Category : Google Analytics
Can you trust Smart Goals in Google Analytics?
Recently, Smart Goals in Google Analytics have resurfaced as a helpful feature for ecommerce merchants, but particularly Shopify merchants. In a previous post, we outline what Smart Goals are and why some ecommerce businesses use them. However, a lack of trust (and lack of endorsement) with the Google Analytics feature has turned away ecommerce merchants, particularly Shopify merchants. Like we discussed in the popular post, Smart Goals is a goal setting users can enable in Google Analytics. Unlike other goals, Smart Goals uses both behavioral data and contextual (shared) data to predict which of your web sessions will result in a conversion. The pitfall here is that the data is not your data, which would naturally be the best predictor of future conversions. Instead, Google's algorithm seeks highly-engaged visitors and then uses that data to conclude the likelihood a given web session ends with a conversion. Google puts it this way: To generate Smart Goals, we apply machine learning across thousands of websites that use Google Analytics and have opted in to share anonymized conversion data. From this information, we can distill dozens of key factors that correlate with likelihood to convert: things like session duration, pages per session, location, device and browser. We can then apply these key factors to any website. The easiest way to think about Smart Goals is that they reflect your website visits that our model indicates are most likely to lead to conversions. Are Smart Goals a good idea? There's a big hitch in the original concept. Smart Goals was designed for merchants using Google Ads who don’t use conversion tracking. Smart Goals was to help optimise their Ads campaigns by collecting important metrics of user engagement. In theory, it sounds brilliant and helpful for ecommerce merchants and business owners of all scales. But here's how it breaks down in real life: Advertise, measure, repeat As a rule of thumb, ecommerce merchants with stores of all sizes should be measuring their advertising performance. Even if you're creating a "set it and forget it" Google Ads campaign, it's still crucial to track product views, page views, user engagements, cost per click, etc. If you're advertising your products without measuring, you're likely wasting your time and your budget. So how do you ensure you're making good use of ad dollars? Properly set up conversion tracking. Littledata's Google Ads connection is a great place to start. With the connection, you can be confident in your data reporting and that you're tracking the metrics that matter. With conversion tracking, you can follow a shopper's journey and see how many ad clicks lead to purchases, contacts, downloads, signups and more. This data will help you better optimise your campaigns and adjust the ad copy, visuals and calls-to-action to what performs best. Unfortunately, there are thousands of ecommerce merchants who advertise their products without proper conversion tracking. This sets them up for underperforming campaigns and stalls their online store from scaling. [subscribe heading="Try Littledata free for 14 days" button_text="Start your free trial" button_link="https://www.littledata.io/app/get-free-trial"] Can you really trust anonymous data? The short answer is a resounding no, and for a few reasons: Using other people's data to make crucial product and marketing decisions around your campaigns, your website and your customers isn't a good idea. Only your own customer behavior trends will guarantee you're making optimal business decisions for your product marketing campaigns and your online store. How does Google's algorithm determine likely conversions? If conversions aren't defined and conversion tracking isn't properly set up, how can likely conversions be determined? Google basically assigns each web session a score, with the top sessions made into Smart Goals. That begs the question, "what defines top sessions?" Google scans anonymous data (such as session duration, pages per session, location, device, and browser) to select the users that are "most engaged" in your online store. For example, let's say Shawna the Shopify merchant. Shawna uses Google Analytics to track her product sales and other "big data" figures. However, Shawna has never set up goals in GA. For someone like Shawna, Google would use engagement metrics in place of conversion metrics, since Shawna has no conversion tracking for her Shopify store. This is not necessarily problematic. What is problematic is that other important metrics are left untracked. This includes metrics like: Average order value Customer lifetime value Cost of engaged users Sales increases Google Ads campaign optimisation If conversion tracking was set up (rather than Smart Goals), Shawna would easily be able to trace the online journeys and user engagements on her Shopify store. Littledata's Shopify connection with Google Analytics would also provide Shawna with curated reports and analytics to help make sense of her GA data stream. What's the verdict? While even Google advocates for conversion tracking, there is a better way to track the metrics that support better decisions for your ecommerce business. When advertising, especially with Google Ads, it’s incredibly important to use your own data to make decisions for the positive growth of your campaigns.
