Category : marketing attribution
Using Postscript SMS to fuel your conversions
With a staggering 98% open rate, SMS marketing should be part of every DTC brand’s marketing strategy. The best part is that SMS marketing works well for both acquisition and retention. With Littledata’s new Postscript integration, you can better track which SMS campaigns are driving sales and exactly when and where customers are converting. Narrowing down campaigns to the channel level in Google Analytics 4 gives your business a single source of truth for attribution. 1 of every 5 orders is missed by merchants who rely solely on Shopify’s tracking, and this is getting even worse with recent privacy changes. With proper tracking of your SMS campaigns you can up your analysis of key ecommerce metrics gathered by Littledata like AOV, LTV, and more. Helping your team save time, money, and resources by setting up tracking or doing analysis manually. Littledata even lets you see which SMS campaigns perform best for different types of orders (e.g. subscription recurring orders, first time subscription orders, one off purchases, upsells). Merchants continue to dive into channel data in order to optimize their campaigns and understand customer behavior. Knowing how channels are performing and contributing to key ecommerce metrics enables merchants have a better understanding and build custom reports in Google Analytics 4's newly launched exploration tool. Allowing merchants to have better insight and control over their data. A popular example is Funnel exploration which allows you to see direct or indirect steps around efforts like SMS and how they play a role in the customer journey. Benefits of using Littledata with SMS include: Single source of truth in Google Analytics. See which SMS campaigns are driving sales and exactly when and where customers are converting. Better marketing attribution. Littledata’s app magically stitches sessions together so you can understand performance across paid and organic channels. And build better audiences in Facebook Ads, Google Ads and more. Audience building. Littledata captures complete data about browsing behavior, checkout steps and purchasing behavior (orders, refunds, repeat purchases) for more accurate retargeting campaigns and audience building. Complete subscription tracking. Many subscription ecommerce merchants use Postscript to power their SMS/text marketing, and Littledata integrates with leading subscription apps like Recharge, Smartrr and Ordergroove to track recurring orders directly in Google Analytics 4 and tie them back to customer touch points like email, SMS and Facebook Ads. Littledata’s no code solution offers easy setup without the need for developers. Simply add the correct UTM parameters when setting up your Postscript campaigns and our app will start stitching sessions together behind the scenes. See for yourself with a free 30-day trial. [note] Learn more about our Postscript connection here [/note] Curious about how to succeed in a world without third-party cookies? Learn more about why top DTC brands are moving to server-side tracking.
How to track ecommerce conversions in GA4 (Google Analytics 4)
Have you mapped out a data plan for 2023 yet? If you’re selling on a major DTC platform like Shopify or BigCommerce, GA4 is probably on your mind. With the sunsetting of Universal Analytics (GA3 or the “old version” of Google Analytics) on the horizon, it’s time to get going with event-based tracking. Many brands have been procrastinating about setting up GA4 – or, worse, only setting it up halfway so that browsing behavior is tracked but revenue and conversions are missing. But can you blame them? Shopify isn’t planning to release native GA4 integration until March 2023 at the earliest (and nobody’s expecting it to work well for serious DTC brands) BigCommerce released a beta version of their GA4 integration in November, but it’s extremely minimal, tracking only begin_checkout and purchase events Manual setup is costly and confusing (and has to be maintained every time you change your site or checkout flow) GA4 revenue tracking should be your top priority, but there’s a lot of confusion around GA4, made worse by Shopify apps that claim to offer GA4 integration but only offer client-side tracking. It shouldn’t be so complicated. At Littledata we’ve already fixed GA4 tracking for hundreds of top DTC brands. In this post I’ll show you how to check if you’ve set up GA4 correctly to capture orders and revenue, and how to start tracking ecommerce conversions today in the most secure and reliable way possible. Follow this guide to GA4 and you’ll be on your way to ecommerce data tracking in no time. We’ll look at how to get from this: To this: How to check if you’re tracking GA4 revenue and conversions After creating a new GA4 property and following