Category : Google Analytics
10 reasons to move to GA4 for ecommerce analytics
In November 2020 Google surprised the analytics world by making the beta of Google Analytics 4 (GA4) the default for all new web properties. Many GA4 ecommerce features are yet to be released, but I think there are compelling reasons to start using GA4 now, especially for data-driven Shopify Plus stores.Google is clear that GA4 is the future for integrating marketing data with Google Ads. Yet there's more to the picture, including custom funnels and other key features which were previously restricted to GA360 (costing $100k and upwards per annum), but are now free for anyone to use in GA4. Here are my top 10 benefits of GA4 from a data analyst’s perspective: Faster reportingCustom funnels *Analysis module *Export raw data to BigQuery *No event collection limits *Track mobile app events alongside web events **Streamlined audience buildingPredictive insightsMore custom dimensions *There’s more to come * Previously only available with GA360** Requires a roll-up property in GA360 Read on to dive into the details of each reason. We'll look at what's new in GA4 and how we expect these features to be useful to ecommerce managers and data scientists. 1. Faster reporting If you’ve used GA with high-traffic sites, especially with GA 360 properties, then you’ll be all too familiar with the ‘Loading…’ bar -- waiting many minutes for some reports to load. Ultimately Universal Analytics was built on 10-year-old data processing, and although the GA4 user interface looks similar, Google has rebuilt it from the ground up for speed and flexibility. In GA4, standard reports generate more quickly and are more powerful at the same time, bringing us to Reason #2: Custom funnels. 2. Custom funnels Goal funnels have always been a useful feature of GA, but the full power to choose a series of events to analyze was previously restricted to GA360, due to high processing costs. With GA4 you easily build a funnel using any combination of events or pageviews, filtered by any event property (see reason #9), with clever features like measuring elapsed time through the funnel. This is equivalent to the funnel functionality that made Mixpanel and Amplitude really popular, and is a massive upgrade on the previous version of GA -- where you could only add events or pages but not both. And where you had to set the goal funnel up in advance to see any report at all! 3. Analysis module The funnel reporting is part of a new ‘analysis’ tab in GA4 that brings more powerful report-building functionality. Compared with the previous ‘custom reports’ in Google Analytics (Universal Analytics), it is more intuitive to add dimensions, with more report templates like the Segment Overlap report below. Hopefully Google extends the template gallery to allow other analysts to share reports, as we’d love to see more reports for ecommerce metrics. 4. Export raw data to BigQuery This is a big one. Power users who wanted to go further and run their own algorithms, or build unsampled reports from raw, row-level data, previously needed a GA360 account. In GA4 you can set up an export to Google BigQuery, steaming events within a few minutes of them being recorded from your website. You pay for the BigQuery transfer and storage, but this is free for smaller sites and merely hundreds of dollars a month for larger sites. This makes GA4 + BigQuery a very viable data warehouse solution for ecommerce, and an insurance policy if you want to own your own data for future analysis. 5. No event collection limits In the free version of Universal Analytics you are limited to 10M hits (pageviews and events) per month, and 500 hits in any one session. For GA4, Google’s policy is ‘there is no limit on the total volume of events your app logs.’ Google has made no announcements on GA360 support for GA4, so these event limits may be subject to change. However, I see unlimited event collection as fitting with Google’s strategy to enable more ad retargeting and head off competition from tools like Heap (which has always advocated maximum possible event collection).There are limits to data export via the reporting API, with higher quotas for GA360 customers. But those limits could be bypassed by maintaining a BigQuery export (see above). 