What you can track with Littledata's Google Analytics app for Shopify

Here at Littledata we believe that everyone should have access to professional-level analytics tools for tracking, reporting, and improving sales and engagement. That's why we built the ultimate Shopify app. Shopify is one of the best ecommerce platforms, but Shopify's native analytics are limited and the platform's standard integration with Google Analytics is incomplete and unreliable. In contrast, our Shopify connection uses a combination of client-side and server-side tracking to ensure 100% accurate data about your Shopify store in Google Analytics. Littledata automatically integrates with Shopify and Shopify Plus sites to capture every customer touchpoint, including sales, marketing and product performance data. Below is a table outlining the differences in tracking. What you can track with the Littledata Shopify app for Google Analytics [subscribe heading="Top Shopify app for Google Analytics" button_text="Learn more" button_link="https://www.littledata.io/shopify"] * Orders can be attributed back to a marketing channel or campaign, and linked to multiple previous visits by the customer using multi-channel attribution in Google Analytics The Littledata app makes all of this remarkably easy. It guides you through the correct Google Analytics setup for your Shopify store, then provides curated reports and analytics to help you make sense of your new stream of reliable data. In addition to 100% accurate sales tracking, Enhanced Ecommerce events and advanced marketing attribution, our Shopify app includes a ReCharge connection for subscription analytics. [tip]Now, with a revamped ReCharge connection — ReCharge v2 — you can track subscription lifecycle events with ease![/tip] After all, how can you grow a business unless you understand what share of your sales comes from repeat buying versus new customers? You don't have to be a Google Analytics expert to use Littledata's Shopify app. In fact, the app works best for product and marketing teams that are eager to learn about the big power of little data. We simplify the setup process and streamline the reporting process. It's that simple. Try it today for free in the reporting section of the Shopify App Store and see for yourself!

2019-11-26

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

Shopify analytics vs Google Analytics: which offers better ecommerce data?