the setup assistant to create a new data stream, you might have noticed that you’re instructed to copy and paste the Google tag (gtag.js) script on every page of your ecommerce site. Once you’ve added the Google tag to your site and linked your GA4 property, everything will just start tracking automatically, right? Wrong. With the basic script all you get are engagement events such as page_view, session_start, view_search_result, and click. Obviously these “automatic events” are super important, but they don’t tell you what happens post-click. Here’s how to check if your GA4 ecommerce setup is working or not. 1. Check your Acquisition reporting in GA4 There are two places to look to see if you’re capturing ecommerce conversions. First, the Acquisition reports. You’ll see user and traffic engagement details grouped by channel, but no conversion or revenue data exists. You’re seeing which organic or paid channels are bringing visitors to your store, but you can’t tell if you’re generating any revenue from these visitors. GA4 revenue reporting not showing is one of the most asked questions by merchants and performance marketers. 2. Check your Engagement and Monetization reporting in GA4Taking a step further, check your Engagement and Monetization reports. Do you see GA4 reporting data about cart updates, interactions with the checkout flow, or any purchase or revenue data? If revenue is missing in GA4’s monetization overview, you need to start tracking ecommerce activity ASAP. Otherwise, you’ll end up with a lot of data points that lead nowhere and you will not have an accurate understanding of your ecommerce store’s performance. [tip] Use our complementary instant order checker for GA4 to check your property [/tip] How to track ecommerce conversions and revenue in GA4 After landing on your store, online shoppers interact with collections and products before adding items to their carts and going through the checkout process. These web interactions must be captured as events and linked with customers and marketing data in GA4 to get a complete picture of your business. We have looked at what data can be missing from your GA4 events and which enhanced ecommerce events you should track. But how can you get all these ecommerce events in GA4? Google Tag Manager (GTM) has always been the most common tracking method for Universal Analytics, and the setup process can be carried over to GA4. However, for a lean team, the setup process can be quite time-consuming and complex, having to create a Data Layer In Shopify, and then for each event, you must create: Firing Triggers in GTM Data Layer Variables in GTM Ecommerce Tags in GTM Needless to say, there are quite a few maintenance pitfalls if you're going down this route. Setup is just the beginning. To make matters worse, Shopify is removing GTM from the checkout for Shopify Plus stores (standard Shopify stores never had access). So even if you take the time to add all your own events to tracking visitors before they make a purchase, you’ll no longer be able to track checkout steps (add-to-cart, etc) with GTM. If you want to save time and money while still having confidence in the accuracy of your GA4 data, Littledata is the perfect solution for you. Our proven app is used by over 1500+ brands and can help you track your ecommerce conversions with ease, giving you the reliable data you need to make informed decisions about your business. Littledata’s data layer uses a unique combination of client-side and server-side tracking to ensure accurate, complete ecommerce data in GA4 and any connected data warehouse or reporting destination. Littledata captures complete ecommerce data automatically in GA4 for Shopify and BigCommerce stores. We can break down those events into seven general categories: Marketing channels Browsing behavior Checkout steps Conversions Revenue Recurring orders Upsells Of course, each reporting category has useful data, but brands that really want to scale link it all together to look at revenue and LTV by channel, splitting out first-time purchases from repeat purchases or recurring orders (subscription analytics). As I mentioned earlier, Acquisition reports are some of the most valuable sets of data GA4 offers. They show which of your team’s marketing efforts bring the most results, from traffic through engagement and conversions. The difference between having accurate or questionable ROI data in these reports rests on how the purchase event is tracked. It is useful to have the engagement metrics grouped by channel, but the difference between having accurate or questionable ROI data in these reports rests on how the purchase event is tracked. Get started with Littledata today so you will have the data you need to scale faster the smart way. We recommend tracking in UA and GA4 “in parallel” as soon as possible.