6. Track mobile app events alongside web events GA4 was originally called ‘app+web’ as it built on Firebase’s tracking for mobile apps and extended this tracking for web. Google calls this ‘customer-centric measurement’ as it allows the user-identified app sessions to be measured side-by-side with public website / web app sessions, where user-identification is harder. You could do something similar with roll-up properties in GA360 previously, but getting user identification right was a pain. I don’t rate this as a key feature for ecommerce, because most stores only run a public website, but if you are investing in a native mobile experience for loyalty then this is a killer feature for you. [subscribe heading="Love analytics? Littledata is seeking an Analytics Advocate" button_link="https://blog.littledata.io/2021/01/29/shopify-analytics-littledata-is-hiring/" button_text="See Open Positions"] 7. Streamlined audience building It is telling that one of the first features launched for GA4 was linking a Google Ads account. Google wants to make GA4 the key way you build audiences for retargeting, and export them to Google’s other products. In GA4, Audiences can be configured with any combination of events, demographics or channel, and then synced with Google Ads. For example, let’s say you want to retarget users over the next 30 days who added a product from the ‘handbags’ category to cart, with a value of more than $100 -- but never purchased. No problem! Go ahead and include users who have triggered the add to cart event with a certain product category and product price, and exclude those that triggered a purchase. 8. Predictive insights GA4 adds a number of features for predictive insights. For example, in analysis and audience building you can add predictive metrics: purchase probability and churn probability. Purchase probability is the chance that a user will purchase in the next 7 days, based on their patterns of behavior so far. Churn probability is the chance that they will no longer be an active user in 7 days. This further improves the kind of audiences you can build. How much more would you be willing to pay to re-engage customers that were in the top 10% of people most likely to buy? For ecommerce analytics, we see predictive insights being used alongside metrics already enabled by Littledata's tracker, such as LTV by channel. Yet another reason to be excited about GA4 for DTC growth. 9. More custom dimensions and user properties At Littledata we add custom dimensions about user behavior over time (their lifetime spend, date of last purchase, and more) to aid in audience building and LTV analysis. This used to eat into the 20 custom dimension slots provided in Google Analytics, but with GA4 you can specify as many hit-scope dimensions with events as you like (not just limited to Category, Action and Label). You can also add up to 25 user properties that are persisted with each user as they get tracked across your site. The only downside is there is no support for product-scope custom dimensions (like sizing or gross margin) as such. You can add multiple item_category fields, which could be used as extra product fields, but I hope custom product properties are on the roadmap. 10. There’s more to come Google stopped developing Universal Analytics a few years ago and any new features will only launch on GA4. Although GA4 is not yet perfect I am really excited about the direction and speed of travel of the product. As Spencer Connell at Praxis Metrics puts it: “GA4 feels like a house which is 60% built - missing a couple of walls, and maybe the roof … but you definitely don’t want to wait until the house is 100% finished before you start moving in.” At Littledata we’re so excited that we have built a beta GA4 connection for Shopify, and we will launch it just as soon as GA4’s APIs are ready. Please get in touch in you're interested in access to the beta release. What you can do now If you want to watch the GA progress from the sidelines, keep checking for GA4 product releases and jump in when you’re ready. But I recommend getting started right now by tracking your site on GA4 in parallel with Universal Analytics (or ‘doubling tagging’ in marketing analytics speak). Josh Katinger at our Google Analytics Sales Partner, Cardinal Path, explains: “Why now? You need an overlap of data. Moving to GA4 is really equivalent to a migration from Adobe Analytics - it’s a platform migration. And when you have a platform migration you want to have overlap, so you have time to understand the difference in the data model, understand the data variations and how to handle them. We are counseling everyone to double tag if you can.” Note that adding GA4 tracking to a Shopify store will not slow down your pages, as Littledata shares the same gtag tracker and server-side tracking for both versions of GA. Have you already started playing around with GA4? Let us know what you've discovered. [subscribe heading="Love analytics? Littledata is seeking an Analytics Advocate" button_link="https://blog.littledata.io/2021/01/29/shopify-analytics-littledata-is-hiring/" button_text="See Open Positions"]