[Free ebook] Accurate Shopify data is closer than you think
Even for essential ecommerce data like product sales and transactions, setting up a reliable data collection system is harder than one might think. Many ecommerce marketers use Google Analytics to track performance, but it's not as simple as a "1...2...3" setup. At Littledata, we work with top apps and agencies in the Shopify ecosystem, especially Shopify Plus partners. In turn, these partners work with marketing managers, data analytics experts and ecommerce store managers across the globe. One of the questions we often receive from these managers: Why don’t my transactions in Google Analytics match those in Shopify? While a plethora of factors can cause differences in Shopify tracking results, we’ve narrowed it down to 6 main causes. 1) Orders go unrecorded in Google Analytics Why does this happen? As a Shopify store owner, your customer never sees the order confirmation page. When online orders go unrecorded in Google Analytics, it’s almost always due to payment gateways not sending users back to the order thank you page. 2) Errors occur in the Google Analytics/Google Tag Manager integration The Google Analytics/Tag Manager integration allows Google Analytics to track only a few “micro-moments” (page visits, page bounces, etc.) required for a complete picture of your customers' online shopping journey. Though commerce connections like Shopify’s are designed to work for standard websites, some store owners build themes that are more personalised to their products. This requires a custom integration with Google Analytics. Want to know the other 4 causes? These two issues probably seem highly fixable (they are) but they don't stand alone. There are a host of factors that cause data mismatches between Shopify and Google Analytics data, all of which threaten to weaken your marketing strategy, hurt your sales performance and damage your bottom line. Luckily, we have just the thing to help. Our free ebook, Why your Google Analytics data doesn't match your Shopify data, isn't just an answer to the question — it's packed with details, pro tips and an ultimate solution to your data mismatches. The ebook will also show you how common tools like ReCharge and CartHook can actually skew your data (and how to fix this). The best Shopify analytics are those that are accurate and trustworthy. With the help of our ebook, you're on your way to Shopify greatness! [subscribe heading="Get the free ebook" background_color="green" button_text="Free download" button_link="https://www.littledata.io/app/ebook-why-google-analytics-dont-match-shopify-analytics"]
How to fix marketing attribution for Safari ITP 2.2
The latest version of Safari limits 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 12th June 2019 to clarify changes for ITP 2.2. 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 2.1 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 two 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) 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, 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 between a quarter and a half of all your visits. The update (ITP 2.1) is included in Safari version 12.1 onwards for Mac OS and Safari Mobile. It does not affect Safari in-app browsing. Apple released iOS 12.2 and Mac OS 10.14.4 on 25th March 2019, and at the time of writing around 30% of all web visits came from these two browser versions on a sample of larger sites. The volume for your site may vary; you can apply this Google Analytics segment to see exactly how. 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 are three outline fixes I would recommend. I’m grateful to Simo Ahava for his research on all the possible solutions. The right solution for your site depends on your server setup and the development resources you have available. If you’re lucky enough to use our Shopify app the next version of our script will include solution 1 below. Contact our support team if you'd like to test the private beta version. For each solution, I’ve rated them out of three in these areas: Quick setup: how much development time it will take to solveCompatibility: how likely this is to work with different domain setupsLongevity: how likely this is to work for future updates to Safari ITP Solution 1: Local storage Quick setup *** Compatibility ** Longevity* To solve the one day cookie expiry, you store the GA client ID in the browser’s local storage (which does not expire), along with the cookie. So before we allow GA to set a new client ID we first check if the Safari browser has a local storage. Here are the full technical details. Solution 2: Common iFrame plus local storage Quick setup ** Compatibility*** Longevity * The problem with solution 1 is that local storage is only available to an individual subdomain. Let's imagine a user journey that goes: Day 1: Visits blog.mysite.comDay 8: Visits shop.mysite.com In this case, the two visits cannot be linked because after 7 days the cookie has expired, and shop.mysite.com cannot access local storage on blog.mysite.com. Solution 2 fixes this by setting up a page on the top level domain (e.g. www.mysite.com/tracker.html) on which that local storage is set, and the page can be accessed from any subdomain. What makes it longer to setup is it will require a new page on your web server, not just script changes on the existing pages (or via GTM). Full technical details. Solution 3: Server-side cookie service Quick setup * Compatibility *** Longevity *** In the long term, ITP may target the local storage API itself (which is already blocked in Private browsing mode). So solution 3 securely sets the HTTPS cookie from your web server itself, 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 2.2. 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. 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.