What's the real ROI on your Facebook Ads? [webinar]
Is your FB/Insta ad spend leading to high LTV customers? What happens after a shopper clicks on a link? One thing is clear: you've got to get the tracking right before you can start making data-driven decisions. Join Littledata and Beacon on Thursday, March 4th for a free webinar where we will explore the details of marketing attribution and Facebook campaign ROI. Pretty much all ecommerce brands today are using Facebook and Instagram ads as part of their digital marketing mix. When it comes to Facebook Ads, marketers are drawn to messaging about a strong return on investment. But are you measuring that return correctly? In this free webinar, you'll learn: Common issues with marketing attribution How to track post-click shopping behavior (what happens after someone clicks an ad) The importance of using external platforms for an unbiased view of marketing channels How to calculate complete ROI for your Facebook and Instagram Ad spend, including repeat purchases, refunds, and customer lifetime value (LTV) How benchmarking your site against similar brands can help make sense of the data Signup for the free webinar >>> About Littledata Littledata automatically fixes tracking for Shopify stores, offering complete marketing attribution, accurate sales data, and custom dimensions for lifetime value reporting. Check out our Shopify app for Google Analytics Learn more about our Shopify source for Segment Try Littledata's Facebook Ads connection free for 30 days Signup for the free webinar >>> About Beacon Beacon is the digital marketing campaign intelligence platform that is easy-to-use and presents real-time information based on data you can trust. It empowers marketers to accurately measure campaign results, take back control of their digital spend, and get a better ROI on their campaigns. Signup for the free webinar >>>
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]
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. [tip] Littledata now supports conversion tracking in Google Analytics 4 (GA4): Learn More [/tip] I've written a patch for our tracking script so that we set utm_medium as referral if only the source is specified, but you can also edit the default channel grouping in GA so that shop_app is grouped as a referral. Thirdly, you want to differentiate orders going through shop.app from the normal Shopify checkout. Littledata's Shopify app does this by translating the order tag shop_app into the transaction affiliation in Google Analytics, so the affiliation is Shopify, Shop App. Conclusion So if you're a Littledata customer: our app has got you covered. And if not there's a few changes you'll need to make in Google Analytics settings to make sure shop.app traffic is treated correctly.
6 FAQs you may have asked during a Littledata demo
Like many SaaS companies (and Shopify app developers), we get a LOT of merchants writing in with questions. Big, small, new, old, Shopify Plus, Shopify basic, headless Shopify, platform migrations from Magento...you name it. But some questions stand out for every Shopify store. For those of you who've gone through a demo with our support or sales team, it is highly likely that you asked one of the following questions about Littledata, Shopify and Google Analytics (GA): When's the right time to install Littledata? Do you fix marketing attribution? Should we use Segment? Why doesn't my Shopify data match what I see in GA? How do you capture complete revenue data? What's included in enterprise plans? And there's a reason why — these are the questions we get the most from merchants like you. In this post, we'll break down the answers as clearly and directly as possible. Plus, we'll give you the resources you need for more detailed answers. (Rather talk directly to a human? Book a demo). [subscribe] 1) When's the right time to install Littledata? In short, it really depends on your internal process. What do we mean by process? Let's put like this: why do you need accurate data? What will you do with it? If you're still working on your checkout architecture, it's probably not the right time. If you generally don't trust data to help make decisions about CRO, marketing plans, online product merchandising, retargeting, etc., then it's definitely not the right time (nor a good fit in general). But if you just don't trust your Shopify data in Google Analytics and want to trust it, then it definitely IS time. And if you're still shopping around for Shopify Plus development agencies, it's probably not the right time (though we can help recommend one). But in most cases, the time is NOW! Every ecommerce site and DTC brand has their own internal process for moving toward data-driven decision making, and whether you're ju or already en route to scale insanely fast, we're here to help. But don't take it from us. Here are some of the cases where clients have said they were really glad they started a free trial of Littledata then and didn't wait to fix their tracking: Migrating from another ecommerce platform (most often Magento) to Shopify Ramping up paid spend and want to make sure the data is accurate (most often Facebook Ads and Instagram Ads) Recently redesigned the site or checkout -- or added products by subscription -- and want to ensure complete sales data and better segmentation in Google Analytics Recently launched multi-currency (multiple "stores" in Shopify-speak) and looking for a way to segment marketing campaigns and track sales in Google Analytics And one of my favorites: "We were actually already loving Littledata but upgraded for