If your Shopify store is starting to pick up traction, you've probably wondered if you're better off using Shopify's native analytics platform or Google Analytics, the household name for cross-industry reporting. Truth is, both Shopify analytics and Google Analytics offer unique benefits and features of their own. The difference, however, is that one of them is inherently incomplete, leaving Shopify merchants without valuable insights to make well-informed decisions for their store. So, which of them is incomplete? Let's dive in. Shopify tracking Shopify's analytics dashboard (available to both basic Shopify stores and Shopify Plus stores) provides a birds-eye view of the "big ticket" metrics, including average order value (AOV), conversion rate, sessions by location, sessions by traffic source, etc. With Shopify analytics, merchants can do the following: check and compare the value of recent sales by time period compare sales channels by performance track average order value identify store visitors by source (social media channel, location, etc.) monitor shopper trends over time Break in the system However, Shopify analytics offers an incomplete and inaccurate view for merchants, including key metrics like average order value and customer lifetime value (LTV). How do we know this? Take an example from earlier this year, when our team analyzeddata from 10 Shopify Plus customers to see whether the sales by traffic source report within Shopify analytics could be trusted. [subscribe] Turns out, the sales by traffic source report was 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% Clearly, the Direct channel traffic seems high — what channels was Shopify grouping under Direct? As you can see below, Shopify's data is all wrong. Here’s a comparison of Shopify’s attribution to Google Analytics last-click attribution of sales for one of these customers: Unfortunately for merchants primarily using Shopify analytics, the proof is in the pudding. Shopify users have frequently shown doubts as well — when we googled the keyword shopify analytics, the first Google-generated FAQ was is Shopify Analytics accurate? So is Google Analytics any more reliable for Shopify merchants? Google Analytics tracking With Google Analytics, merchants can do the following: Track number of sessions/purchases AND unique sessions/purchases Calculate accurate customer lifetime value (LTV) Dive deeper with acquisition reports — analyze campaign performance, referrals, etc. Segment by user type to evaluate your visitors (and potential ROI of retargeting them) Run conversion rate optimization (CRO) tests Analyze checkout funnel drop-offs Track which landing pages generate the most revenue Monitor your target keywords and optimize your store messaging accordingly Use custom segments to see the difference in revenue between search terms The list goes on. But beyond tracking site visitors, sessions, and other customer behavior on your store, Google Analytics provides a more complete picture of store performance within a more robust dashboard. Out with the old Without Enhanced Ecommerce reporting, GA still offers a somewhat limited view of shopper behavior. The EE plugin provides useful data about customer behavior before a purchase is made, giving you a better picture of the buying journey for your customers. Every stage is tracked — from research to consideration to purchase and even refunds. Enhanced Ecommerce does a little bit of everything: Customer behavior before, during, and after a purchase Detailed reports on: Average order value Add to carts Average order size Affiliate data records (number of transactions, affiliate revenue, etc.) Cart abandonment Track customer turnover — at what stage of the funnel are they walking away? Shopper engagement, including product views and purchases Coupon and discount reporting Even with EE, Google Analytics isn't a perfect platform. There is a problem with the reliability of transaction volumes within GA (luckily, this can be fixed with Littledata's Shopify app). But using Shopify’s reports alone to guide your marketing is ignoring the power that has led Google Analytics to be used by over 80% of large retailers. [note] See 4 reasons why you need Google Analytics for your Shopify store.[/note] GA's Enhanced Ecommerce plugin also offers a big step up from Shopify's basic reporting: Google Analytics Enhanced Ecommerce If you're a Shopify merchant using Google Analytics (either as your main reporting tool or in conjunction with Shopify analytics), make sure you enable Enhanced Ecommerce (EE) reporting on your GA dashboard, if you haven't already done so. [note] Learn more about EE reports and how to set them up here.[/note] EE offers Shopify merchants a gold mine of additional data. But while GA users have EE reporting functionalities by default, the biggest difference is that Shopify's tracker (in this case) does not accurately populate all the reports available with EE enabled. Bridging the data gap Littledata's solution comes packaged in a top-rated Shopify app, where you can get a complete picture of your Shopify store performance, all within the familiar Google Analytics dashboard. With the app, you won't have to worry about switching back and forth between reporting tools or crossing your fingers in hopes that the data you're seeing is accurate. The app offers 100% accurate data from every event (including page views, add to carts, purchases and refunds) that takes place in your Shopify store at every step of the customer journey. It also guarantees pinpointed marketing attribution, so you can track where your customers are coming from and exactly how they arrived at your store. Consider your tracking accurate and automated from here on out! [subscribe] A better question to ask While Shopify’s dashboards give you a simple, daily overview of sales and product data, if you're spending at least a few hundred dollars per month on online advertising or investing in SEO, you need a more robust way to measure success. So, Shopify analytics vs Google Analytics might be the common search query, but here's a better one: how do I ensure my Shopify tracking is accurate? For that, it's Littledata to the rescue. Shopify Plus users should stay tuned for Part 2: Do I need a Shopify Plus expert to help with Google Analytics?

by Nico
2019-11-05

Advanced Google Analytics connection for CartHook

We're excited to announce a completely updated connection for Shopify and Shopify Plus merchants using CartHook. The smart connection makes it easy to track your unique CartHook funnel in Google Analytics. CartHook is a powerful one-page checkout and upsells app for Shopify stores, and Littledata's mission is to fix your tracking, automatically. The updated CartHook connection - available for the first time directly from your CartHook admin - heeds that mission in helping merchants track every sale, refund and ecommerce checkout step: Track your unique checkout journey, including CartHook Checkout, landing pages and one-click upsells Get complete marketing attribution thanks to Littledata's smart script Segment sales by payment gateway Own the data in Google Analytics, and connect to your favorite reporting tools It's an advanced Google Analytics integration for Shopify and CartHook, easy to set up in less than 10 minutes. What's new CartHook was one of our first integrations at Littledata - before we even had 'connections' in the app! But it had to be done manually, and some merchants needed a custom setup. Now any Shopify store using CartHook can activate our automated Shopify and CartHook connections.  And what's even better? We're honored to be one of the first CartHook apps available directly from their admin. You can enable the connections from the CartHook dashboard or from the Littledata dashboard. Either way, the app will guide you through the setup steps to get the data flowing. Seriously, it's that easy! How it works Littledata's advanced Google Analytics connection for CartHook merchants automatically tracks every sale, refund and checkout step, so you can focus on growing your business.  The integration makes it easy to get accurate data on all CartHook purchases, including upsells, with clear attribution from all traffic sources in Google Analytics. In short, whatever you're doing with CartHook Checkout, we can help you track it. The connection takes advantage of Littledata's smart script for Shopify stores, making it easy to get extra benefits like multi-currency tracking and gtag/Google Tag Manager support, plus free reporting on your sales and marketing data.  [note]The CartHook connection works in tandem with our Shopify connection, so you need to activate that one first.[/note] Support from an analytics expert Have questions about using CartHook with Google Analytics? Check out our new help center for a range of articles about scaling fast with accurate data, from technical documentation about how the Littledata app works with CartHook and Google Analytics, to Google Tag Manager setup and event mapping guides. And if you're looking for analytics support, we've got your back. Littledata Enterprise is a popular choice among Shopify Plus merchants who want custom setup and reporting, or maybe just a Google Analytics-certified account manager to help them scale.