Product update: Shopify Order Names
We are pleased to announce a product update for how Littledata tracks unique identifiers for Shopify orders. Previously Littledata passed orders from Shopify to Google Analytics (or Segment) using only the order number (Order ID). Shopify offers the ability to add a prefix or suffix to this number to create an order name, and we now support Shopify Order Name tracking in addition to Shopify Order ID tracking. You can now choose between tracking either the Shopify Order ID or Shopify Order Name, and Order Name tracking is the default for new installs. Read on to see what's changed, and why we made the shift. What was the problem with tracking order numbers? There is nothing wrong with tracking order numbers per se, but for some Shopify stores -- especially larger brands on Shopify Plus -- it's often more useful to track the complete order name, which includes a particular prefix or suffix. Brands running multiple Shopify stores in local currencies often want to analyze total sales across geographic operations, while also segmenting by individual stores. This is useful whether or not you are using a rollup property for data analysis. With only order number tracking, there were two options: The largest brands, running GA 360, could set up a different web property for each store and then a 'rollup property' for all the stores. This option is expensive.The brand could send all the web orders to one GA web property, and then create filtered views based on the hostname the order was made on. But this didn't work for non-Shopify checkouts, such as ReCharge, where the hostname did not vary by store. So Littledata built a third option, order name tracking, which makes it easier to track multi-currency sales in GA and other data destinations, and also ensures no clashes with order numbers from non-Shopify systems. How to change the order ID format for your Shopify store Shopify and Shoify Plus merchants can change their Shopify order numbers to include a particular prefix and/or suffix. If you want to make this change, go to Shopify Admin > Settings > General > Standards and formats. Here you can configure a prefix or a suffix to every order, unique for that store. While you can't change the order number itself, you can add this default info to make it easier to see and segment your orders. For example, if you are selling in the US and the UK, you might want to add country-type prefix to your orders, such as 'US' and 'UK' to those country stores. Then your orders will come through with order names such as 'US1792' and 'UK1793'. [subscribe] How to enable Order ID or Order Name tracking in Segment or Google Analytics Shopify Order Name tracking is now the default. So if you installed Littledata after 19th October 2020, then you will already be using order names. This applies to both our Segment connection and our Google Analytics connection in the Shopify App Store. [note]If you installed Littledata after 19th October 2020, then we will be tracking the Shopify Order Name by default. You can change this in your Littledata Settings.[/note] If you installed Littledata before 19th October 2020, we will be tracking Shopify Order ID by default. You can check which unique order identifier we're using for your store, and make any necessary changes, directly in the Littledata admin. Go to Settings > General on the bottom leftUnder Unique identifier for all orders, select either "Shopify Order ID" or "Shopify Order Name"Click Save We will then pass the order information in your chosen format. How to use the data in Google Analytics Order identifiers offer a broad range of reporting and analysis possibilities in Google Analytics and connected analytics dashboards. Here's the ecommerce Sales Performance report showing orders including the prefix appearing in Google Analytics. If you are operating multiple country stores and using Littledata for multi-currency tracking, you will see different prefixes here for each currency. You can also create a segment including only orders with that prefix, by filtering by Transaction ID. What's next We are constantly enhancing Littledata's functionality. This year we have introduced a range of general updates and a new version of our Shopify to Segment connection. If you are setting up a raw data pipeline, we also now offer a Measurement Protocol connection for use with a range of ETLs, data collection platforms (like Snowplow) and data warehouses (like Google BigQuery). Check out our release notes to stay up to date, and don't forget to browse the complete documentation in our help center.