analytics training and extra support!" [tip]Testing your new setup in a dev store or production site before moving to a live site? Let us know and we'll set up a free test account[/tip] 2) Do you fix marketing attribution? Yes. Littledata is uniquely suited to stores that really care about getting their data right, and that's especially true if you want accurate marketing attribution. Our app fixes attribution for Shopify stores automatically with a combination of server-side and client-side tracking. We stitch sessions together to make sure nothing's lost, so you can rely on Google Analytics or Segment (our current data destinations) as the single source of truth for both pre-click and post-click data, as well as more complex stuff like segmented remarketing, comparative attribution models and LTV calculations for subscription ecommerce. Our script uses gtag and GTM data layer, and can easily supplement and improve your GTM setup (though many clients find that they no longer need GTM). So if you're asking questions like "Why is an absurd amount of my traffic showing as Direct?" or "Is it possible to see the LTV by channel for our Shopify store?", we've got you covered. As our CEO puts it, "What's the real ROI on your Facebook Ads?" [tip]Get accurate campaign tracking and know your true ROAS with our connections for Facebook Ads and Google Ads[/tip] As an added bonus, we have ecommerce benchmarks in the app. So once you have accurate data, you can see if your Facebook referrals are higher or lower than average, as well as if there are technical factors such as page load speed affecting conversions. 3) Should we use Segment? If you're considering different data pipeline and customer data solution, we highly recommend Segment. It's a powerful, clean way to track customer data alongside anonymous browsing behavior, ad performance and more. In fact, we love Segment so much that we built the only recommended Segment connection for Shopify stores. Here's what one customer has to say about it: "This app seamlessly integrated Shopify with Segment. All of our data is flowing seamlessly from Shopify into all of our destinations via Segment." If you're comparing Segment against other CDPs like mParticle and Stitch, we're happy to chat about the pros and cons and give you an honest opinion about what's best for your ecommerce business. One thing our larger Segment users find particularly useful about Segment is that once a source is set up, it tends to run really smoothly. So Segment becomes a single source of truth in a way that few other data platforms can offer, with literally hundreds of destinations for using, acting on and modeling that data. [note]Using a Headless Shopify setup? Littledata fixes tracking for headless Shopify in Segment or Google Analytics. See the headless tracking demo for more details.[/note] 4) Why doesn't my Shopify data match what I see in Google Analytics? [tip]There's a free resource for that! Learn how to fix Shopify <> GA data differences in our free ebook[/tip] The truth is that Google Analytics (GA) and Shopify need a little help to play nice. Most marketers use GA to track performance, but having a good data setup — even for bare essentials like transactions and revenue — is harder than it looks. In some cases, you may need the help of a Google Analytics consultant or GA expert. For other stores (especially teams well-versed in GA tracking) don't need the help of an expert. There are many reasons for differences in tracking results, but let’s take a look at the top 6 reasons. a) Orders are never recorded in Google Analytics Usually, this happens because your customer never sees the order confirmation page. More commonly, this is caused by payment gateways not sending users back to the order "thank you" page. b) The Analytics / Google Tag Manager integration contains errors Shopify's integration with Google Analytics 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 designed to work for most standard stores, there are those who build a more personalised theme. In this case, they would require a custom integration with Google Analytics. But with Littledata's Shopify app, here's what you can track. c) 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 from executing. d) 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 grow 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 information for about 20 products. When this limit is reached, GA will not send the payload to its servers, resulting in lost purchase data. e) 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 GA'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. 5) How do you capture complete revenue data? It's magic. Or at least it might feel that way. Once you put our tracking script in your theme and install the relevant connections, Littledata uses a savvy combination of client-side and server-side tracking to capture every shopper interaction with your online store. Because our server-side tracking sends revenue data with purchase and refund events directly to your chosen data destination (Google Analytics or Segment), it's much more reliable than waiting for an event to fire when a confirmation page loads completely, or trying to hack together a way to capture revenue data with GTM from third-party checkouts. Our app often fixes revenue variance of 20-30%, even for large retailers! Behind the scenes the setup looks something like this: Not only does Littledata capture complete sales data, including refunds, but our Shopify integration also sets up custom dimensions in your Google Analytics account for smarter segmentation