by Ari
2019-10-08

How Shopify Plus stores can set up multi-currency reporting in Google Analytics

An increasing number of ecommerce brands are using Shopify Plus to manage international stores and sell in multiple currencies. Since there are a few setups you may have, here are my recommendations in each case to get the most versatile reporting in Google Analytics (GA).  For a single store accepting multi-currency Littledata’s enhanced Shopify tracking already handles multi-currencies at all stages of the shopping journey.  We recommend you have just a single web property and single view in Google Analytics. Our audit checks will make sure the currency you have set up for this view matches your Shopify store currency. For multiple stores, with different default currencies (GA standard) I recommend you set up a single web property, but with different Google Analytics views for each country store. You can create one ‘All countries’ view in the same currency as your company’s default reporting, and then each country store would need filters set up to include traffic only from that country. Here's how to set up the filters: Go to the Admin section in Google Analytics, and click Filters under the View settings Then click to ADD Filter Then set up a filter to include traffic only from this store’s hostname Then Save the filter This could be tricky if you use a third-party checkout, where the hostname will be shared across stores (see below). Each country view in Google Analytics would have the same currency and timezone set as the Shopify store, so you can compare like-for-like orders. In Littledata, you would create different accounts for each country store and be able to audit and benchmark your stores' performances separately. Multiple stores, with different default currencies (GA 360)  With GA 360, you have the added flexibility of being able to setup a roll-up property, combining ecommerce events from multiple properties. So you have two options:  Go with the same solution as for GA Standard. The advantage here is that with a single web property, you can easily track visitors as they move between your country stores (i.e. if users are directed to a country after seeing a marketing campaign, you can still attribute the marketing campaign as they move to a different store). Set up a separate web property for each country store, and roll-up into a group property. The advantage here: your data is clean, but you can’t track cross-country visitors. Option 2 is going to work better if you leverage third party checkouts like ReCharge Payments or Bold Cashier, where it may be hard to filter out the traffic from only one country. If you're not sure what to think of this, don't fret — Littledata's analytics team can guide you in multi-site setup with an Enterprise plan, so please reach out if you're feeling confused. [subscribe] Multicurrency support for Shopify If your store presents prices in multiple currencies using Shopify Payment’s multi-currency feature, then Littledata’s app is 100% compatible with multi-currency. Here’s how it works for different parts of the data processing. We use Shopify’s definition of ‘presentment currency’ and ‘shop currency’. Storefront data layer All prices for products in the LittledataLayer and dataLayer variables will be in shop currency, regardless of the presentment currency. This includes the add-to-cart events handled by Littledata’s servers. Checkout steps Prices are sent in the presented currency and converted by Google Analytics (or Segment) to the target currency at current exchange rates. Orders & Refunds All orders and refunded items are sent to Google Analytics in the shop currency. Multiple country stores sending to one web property If you have multiple country stores, with different shop currencies, all sending data to a single web property in Google Analytics, this is also handled by our tracking script.