Link Analytics to AdWords with our new Google Ads connection
To target -- and retarget -- the right shoppers, ecommerce sites need to connect customer behaviour and ecommerce data from Google Analytics with their Google Ads (AdWords) accounts. But until now that was a complicated process, to say the least. Marketers have spent years going through detailed setup steps to connect the platforms, or wading through spreadsheets with manual imports and exports, building custom audiences and segments. It was an ongoing headache, but they did it because connecting shopping behaviour data with AdWords campaigns gets big results. Now there's a better way. Littledata's new Google Ads connection makes it easy to link Analytics to AdWords. Ecommerce sites are using the connection for smarter targeting that increases online sales and customer LTV. Why should you link Analytics to AdWords? In past posts we've highlighted the benefits of linking Analytics with AdWords for a mutually beneficial relationship. Littledata's new connection automates the process to ensure accurate tracking and more targeted campaigns. Benefits include: Online sales data in AdWords reports, and visa versa. Add sales columns to reports in Google Ads and view Google Ads costs in Google Analytics. Abandoned cart campaigns. Get higher ROI with targeted PPC campaigns based on shopping cart activity. Ecommerce hyper-segmentation, especially for Shopify stores and enterprise clients. Since Littledata fixes ecommerce tracking across the checkout flow, the Google Ads connection is especially powerful for marketers looking to retarget with granular user behaviour data, such as product list views, product detail pages and adds-to-cart. Multiple accounts. Multiple views. Our Google Ads connections lets you link multiple AdWords accounts to multiple Google Analytics views. It's that simple. Wait, do you mean Ads or AdWords? Have you heard the news? Google AdWords is now Google Ads. Google pitched the switch to Ads as a large-scale rebrand for simplicity, but it's clearly targeted in part at bumping up competition against other 'ads' in common parlance: Facebook Ads, Instagram Ads and Twitter Ads, with Reddit Ads quickly gaining pace among SaaS companies in particular. We still talk about AdWords a bit on the blog (as does the rest of the internet, such as Search Engine Land), but soon we'll all have to adapt to the change. So we're calling this new connection a Google Ads connection, but we don't expect marketers to stop chatting about AdWords any time soon. How does it work? After you sign up for Littledata, you can connect Analytics to AdWords from the Connections tab in the Littledata app. Just follow a couple of setup steps and the app makes the connection for you. No more manual connections. Plus, we audit your analytics setup continually to ensure consistent ecommerce tracking, campaign tagging and UTM parameters. So what are you waiting for? Those products aren't going to retarget themselves... And don't forget to try our Facebook Ads connection to complete your marketing analytics stack. It's an easy way to link Facebook Ads to Google Analytics. All paid plans in the Littledata app include a variety of Google Analytics connections for Shopify, Shopify Plus, ReCharge, Refersion, CartHook and more. PS. The next iteration of our Google Ads connection will provide automation for retargeting using ecommerce segments. Sign up for Littledata today so you're first in line!