and long-term tracking. After all, smart ecommerce businesses know that revenue isn't just about the first purchase numbers -- you need to track what types of customers purchase more over time. For example, do customers who come from a particular marketing channel tend to make a number of smaller purchases that actually add up to higher lifetime revenue than those one-off big spenders? So we add custom dimensions including: Lifetime value (LTV) Last order date Shopify customer ID If you're using ReCharge for subscriptions, note that we also track subscription lifecycle events such as payment method updates and subscription updates, so you can do deep dives into not just revenue changes but the reasons for those changes. [tip]Do you really know which marketing channels bring you profitable customers? Learn from our CEO how to accurately calculate lifetime value[/tip] 6) What's included in Enterprise plans? At Littledata, we've been lucky to have a chance to scale along with Shopify. Larger brands have been increasingly drawn to the platform's ease of use, and Shopify Plus merchants now include Leesa, Bulletproof Coffee, LeSportsac and Gymshark. But even with Shopify's growth, there's a consistent problem: questionable analytics. One thing I really love about working at Littledata is that we’ve managed to keep the core tracking tools extremely affordable, while also offering a wider range of enterprise plans at approximately 1/10 the cost of hiring outside consultants or someone in-house. We have a range of options for enterprise plans to fit your needs and budget, grouped around two enterprise "tiers": enterprise basic and enterprise plus. Basic enterprise Basic enterprise plans can be paid monthly or annually. They include: Dedicated account manager Shopify Plus support Unlimited connections Unlimited country stores Every account manager at Littledata is an analytics expert. They can help to ensure accurate setup of your Segment or Google Analytics tracking, and recommend proven implementation and optimization strategies for Shopify Plus. After all, once you know that you can trust your data, focusing on the right metrics can make a world of difference. Enterprise Plus Enterprise Plus plans include everything in basic Enterprise plans, such as support from an analytics expert, plus custom setup and training to fit your needs. Options include: Custom setup Analytics training Manual data audits Segment support, including solutions engineering Google Tag Manager support Analytics 360 Suite support And a whole lot more. See what’s included in our enterprise analytics plans. In short, we’re here to make sure that you can trust your data — and use that data for actionable results. If you’d like to get started with the app, you can try it free for 30 days. We're also happy to walk you through the app — just book a demo with us online!
How to fix marketing attribution for iOS 14
The latest version of Safari, and all browsers running on iOS for iPhones or iPads, limit the ability for Google Analytics (and any other marketing tags) to track users across domains, and between visits more than a day apart. Here’s how to get this fixed for your site. This article was updated January 2021 to include the changes for iOS 14 How does this affect my analytics? Safari's Intelligent Tracking Prevention (ITP) dramatically changes how you can attribute marketing on one of the web's most popular browsers, and ITP 2.3 makes this even more difficult. How will the changes affect your analytics? Currently your marketing attribution in Google Analytics (GA) relies on tracking users across different visits on the same browser with a first-party user cookie - set on your domain by the GA tracking code. GA assigns every visitor an anonymous ‘client ID’ so that the user browsing your website on Saturday can be linked to the same browser that comes back on Monday to purchase. In theory this user-tracking cookie can last up to 2 years from the date of the first visit (in practice, many users clear their cookies more frequently than that), but anything more than one month is good enough for most marketing attribution. ITP breaks that user tracking in major ways: Any cookie set by the browser, will be deleted after 7 days (ITP 2.1)Any cookie set by the browser, after the user has come from a cross-domain link, will be deleted after one day (ITP 2.2)Any local storage set when the user comes from a cross domain link is wiped after 7 days of inactivity (ITP 2.3)With Safari 14, any script known to send events about the user is blocked from accessing cookies or any way of identifying the userFrom iOS 14 onwards all browsers will implement these restrictions by default, unless the user opts in to 'allow cross-website tracking'. This will disrupt your marketing attribution. Let’s take two examples. Visitor A comes from an affiliate on Saturday, and then comes back the next Saturday to purchase: Before ITP: sale is attributed to AffiliateAfter ITP: sale is attributed to ‘Direct’Why: 2nd visit is more than one day after the 1st Visitor B comes from a Facebook Ad to your latest blog post on myblog.com, and goes on to purchase: Before ITP: sale is attribute to FacebookAfter ITP: sale is attributed to ‘Direct’Why: the visit to the blog is not linked to the visit on another domain The overall effect will be an apparent increase in users and sessions from Safari or iPhones, as the same number of user journeys are broken in down into more, shorter journeys. How big is the problem? This is a big problem! Depending on your traffic sources it is likely to affect half of all your