How to track Klaviyo flows and email campaigns in Google Analytics
Klaviyo is one of the most popular email marketing platforms for Shopify stores, but the analytics setup is often overlooked. By following a few simples rules, you can ensure accurate Klaviyo data alongside other sales and marketing data in Google Analytics. In this article we cover how to set up Google Analytics tracking for Klaviyo, including best practices for UTM parameters and dynamic variables, and how this tracking works alongside Littledata's Shopify to Google Analytics connection. Why Klaviyo Klaviyo is a popular customer engagement platform used by over 50,000 Shopify merchants. Their focus is on email and SMS automation, and they have been one of the major success stories in the Shopify ecosystem, recently closing a $200 million funding round. Klaviyo's features for Shopify include: Codeless signup forms Pre-built flow templates for quick automation Email campaigns for customers and leads Advanced segmentation and personalization, including product recommendations Many of Littledata's Shopify customers use Klaviyo in one way or another, as do almost all of our Shopify Plus customers. But we've noticed a trend where even the biggest Klaviyo users aren't correctly tracking Klaviyo flows in GA, which ends up blocking data-driven decisions for growth. Read on to see how to fix this. Why Google Analytics The Klaviyo dashboard has useful built-in reporting, but for ecommerce managers focused on more than just email, there are some significant limitations compared with a dedicated analytics platform like Google Analytics (GA). One key limitation is for sales attribution (marketing attribution for online sales). In Klaviyo, any sale that happens after engagement with an email is attributed to that email. This overstates Klaviyo's contribution to sales. For example, if a user first comes from a Facebook Campaign, then clicks on an abandoned cart email from Klaviyo, then goes on to complete a purchase after being retargeted in Facebook, Klaviyo will claim this as owned revenue attributed to that email engagement and credit Facebook with nothing! Another limitation of reporting in Klaviyo's dashboard is that it's hard to see the contribution of an entire email flow to sales, as opposed to the impact of a particular email message in the flow. In Google Analytics (if set up correctly) you can see multi-channel contribution to sales, comparing apples with apples across different marketing channels. What is UTM tracking? UTM parameters are extra data in the link the user clicks to tell Google Analytics (and Shopify) where the click came from. These parameters are automatically added by Google Ads, but for other platforms (e.g. Facebook or Klaviyo) you will need to add them manually or via the software. Why does this matter? Because link clicks coming without a UTM tag will typically be treated by GA as "direct" traffic -- in other words, the source of those visits will be unknown. [note]Read Littledata's free guide to common reasons Shopify doesn't match Google Analytics[/note] Recommended settings To provide the most reporting flexibility we recommend having the same standard UTM parameters across all email flows and campaigns. Klaviyo allows dynamic variables to be used in your default UTM tracking settings. To get the most out of your Klaviyo reporting in GA, we recommend using static values for Source and Medium, and dynamic values for Campaign and Content. You can change these defaults in go to Account > Settings > UTM Tracking UTM Parameter Campaign Email Value Flow Email Value Source (utm_source) 'Klaviyo' 'Klaviyo' Medium (utm_medium) 'email' 'email' Campaign (utm_campaign) Campaign name (Campaign id) Flow email name (Flow email id) Content (utm_content) Link text or alt text Link text or alt text [tip]Content is not a default parameter in Klaviyo, so you will need to add that manually (enter `utm_content` as a new parameter).[/tip] With static values for Source and Medium (Klaviyo / email), you will be able to see Klaviyo compared against other marketing channels in GA, and in particular how Klaviyo campaigns contribute to customer lifetime value and other key metrics for Shopify sales and marketing. We do not recommend sticking with Klaviyo's default UTM settings, where Klaviyo flows, for example, are given a dynamic variable that pulls in the name of the flow. You can already see that type of data in the Klaviyo analytics dashboard -- better to use GA for complete marketing analysis. Whichever naming convention you choose, consistency is essential. Many Littledata customers create internal spreadsheets to manage UTM naming conventions and channel groupings in GA, and run regular QA checks to ensure consistency. Note that we have analytics audit checks within the Littledata app, and we now offer analytics training on Plus plans. Enabling UTM parameters In addition to setting up the UTM Parameter values in your Klaviyo account, you need to enable UTM tracking to ensure that those parameters are applied to all emails in flows and campaigns. The first step is to enable global UTM settings. Go to Account > Settings > UTM