2019-09-24

Quick tips for subscription stores using Google Analytics custom dimensions

One of the challenges subscription businesses face is differentiating between order types.  The problem For Shopify merchants, offering single purchase options complicates things even more — with single purchase options, order data will show in two places (Shopify and ReCharge). This leads to a major disconnect between user behaviour and orders, unable to leverage the full potential of Google Analytics.  At this point, you probably have a multitude of “known unknowns”, such as: Which traffic sources drive more first time subscription orders? What's my conversion rate on one time purchases? What's my average customer lifetime value (CLV or LTV)? Do my one time purchasers end up converting to subscribers? What's my churn rate month over month? [tip]Get accurate tracking for repeat orders with the ultimate Shopify ReCharge guide.[/tip] The solution Bridging the gap with Littledata Littledata helps bridge different platforms by linking orders betweenShopify, ReCharge and Google Analytics.  [subscribe] Differentiating between order types With Littledata’s improved tracker, merchants can differentiate between order types. For this, we use the Affiliation dimension.  In the Google Analytics report, it will look something like this:  Right away, this information answers a few questions: What is the distribution between my order types? Are my recurring subscription orders growing month over month? Is the average order value (AOV) of subscribers higher than that of one time purchasers?  Both of these can be viewed in this custom report. What traffic sources drive the most sales?  One of the questions our team is asked most often is what sources of traffic drive the most subscription orders?  Short answer: the Affiliation dimension can be used as a secondary dimension in the source/medium reports, or use this custom report.  By using filters to single out an order type, you can easily determine what traffic sources drive the most first time subscription orders. Segment more Segmentation opens up new ways to look at the data as well. Creating two segments for one time purchases and first subscription purchases, you can see how the two types of purchases differ.  Look for behavioural differences like:  Do One Time purchasers AOV higher or lower compared to First Subscription orders? Are users testing the product first and then committing to a subscription?  Littledata custom dimensions Google Analytics custom dimensions are an excellent way to expand your data collection and reporting power. With our Shopify app, Littledata adds these custom dimensions: Littledata - Shopify Customer ID Littledata - Last Transaction Date Littledata - Purchase Count Littledata - Lifetime Revenue Littledata - Payment Gateway With the help of these custom dimensions, we can answer the following questions:  What's my median customer lifetime value (CLV)? How many purchases do customers make in their lifetime? What's my churn rate month over month? Since these are custom dimensions, they cannot be aggregated on Google Analytics, meaning the data will need to be displayed using a different method. For this, we’ll use Google Sheets with the Google Analytics add-on to query the data and pivot tables.  Step 1 - Query all the data you need Metrics Avg. Order Value Revenue Dimensions Littledata - Shopify Customer ID  Littledata - Lifetime Revenue Littledata - Purchase Count Affiliation - to differentiate between the order types.  It should look something like this:  In this case, the custom dimensions are at index 4, 6 and 8. This may differ depending on your setup.  Step 2 - Run the report After you run the report, this will create another sheet in your document. It will look something like this:  Step 3 - Create a pivot table  In the rows section, add the Affiliation dimension to differentiate between the order types.  Shopify will mean a one time purchase (normal purchase). The other two order types are the first subscription order and recurring order.  In the values area, add:  The user IDs summarised by countunique The customer lifetime value summarised by median so that we have the median LTV. We use median over average so that this number is not influenced too much by the outliers.  Purchase count summarised by median.  Average order value  The end result should look something like this:  Step 4 - Interpret the data In this report, we can instantly draw some conclusions:  Most customers make single purchases rather than subscribing  Subscription first order median purchase is 2, so this means users have purchased in the past before committing to a subscription Subscribers purchase 8 times (median value), with a median CLV is around $500.  How to take this further Since we know most customers order at least once before committing to a subscription, we can calculate the average number of days between a single purchase and a first subscription purchase.  When you’re armed with that type of information, you can adjust your email marketing flows accordingly and adjust your remarketing campaigns to shorten or lengthen the number of days your ads show to leads.  With the help of the Customer IDs, we can also calculate the month over month churn rate (we’ll get to that in a follow-up post). It's your turn now How do you use these additional events and custom dimensions in your segmentation?  What was your biggest insight using these events and custom dimensions?  How did it influence your marketing campaigns? Share your experience (and current approach with GA) via the live chat in the bottom corner. I'm curious about the different ways you make use of these additional data points! In the meantime, our team is at the ChargeXSummit in Santa Monica sharing all about our ReCharge connection for subscription-based stores. [note]Now, with a revamped ReCharge connection — ReCharge v2 — you can track subscription lifecycle events with ease![/note]

2019-09-19

Does Littledata work with my ecommerce reporting tool?