Why you should link Google Ads with Google Analytics
Google Ads (formerly Google AdWords) and Google Analytics have constantly proved their worth as valuable tools for ecommerce marketers to get insights and detailed reporting on advertising ROI. But why should you link Google Ads and Google Analytics together? What does it mean to connect them? Our enterprise ecommerce customers in particular have seen a major benefit of linking Analytics with Ads. Those who linked these two platforms have seen a significant improvement in reporting and it made it much easier to retarget ads to clients that have forgotten or abandoned their services but shown intent to purchase a particular product or type of product. Why connect? Is it really necessary to connect Google Ads linked with Analytics? Let's get down to basics. In the Ads platform you can’t see what your users do after they click on your ads or if said ads led to a sale, you can’t see their path on your website, so you are basically losing the big picture of your customer’s behaviour after they see the ad. In short, without connecting the two technologies together, your shopping funnel is incomplete. You can't see Google Ads performance compared with other marketing channels, or how those Ads actually contribute to revenue. Both Google tools have their individual strengths but you can see their real power once you have linked both of them. If you are already using both Analytics and Google Ads but haven’t linked them yet, then you are missing a lot of valuable information about how to connect marketing with revenue -- and where to optimise. [subscribe button_text="Free Google Analytics Connection"] With the two platforms tied together, they will be able to communicate much more efficiently and provide more granular data in your reporting. Google Analytics has a dedicated section within the Acquisition reports solely detailing Google Ads performance which you cannot obtain unless you have linked your Google Ads and Analytics accounts and are using auto-tagging in Google Ads. These reports share some common information with the types of data that can be found in Google Ads, but here you are able to combine and link the Google Ads data with all the data available in Analytics to find more meaningful insights and potentially make better decisions. Moreover, you are able to leverage these insights into a number of different goals that you wouldn’t be able to easily see in Google Ads. Surprisingly though, a full connection doesn’t happen automatically. Yes, they are both Google products, but you need to do some work to connect the platforms and then take action based on that data. Google's thoughts on connecting Google Ads with Google Analytics This quick video highlights the benefits of linking the two platforms together (whether you call them Ads or AdWords is up to you...marketers are still a bit confused by Google's rebrand). https://www.youtube.com/watch?v=8EmXFM1_xEo Top four benefits of linking Google Ads with Google Analytics for ecommerce 1. Retarget based on checkout steps in ecommerce The most effective way to grab these customers is to target them based on where they dropped off. Luckily, Google lets you do exactly that: with the right analytics, you can set up retargeting campaigns based on checkout behaviour. We highlighted this in a more comprehensive blog post on how you can improve Google Ads retargeting by analyzing the customer behavior during checkout. Our customers have been applying those tips and seeing results in less than a week. Learn more about how to improve AdWords retargeting using ecommerce checkout steps. 2. Retarget based on users who reach a Google Analytics goal You can set up a simple or complex goal and then target that audience with the right messaging. For example, even a newsletter subscription can lead to a goal completion. That user showed interest in your product and with a bit of persuasion and smart ad targeting, you’ll most likely succeed in transforming that lead into a buying customer. PRO TIP: Watch our video on troubleshooting your Google Analytics goals setup if you're having issues with goals. 3. Block advertising to people who have previously purchased An effective retargeting audience setting is crucial. There is no need to spend money on retargeting ads for people who will not be convinced to buy by them. If someone has already purchased a product from your online store, then the chance of them buying the same product in the next few days is nihil. If you don’t set an effective retargeting audience, you are more likely to spend way more money for with no result. The solution is to exclude people who recently bought your products from retargeting for a certain period, and you’ll be able to retarget them again after a certain time frame. That means that if John from California just bought a shirt from my website, I will not retarget him for the next month; he will not see any ads of the shirt appearing on his browser for that period. [subscribe "button_text="Free Google Analytics Connection"] If you want to see the best result of with your retargeting campaign then keep this in the back of your mind when making campaign planning. You will be left with more budget to spend on retargeting ads that are actually effective and most important of all, a happier audience. 4. Send different adverts to different segments of customer lifetime value (LTV) Our biggest customer segment right now is automated analytics for ecommerce subscription businesses. It should come as no surprise that subscription ecommerce merchants get a special benefit from linking Ads with Analytics. Littledata's ReCharge connection enables you to see customer lifetime value and create different audiences based on a customer’s last purchase or the number of orders placed. By this segmentation of audience you can customise your PPC ads and reach the right people who are already loyal to your brand and know your products. Your ROAS will be amazing and you won’t have to make huge efforts to get major results. Questions? The benefits above speak for themselves, so what are you waiting for? Especially if you run an ecommerce site, the time to connect is now :) If you’re trying to connect Google Analytics with AdWords for an ecommerce site, it should go smoothly. But sometimes an account manager can help with custom setup and reporting, or simply check to make sure you’re tracking things correctly. Littledata’s pricing options include various levels of support to fit every business size and goals for growth. Check out our free guide on how to connect your Google Analytics and AdWords accounts.