visits. Apple released iOS 14 and Safari 14 on 16th September 2021, and at the time of writing around 20% of all web visits came from iOS 14, and another 20% of visits from Safari 12 or higher, on a sample of larger sites. The volume for your site may vary; you can apply this Google Analytics segment to see exactly how many iOS users you have. The affected traffic will be greater if you have high mobile use or more usage in the US (where iPhones are more popular). Why is Apple making these changes? Apple has made a strong point of user privacy over the last few years. Their billboard ad at the CES conference in Las Vegas earlier this year makes that point clearly! Although Google Chrome has overtaken Safari, Internet Explorer and Firefox in popularity on the desktop, Safari maintains a very dominant position in mobile browsing due to the ubiquitous iPhone. Apple develops Safari to provide a secure web interface for their users, and with Intelligent Tracking Prevention (ITP) they intended to reduce creepy retargeting ads following you around the web. Genuine web analytics has just been caught in the cross-fire. Unfortunately this is likely not to be the last attack on web analytics, and a permanent solution may not be around for some time. Our belief is that users expect companies to track them across their own branded websites and so the workarounds below are ethical and not violating the user privacy that Apple is trying to protect. How to fix this There is only one fix I would recommend. I’m grateful to Simo Ahava for his research on all the possible solutions. If you’re lucky enough to use Littledata's Shopify app then contact our support team if you'd like to test the private beta of our 'trusted cookie' solution. Server-side cookie service ITP limits the ability of scripts to set cookies lasting for longer than 7 days (or 24 hours in some cases). But this limit is removed if a web server securely sets the HTTPS cookie, rather than via a browser script. This also has the advantage of making sure any cross-domain links tracked using GA's linker plugin can last more than one day after the click-through with ITP 2.3. The downside is this requires either adapting your servers, proxy servers or CDN to serve a cookie for GA and adapt the GA client-side libraries to work on a web server. If your company uses Node.js servers or a CDN like Amazon CloudFront or Cloudflare this may be significantly easier to achieve. If you don’t have direct control of your server infrastructure it’s a non-starter. Also, a caveat is that Apple recommends settings cookies as HttpOnly to be fully future proof - but those would then be inaccessible by the GA client tracking. Full technical details. What about other marketing tags working on Safari? All other marketing tags which track users across more than one session or one subdomain are going to experience the same problem. With Google Ads the best solution is to link your Ad account to Google Analytics, since this enables Google to use the GA cookie to better attribute conversion in Google Ads reporting. Facebook will no doubt provide a solution of their own, but in the meantime you can also attribute Facebook spend in GA using Littledata’s connection for Facebook Ads. Are there any downsides of making these changes? As with any technical solution, there are upsides and downsides. The main downside here is again with user privacy. Legally, you might start over-tracking users. By resetting cookies from the local storage that the user previously requested to be deleted, this could be violating a user’s right to be forgotten under GDPR. The problem with ITP is it is actually overriding the user’s preference to keep the cookie in usual circumstances, so there is no way of knowing the cookie was deleted by the user … or by Safari supposed looking out for the user! Unfortunately as with any customisation to the tracking code it brings more complexity to maintain, but I feel this is well worth the effort to maintain marketing attribution on one of the world's most popular browsers.
Ecommerce trends at Paris Retail Week
Physical or digital? We found merchants doubling down on both at Paris Retail Week. At the big event in Paris last month, we found retailers intent on merging the online and offline shopping experience in exciting new ways. See who we met and what the future of digital might hold for global ecommerce. Representatives from our European team had a great time at the big ecommerce event, one of the 'sectors' at Paris Retail Week. Outside of the event, it was great to have a chance to catch up with Maukau, our newest Shopify agency partner in France. (Bonjour!) Among the huge amount of digital sales and marketing trends we observed throughout the week, a few emerged again and again: mobile-first, phygital experience, and always-on, multi-channel marketing. Getting phygital Phygital? Is that a typo? Hardly. It’s the latest trend in ecommerce, and it was prevalent everywhere at Paris Retail Week. Phygital combines “physical” and “digital” experiences in a new ecosystem. This offers the consumer a full acquisition experience across different channels. From payment providers to marketing agencies, everyone was talking about going phygital. One of our favourite presentations was by AB Tasty. They focused on how optimising client experience can boost sales and conversions in the long-term. It’s not enough to promote your products, nor to link to an influencer for social proof -- you need to create a full customer experience. Starbucks and Nespresso are good examples of how this works offline, assuring that a customer who comes in to drink a coffee will linger around for the next 20-30 minutes. By keeping the customers in the shop, they will eventually order more. The goal is to reproduce this immediately sticky experience online too, and focusing on web engagement benchmarks is the best way to track your progress here. Using the example of conversion rate optimisation (CRO) for mobile apps, AB Tasty's Alexis Dugard highlighted how doing data-driven analysis of UI performance, on a very detailed level, can help clarify how mobile shopping connects with a wider brand experience. In the end, customer experience means knowing the customer. 