We often get asked if Littledata works with certain reporting tools that are popular among merchants. Here's the short answer: if your tool can pull data from Google Analytics or Segment, then our smart connections will help you get accurate data to use with those reporting or data insight tools. Here’s exactly how we work with each platform. The Establishment These are the main ecommerce reporting tools. If you're using one of these tools, you're in luck. Littledata integrates with them automatically. These products include: Google Analytics Google Data Studio Tableau Segment Power BI Read on to see how Littledata works with these data insights tools to improve the accuracy of your data and the usefulness of your reporting. Google Analytics The world’s most popular analytics tool gets even better when paired with Littledata’s smart connections and full audit to enhance the ecommerce event data captured from your store. GA is the core tool to which Littledata connects, allowing you to connect to other dashboards below, such as Tableau and Data Studio. [subscribe] Segment Segment’s data pipeline is a trusted way to get analytics from one platform into dozens of others without complex engineering. Our source for Shopify and Shopify Plus helps you automatically send ecommerce events into any of Segment’s hundreds of destinations. Once the Segment connection is set up, you never lift a finger. Google Data Studio Data Studio is our dashboard tool of choice for more custom-designed reports.  Because Data Studio integrates seamlessly with Google Analytics, Littledata’s connections can all be exported from Google Analytics into Data Studio, making our Shopify app the top Data Studio connector for Shopify stores. While it can be slow to generate reports at scale, Data Studio's unlimited free reporting makes it hard to beat for ad-hoc analysis. And they often add new report templates and visualizations. With Littledata's Data Studio connection, you get: Accurate sales data, including refunds and repeat purchases Custom dimensions for LTV reporting and cohort analysis Better marketing attribution, since our app stitches sessions together automatically [note]Are you looking for accurate Shopify sales data in Google Analytics and Google Analytics? Get the free ebook on Shopify tracking, including tips for tracking refunds and repeat purchases.[/note] Tableau Tableau, now part of the Salesforce family, was one of the first tools to provide a smart, easy setup dashboard. Their connection with Google Analytics is well established, and as with Data Studio you can access the Littledata events from there. Power BI Microsoft’s popular reporting tool can also import data from Google Analytics, so anything Littledata pushes to GA is available in Power BI. Power BI is especially useful if you want to visually explore your ecommerce data, as the platform offers interactive visualizations and a range of business intelligence (BI) insights. They also allow on-premises report deployment (behind a firewall), which is great for larger brands with large in-house teams. Newer solutions In addition to the 'establishment' above, Littledata seamlessly integrates with a number of newer reporting tools that offer Google Analytics insights and visualizations. These apps and reporting tools include: Glew Glow Yaguara These tools are especially popular with Shopify and Shopify Plus stores. Glew Glew provides some cleverly-curated ecommerce reports, but any of the underlying data on marketing attribution or customer behaviour pulled from Google Analytics will require Littledata’s improved tracking for full accuracy. Here’s a more detailed guide of the differences between Glew and Littledata. Grow Grow is a newer dashboard tool with hundreds of reporting sources, of which Google Analytics is their ‘most popular’. While some of the detail from Littledata’s connections may be lost in ‘basic reporting’ from GA, their multi-channel marketing reports are useful. Yaguara Yagura provides a series of templates to gain insights into your ecommerce business. One of their key integrations is with Google Analytics, and so the extra insights from Littledata’s tracking can be pulled into a Yaguara dashboard. Tools we don't work with directly The following tools don't connect with Littledata, and we aren't planning an integration. Conversific Conversific is an analytics tool for Shopify, with similar reporting to Littledata. While Conversific doesn’t offer the same smart connections as Littledata, it’s unlikely you’d need to use the two together. Metrilo Metrilo offers to optimize marketing channels for ecommerce. While their guide says Metrilo is a good alternative to Google Analytics, it won’t replace the reporting that Littledata provides. Zaius Zaius is an ecommerce CRM, allowing you to personalise and automate marketing based on customer interactions. As such, it needs its own event data capture, and can’t integrate with Littledata reporting. [note]Have you built custom reports using Littledata tracking? We'd love to hear about it. Give us a shout and let us know.[/note]