How to calculate customer lifetime value (CLV) for subscription ecommerce in Google Analytics
Many of Littledata's subscription customers come to us with a similar problem: how to calculate return on advertising spend, considering the varying customer lifetime value (CLV) of subscription signups. Calculating marketing ROI for subscription ecommerce is a big problem with a number of potential solutions, but even the initial problem is often misunderstood. In this post I break down what the problem is, and walk through two proven solutions for getting consistent, reliable CLV reporting in Google Analytics. What is customer lifetime value? I work with all kinds of subscription ecommerce businesses: beauty boxes, nutritional supplements, training courses and even sunglasses-by-the-month. All of them want to optimise customer acquisition costs. The common factor is they are all willing to pay way MORE than the value of the customers' first subscription payment... because they expect the customer to subscribe for many months. But for how many months exactly? That's the big question. Paying for a marketing campaign which bring trial customers who cancel after one payment - or worse, before the first payment - is very different from paying to attract sticky subscribers. A marketing director of a subscription business should be willing to pay WAY more to attract customers than stay 12 months than customers who only stay one month. 12 times more, to be precise. So how do we measure the different contribution of marketing campaigns to lifetime customer value? In Google Analytics you may be using ecommerce tracking to measure the first order value, but this misses the crucial detail of how long those shoppers will remain subscribers. With lifetime customer value segments we can make more efficient use of media, tailor adverts to different segments, find new customers with lookalike audiences and target loyalty campaigns. There are two ways for a marketing manager to see this data in Google Analytics: one is a more difficult, manual solution; the other is an easier, automated solution that ties recurring payments back to the original campaigns. A manual solution: segment orders and assign a lifetime value to each channel It's possible to see the required data in GA by manually segmenting orders and assigning a lifetime value to each channel. For this solution you'll need to join together: (a) the source of a sample of first orders from more than a year ago, by customer number or transaction ID and (b) the CLV of these customers The accuracy of the data set for A is limited by how your Google Analytics is set up: if your ecommerce marketing attribution is not accurate (e.g. using Shopify's out-the-box GA scripts) then any analysis is flawed. You can get B from your subscription billing solution, exporting a list of customer payments (and anonymising the name or email before you share the file internally). To link B to A, you'll need either to have the customer number or transaction ID of the first payment (if this is stored in Google Analytics). [subscribe] Then you can join the two data sets in Excel (using VLOOKUP or similar function), and average out the lifetime value by channel. Even though it's only a sample, if you have more than 100 customers in each major channel it should give you enough data to extrapolate from. Now you've got that CLV by channel, and assuming that is steady over time, you could import that back into Google Analytics by sending a custom event when a new customer subscribes with the 'event value' set as the lifetime value. The caveat is that CLV by channel will likely change over time, so you'll need to repeat the analysis every month. If you're looking to get away from manual solutions and excessive spreadsheets, read on... A better solution: tie recurring payments back to the original campaign(s) What if you could import the recurring payments into Google Analytics directly, as they are paid, so the CLV is constantly updated and can be segmented by campaign, country, device or any other standard GA dimension? This is what our Google Analytics connection for ReCharge does. Available for any store using Shopify as their ecommerce platform and ReCharge for recurring billing, the smart connection (integration) ties every recurring payment back to the campaigns in GA. Here's how the connector works The only drawback is that you'll need to wait a few months for enough customer purchase history (which feeds into CLV) to be gathered. We think it's worth the wait, as you then have accurate data going forward without needing to do any manual imports or exports. Then, if you also import your campaign costs automatically, you can do the Return on Investment (ROI) calculations directly in Google Analytics, using GA's new ROI Analysis report (under Conversions > Attribution), or in your favourite reporting tool. Do you have a unique way of tracking your marketing to maximise CLV? Are there other metrics you think are more important for subscription retailers? Littledata's connections are growing. We'll be launching integrations for other payment solutions later this year, so let us know if there's a particular one you'd like to see next.
