so you can focus on growing your business instead of worrying about tracking issues. And the tech extends to all the apps you use. We include smart connections with apps like ReCharge and Refersion, to ensure accurate data about every marketing channel and product mix, including subscriptions. For example, our ReCharge connection automatically tracks both first-time payments and recurring transactions. This gives you accurate sales data and marketing attribution for those sales. Compare different tracking methods I know it may sound too good to be true, and this is why we offer a 14-day free trial so you can test the results by creating a Test Property in your Google Analytics account and compare data between Shopify’s standard tracker and Littledata’s advanced solution. Once you have accurate data, you can start benchmarking against other Shopify sites and optimising your website with data-driven decision making. Questions? Littledata is here to help. We built our smart ecommerce analytics app to simplify everything, and with a clear picture of your ecommerce data and access to automated optimization tools you can truly take your business to the next level. Are you ready for accurate data?

2018-12-14

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