2019-09-12

3 massive hurdles for merchants who manage subscription orders

For merchants who run subscription-based businesses, accuracy is crucial for tracking recurring orders. The problem: popular platforms like Shopify provide merchants with native analytics that are broken. In other words, these platforms don't offer a complete picture (or an accurate one) of data that subscription-based stores depend on. [tip]Get accurate tracking for repeat orders with the ultimate Shopify ReCharge guide.[/tip] There are many potential blockers for these store owners, but we narrowed it down to three: 1) Customisable orders & levels of membership Many successful subscription-based stores allow shoppers to customise their monthly orders. While this is an effective draw for consumers, it causes all kinds of headaches for the teams that manage the orders. The ability for customers to customise monthly orders adds layers of complexity for teams who manage product inventory, fulfillment and logistics in the back end. Perhaps the best example is from the hugely popular Dollar Shave Club. Known for their humor-driven marketing approach, the brand constantly encourages its subscribers add more and more products to their monthly shipments, which go out at different times each month. Due to the brand's meteoric growth over the past five years, this creates headaches — imagine fulfilling dynamic orders each month (different cart sizes, products and membership levels) for hundreds of thousands of customers across America. The 'curated box package' is another common subscription model. StitchFix, a curated clothing company for men and women, surprises its customers each month with a package containing 'personalised' new outfits. While the surprise factor might not be a draw for some, the brand's main appeal is the diversity of its products. Every month, StitchFix's variety is what appeals to its majority millennial market. Whether your store offers dynamic monthly ordering (where customers can change the contents of their cart) or follows a more traditional subscription model, it's crucial to have data you can trust. This means finding an ecommerce solution built to handle both customer changes and increased payload as your store scales. [subscribe heading="Automatically track your subscription orders" background_color="green" button_text="find out how" background_link="https://www.littledata.io/connections/recharge"] Affiliate marketing & partnerships It's common for subscription-based stores to partner with affiliate marketers to generate an additional source of revenue and tap into new customer groups. However, with more customers comes more demand, and the importance of accurate data only increases — this includes tracking sales made through affiliate partners, commission owed on each sale, etc. 2) Customer loyalty & reward programs When done right, effective customer loyalty programs create more loyal customers, boost customer retention and increase sales. These programs aren't used by every subscription-based brand, but for the brands that use them, they really do work, according to LoyaltyLion. However, as high shopper expectations continue to soar, the landscape for rewards programs is getting more competitive. Shoppers know that if they don't absolutely love one aspect of a brand's rewards program, they can easily run to a competitor that offers what they're looking for — whether it be a cheaper price tag, better discounts or more rewards available. Mark Hook, Head of PR and Communications for retail management software Brightpearl, had this to say: Over two-fifths of millennial shoppers (45%) admit to being less loyal to brands when compared to a year ago, and are quicker to abandon buying from companies that don’t meet expectations A great example of a rewards program within a subscription is Nike+. By putting the mobile shopping experience at the top of its priority list, Nike has developed multiple apps that work hand-in-hand with the Nike+ loyalty program by allowing its members to 'take the brand wherever you go.' By offering easy member access to the program, Nike gets higher engagement from community members and increased brand loyalty from repeat buyers. However, for merchants, a successful customer loyalty program hinges on back end analytics and whether or not it's set up properly. For merchants relying on Google Analytics for tracking, do you have custom dimensions set up? Are there parameters to track recurring orders, free trial offers, promo codes or even brand events? 3) Payment security & order changes Ecommerce businesses not operating on a subscription model typically receive credit card information every time a transaction is made. On the other hand, subscription-based businesses store data for recurring purchases, which simplifies the user experience and helps encourage users to continue paying each month. With potentially millions of credit card numbers stored in a database, brands are constantly at risk for large-scale fraud. This forces brands to invest in airtight security measures to protect your own revenue and the sensitive data of your customers. Merchants need to stay prepared for orders with expired credit card info, subscription cancellations and changes to recurring orders — all of which make it tougher to accurately track individual events and transactions. Running a subscription-based store with data you can trust Even with these hurdles, there's a shiny silver lining for merchants who rely on subscriptions. Littledata's plug-and-play ReCharge integration connects with Shopify and Google Analytics to do the following: Automatically track first-time payments and recurring transactions Provide accurate marketing attribution for subscription revenue Segment performance by payment source, subscription plan type and product category Benchmark your site and offer access to professional-level subscription analytics tools With Littledata's Shopify ReCharge integration, there's a better way forward for merchants who manage subscription orders. BullyMax, a popular nutrition and muscle-building supplement for dogs, and Dry Farm Wines, a health-focused natural wine club, are two top subscription brands that have seen great success with Littledata's Shopify ReCharge connection. Read more about our topintegration for subscription analytics.   [tip]Now, with a revamped ReCharge connection — ReCharge v2 — you can track subscription lifecycle events with ease![/tip] In a follow-up post, we discuss a fool-proof solution for Shopify merchants who manage subscription orders. Check it out!

by Nico
2019-08-02
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