81% of consumers are willing to pay more for an optimal customer experience. Brands that are reluctant to invest in customer experience, either online or offline, will hurt their bottom line, even if this isn't immediately apparent. Those brands that do invest in multi-channel customer experience are investing in long-term growth fuelled by higher Average Order Value (AOV). 81% of consumers are willing to pay more for an optimal customer experience -- the statistic speaks for itself! Another great talk was from Guillaume Cavaroc, a Facebook Academie representative, who discussed how mobile shopping now overlaps with offline shopping. He looked at experiments with how to track customers across their journeys, with mobile login as a focal point. In the Google Retail Reboot presentation, Loïc De Saint Andrieu, Cyril Grira and Salime Nassur pointed out the importance of data in retail. For ecommerce sites using the full Google stack, Google data represents the DNA of the companies and Google Cloud Platform is the motor of all the services, making multi-channel data more useful than ever in assisting with smart targeting and customer acquisition. The Google team also stated that online shopping experiences that don’t have enough data will turn to dust, unable to scale, and that in the future every website will become, in one way or another, a mobile app. In some ways, "phygital" really means mobile-first. This message that rang out clearly in France, which is a mobile-first country where a customer's first encounter with your brand or product is inevitably via mobile -- whether through a browser, specific app or social media feed. [subscribe] Multi-channel experience (and the data you need to optimise it) Physical marketing is making a comeback. Boxed CEO Chieh Huang and PebblePost founder Lewis Gersh presented the success of using online data for offline engagement, which then converts directly back on the original ecommerce site. Experimenting heavily in this area, they've seen personalised notes on invoices and Programmatic Direct Mail (with the notes based on viewed content) generate an increase of 28% in online conversion rate. Our real-world mailboxes have become an uncluttered space, and customers crave the feel of a paperback catalogue or simple postcard, to name just a bit of the physical collateral that's becoming popular again -- and being done at a higher quality than in the years of generic direct mail. Our real-world mailboxes have become an uncluttered space, and customers crave the feel of a paperback catalogue or simple postcard. However, data is still the backbone of retail. In 2017 Amazon spent approximately $16 billion (USD) on data analysis, and it was worth every penny, generating around $177 billion in revenue. Analysing declarative and customer behaviour data on the shopper’s path-to-purchase is a must for merchants to compete with Amazon. Creating an omni-channel experience for the user should be your goal. This means an integrated and cohesive customer shopping experience, no matter how or where a customer reaches out. Even if you can't yet support an omni-channel customer experience, you should double down on multi-channel ecommerce. When Littledata's customers have questions about the difference, we refer them to Aaron Orendorff's clear explanation of omni-channel versus multi-channel over on the Shopify Plus blog: Omni-channel ecommerce...unifies sales and marketing to create a single commerce experience across your brand. Multi-channel ecommerce...while less integrated, allows customers to purchase natively wherever they prefer to browse and shop. Definitions aside, the goal is to reduce friction in the shopping experience. In other words, you should use anonymous data to optimise ad spend and product marketing. For marketers, this means going beyond pretty dashboards to look at more sophisticated attribution models. We've definitely seen this trend with Littledata's most successful enterprise customers. Ecommerce directors are now using comparative attribution models more than ever before, along with AI-based tools for deeper marketing insights, like understanding the real ROI on their Facebook Ads. The new seasonality So where do we go from here? In the world of ecommerce, seasonality no longer means just the fashion trends of spring, summer, autumn and winter. Online events like Black Friday and Cyber Monday (#BFCM) define offline shopping trends as well, and your marketing must match. "Black Friday" saw 125% more searches in 2017, and "Back to School" searches were up 100%. And it isn't just about the short game. Our own research last year found that Black Friday discounting is actually linked to next-season purchasing. Phygital or otherwise, are you ready to optimise your multi-channel marketing? If not, you're missing out on a ton of potential revenue -- and shoppers will move on to the next best thing.
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