Tracking Switch Automatically add UTM parameters to links to ON. Then click Update UTM Tracking Settings. This will ensure that the UTM parameters are added automatically to all emails sent via Klaviyo. Now that you have enabled UTM tracking, you need to make sure that you are using 'account defaults' for UTM tracking in your flows and email campaigns (as opposed to custom tracking). This should already be the case, but it's good to double-check. Disable any custom UTM tracking for flows or campaigns Make sure that the UTM settings for individual flows are set to 'Yes, use account defaults' Make sure that overall email campaign settings are set to use default UTM tracking as well. In your overall campaign settings, select 'Yes, use account defaults' In addition, when creating/editing a campaign, go to Tracking and make sure that 'Include tracking parameters' is ON and 'Customize tracking parameters' is OFF Tracking across all marketing channels The UTM settings above only solve part of the marketing attribution problem: getting the campaign information to the landing page. Commonly this marketing attribution is lost between the landing page and the order completing. You can try to do this manually with an in-house dev team, but Littledata has built a complete ecommerce tracking solution for Shopify and Google Analytics that works automatically. Our connections use a combination of client-side and server-side tracking to make sure that all marketing channels -- including email, paid channels, organic search and referrals -- are linked to sales, along with all touch points in between. We also track returns/refunds, repeat purchases, and subscriptions, so you can understand customer lifetime value on a deeper level. Read about all of the the events Littledata sends automatically. You can use these events for reporting and analysis, and also to build audiences for your Klaviyo campaigns! Reporting on Klaviyo flows in Google Analytics Google Analytics is a powerful reporting tool once you get to know how channel groupings and custom dimensions work. Here's a quick look at how to analyze your Klaviyo data in GA. Looking at campaign conversions in Google Analytics After you have enabled our recommended settings for UTM tags, you will have access to Klaviyo flow and campaign data in GA. You can look at this on its own, but also compared against other channels for engagement and acquisition. To see revenue and orders attributed to these campaigns, drill into the Klaviyo source and add campaign as a secondary dimension. If you set up the Flow email name as the utm_campaign above, then you can look at the contribution of that whole flow to sales. For example, without caring if the user clicked on email 1 or 2 in a 4-email flow, did clicking on any of the emails in that flow -- for example, the 'Browse Abandonment' flow -- result in sales? Going further, you could create a segment of users who came via an Instagram campaign, and see to what degree they were influenced by the email sequence. Will Google Analytics match Klaviyo? How does the data you now have in Google Analytics compare with what you see in your Klaviyo dashboard? Under the Conversions > Multi-Channel Funnels > Model Comparison Tool in GA, you can compare the default email attribution in GA (last non-direct click), with other attribution models more similar to Klaviyo's dashboard. Keep in mind that there is no model for 'all click' attribution, so the numbers you'll see in GA will always be lower. You can also look at the Multi-Channel Funnels > Top Conversion Paths report to see where Klaviyo fits into the user journey on your ecommerce site. [note]Google Analytics data can also be used as a source for other reporting tools, such as Data Studio and Tableau.[/note] Using Klaviyo with Segment If you are looking to do more with your Shopify and Klaviyo data, consider Segment. Littledata's Shopify source for Segment automatically sends a rich data set for use with a range of Segment destinations. Not only does our Segment connection get all of the post-click events into Segment, but it also sends any event associated with an email address onto Klaviyo as well -- providing a richer set of events, without a developer, than Klaviyo's own Shopify event tracking. For example, you can retarget users in Segment who have purchased a certain value, or got certain products to a stage of the checkout -- all without writing a line of code. Read more about how Littledata's Segment connection works, and check out the latest updates to our Shopify source for Segment. The connection now supports analytics destinations such as Mixpanel, Vero and Kissmetrics, and email marketing destinations including Klaviyo, Hubspot and Iterable. [subscribe]
Going international? How to optimize for BFCM sales around the world
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]
3 deep dives into customer lifetime value for ecommerce sites
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]
Why does shop.app appear as a referral source in Google Analytics?
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. 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.
How to get accurate Shopify data in Google Analytics (VIDEO)
If you're using Google Analytics to report on Shopify data, you need to watch this video. Ecommerce analytics were complicated, so we built a better way. Don't spend money on custom setups or expensive ETL configurations for your analytics. Just use this one automated tool. Check out this quick demo of Littledata's popular Shopify to Google Analytics connection, available in the Shopify app store. Littledata is the easiest way to automate Google Analytics for your Shopify store. By connecting your Shopify store to Google Analytics, get: Smart audits to check for accurate tracking Seamless connections with apps like ReCharge and CartHook Benchmarks against thousands of ecommerce sites Easily extensible via Google Tag Manager (GTM) Own the data in Google Analytics And that's not all. We also add custom dimensions to track LTV and payment gateways like Klarna, Paypal and ShopPay. In the video above, see how the Littledata Shopify app for Google Analytics fixes tracking automatically. Fix your tracking Littledata works behind the scenes to fix your Shopify tracking and ensure accurate data. From marketing channels to checkout steps, Littledata's automated audit checklist gives you a clear picture of what to track and how to track it, and how each integration works. [note] Why doesn't Shopify match Google Analytics? Get the Shopify analytics ebook. [/note] Benchmark your Shopify site Say goodbye to guessing games and start benchmarking your site against top performers with Littledata's automated benchmark tool. Filter by industry, location, website size and more. We look at technical factors like server response time, as well as classic ecommerce benchmarks like conversion rates by device (mobile vs desktop). Check out the top Shopify benchmarks to get started. Automatic tracking for marketing and checkout apps Scalable tracking for Shopify and Shopify Plus Automated import of Facebook Ad Costs and Instagram Ad Costs Checkout flows like CartHook Subscription ecommerce apps like ReCharge and Bold Subscriptions [note]Do you trust your Shopify tracking in GA? Here's a free guide to how you can[/note] If you're about to watch this video, chances are that you're still doing analytics by hand. Or you've tried other apps that were just connectors -- they didn't fix the tracking. Littledata works with popular reporting apps like Google Data Studio, Tableau and Power BI. Littledata's app for Shopify will give you an edge on the competition with accurate data across the entire customer life cycle. For ecommerce managers and developers With Littledata's smart script to fix your tracking, you can enjoy accurate data about marketing channels, product performance, transactions, revenue, shopper behavior and more! Check out our help center for documentation and free training on: Tracking the Shopify checkout funnel events The best GTM and Google Analytics data layer for Shopify How to use custom dimensions to calculate LTV We're here to help you make data-driven decisions based on accurate data. Let us keep up with the complications of webhooks, APIs and server-side tracking, so you can focus on scaling your business! Get started with a 30-day free trial for a full month of accurate Shopify data. [subscribe]
What's new for ReCharge tracking
Are you ready for ReCharge v2.3? The latest version of Littledata's popular ReCharge connection is more powerful and extensible than ever. Subscription ecommerce is booming right now, especially for consumables like wine and coffee. Many Shopify stores are even seeing Black Friday-level traffic. But there's also more competition than ever. ShipBob has noted that subscription discounts are especially popular right now, during the seemingly endless days of COVID-19, as a way to bring new subscribers to your brand. This is a major opportunity -- but it also means that there's a lot more competition. Data is more important than ever to understanding your store performance and benchmarking your site, choosing the best marketing channels for your products and targeting the best customers with a higher lifetime value (LTV). Data is more important than ever to understanding your store performance So what exactly can you track with Littledata's ReCharge integration? ReCharge integration for Google Analytics Our ReCharge connection has gone through a lot of updates over the years, based on feedback from our customers, including smaller Shopify merchants, larger DTC brands on Shopify Plus, and our agency partners around the world. Earlier this year, ReCharge v2 saw the addition of subscription lifecycle events. ReCharge v2.3 is now available to all merchants, with the addition of events to track the ReCharge checkout funnel -- and segment by product and marketing channel. So what's new? Clearer segmentation of first time vs recurring orders When you add Littledata's ReCharge connection we now add three Views in Google Analytics to help segment the data: One-time orders and first-time subscriptions - A good way to track initial purchases. We automatically filter out duplicate and recurring orders from this view. All orders - All orders placed on your store, including one-time orders, first-time subscriptions, recurring orders, and prepaid orders. Raw backup - A raw data backup with no filters! This separation enables stores to easily calculate Customer Acquisition Cost (CAC) on one-time orders and first-time subscriptions. Furthermore, for all the subscriptions that started after you installed Littledata’s ReCharge connection, you can group them by subscriber (Shopify customer ID) or by marketing channel or campaign for insightful Return on Investment (ROI) calculations. Read more about how Littledata works with Views and Filters. Checkout funnel events Starting from June 2020, stores on ReCharge v2.3 can see checkout step events to match the checkout events sent from the Shopify checkout. Littledata’s checkout tracking works without the need to add Google Tag Manager or other tracking scripts to the ReCharge checkout, simplifying implementation -- and reducing the risk that 3rd party script interrupt or intercept the sensitive payment details. Excluding prepaid subscriptions Stores generating prepaid subscriptions were seeing duplicate orders when that subscription eventually got processed. In the new One-time orders and first-time subscriptions view, we filter these duplicates out automatically. Custom dimensions for LTV and more Our ReCharge customers benefit from the same user-scope custom dimensions in Google Analytics that we have for all Shopify stores, allowing you to segment and retarget audiences based on data such as their lifetime spend, date of first subscription, or number of subscription payments. Marketing attribution All of these ReCharge v2.3 updates work with our smart tech for accurate marketing attribution. What's the real ROI on your Facebook Ads? Do customers who pick higher-value subscription bundles come from a particular channel? See how Littledata fixes marketing attribution automatically for Shopify stores, with a combination of client-side (browser) and server-side tracking. [tip]Read our reviews to see what ReCharge customers are saying about Littledata! [/tip] ReCharge integration for Segment Our ReCharge integration is now fully compatible with our Shopify to Segment connection, so if you want to send Shopify and ReCharge events to Segment, we've got you covered. This is a seamless way for ReCharge stores to get revenue and customer information into Segment's hundreds of destinations. Headless Shopify tracking for ReCharge ReCharge Connection v2.3 is fully compatible with Littledata's headless tracking solution. Stores using ReCharge's new Checkout API can use Littledata's headless demo to show you how to get the same seamless customer journey from storefront, through checkout to purchasing. Littledata is the only tracking solution compatible with headless ReCharge setups, including those built by our amazing tech partners like Nacelle. ReCharge in-app analytics ReCharge has also launched a powerful in-app analytics feature available to all users. ReCharge launched Enhanced Analytics for Pro customers in 2019 to allow cohort and metric tracking. This is a powerful feature, but it’s different from what Littledata does. The most successful brands are using both tools. ReCharge’s analytics feature offers easy ways to visualize your ReCharge data in the app, while Littledata fixes sales and marketing tracking and sends that data to Segment or Google Analytics. What you can do ReCharge Enhanced Analytics Littledata + Google Analytics Littledata + Segment Look at trends in subscription sign-ups and cancellations ✔ ✔ ✔ Analyze churn rate by cohort or product ✔ ✔ * ✔ * Visualize cohort retention ✔ Fetch last-click source and medium (UTM parameters) from subscription API ✔ Analyze multi-channel marketing contributions to subscription sales ✔ ✔ ✔ Attribute recurring orders back to marketing campaigns ✔ ✔ ✔ Analyze Customer Lifetime Value including non-ReCharge spend ✔ ✔ Track charge failures by any customer attribute ✔ ✔ Track subscription cancellations or upgrades by any customer attribute ✔ ✔ Track customer updates by any customer attribute ✔ ✔ Track usage of the customer portal on our site by any customer attribute ✔ ✔ See how any ReCharge customer event connects to the pre-checkout behaviour of the user ✔ ✔ Look at cancelation rate by marketing channel ✔ ✔ ✔ Trigger transactional emails based on changes to subscriptions ** ✔ Retarget segments of ReCharge audience in common marketing destinations ✔ * Requires additional analysis in a spreadsheet** In Segment destinations such as Iterable How do you get all this? If you're already a Littledata customer, you can update to ReCharge v2 directly in the app (just login and you'll be prompted to upgrade if you haven't already). New to Littledata? We now offer a 30-day free trial on all plans, and setup only take a few minutes. If you are looking for more support, like account management or analytics training, please contact us about enterprise plans.
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