Shopify's 'sales by traffic source' report is broken
If you're a Shopify store manager, one of your biggest questions should be 'which campaigns lead to sales?'. We looked at data from 10 Shopify Plus customers to see whether the sales by traffic source report can be trusted. Under the Shopify store admin, and Analytics > Reports tab, you can (in theory) see which sessions and sales came from which traffic sources. BUT this sales by traffic source report is broken. Looking at 180,000 orders for 10 stores in Q4 2018, here are the marketing channels which Shopify Analytics says brought the traffic: Direct 83.5%Social 9%Search 4.5%Unknown (other websites, not social or search) 3%Email ~0.1% And using comparative data from Google Analytics we know this is all wrong. Here's a comparison of Shopify's attribution to Google Analytics last-click attribution of sales for one of these customers: Marketing attribution comparison for 700 orders Shopify Google Analytics Direct 99% 43% Search (Paid + Organic) 0.6% 7% Social 0.4% 10% Email - 25% Affiliates - 15% Here's why it's broken 'Direct' traffic is when the source is unknown. But for Shopify's report this means where the source of the last session is unknown - the user most probably visited a search ad or product review previously. Having only 1% visibility on your marketing performance is just not acceptable!We know that tagged Facebook traffic alone represents 7% of traffic for the average store, so 10% of sales from Social is more normal. Social also brings more than the actual sales in terms of visibility and influencers.Google generates billions of pageviews a month for ecommerce stores. If your site gets only 1% of its traffic from search, we'd be very surprised! Including paid search this site is still well below the 40% average. (Check out our 6 essential benchmarks for Shopify stores.)Monthly emails and personalised retargeting emails are now a staple of online marketing, and we know all the customers in this analysis use email marketing of some form - including for new product launches, discounts and cart abandonment campaigns. The problem is, it's unlikely to be the only campaign which brought customers, so it gets drowned out by other 'last click' channels. The solution: multi-channel attribution.Affiliates are a really important channel to get right, as they are paid based on the sales attributed to them. Why should you rely solely on the report the affiliate marketer gives you, and not see the same numbers in Google Analytics? So don't leave your marketing analytics to guess-work! Try the Littledata app to connect Shopify with Google Analytics on a free trial today. All paid plans include unlimited connections, to ensure accurate marketing attribution for sales via ReCharge (subscriptions), CartHook (one-page checkout), Refersion (affiliates) and more.
Introducing Shopify Flow connectors for Google Analytics
Littledata has launched the first Shopify Flow connector for Google Analytics, enabling Shopify Plus stores to analyse customer journey using a custom event in Google Analytics. In addition to Littledata's native connections with Shopify, Shopify Plus, Facebook Ads, ReCharge, etc., we have now launched a beta version of a Flow connector for Google Analytics. What is Shopify Flow? Flow is an app included with Shopify Plus, which enables stores to define automation pathways for marketing and merchandising. Think of it as an ‘If This Then That’ generator just for Shopify. For example, after an order is marked as fulfilled in Shopify’s admin you might want to trigger an email to ask for a review of the product. This would involve setting a ‘trigger’ for when an order is fulfilled and an ‘action’ to send an email to this customer. How do you use Littledata Flow actions? You install Littledata's Shopify app along with Shopify Flow Every time an order is created in your store we send it to Google Analytics, along with information about which customer ID made the order (nothing personally identifiable) You add Littledata's actions to your Flow Every time the order or customer event is triggered, even for offline events, the event is linked back to Google Analytics In Google Analytics you can then: Segment the customer base to see if these actions influence purchasing behaviour Visualise when these events occurred Analyse the customers making these actions: which geography, which browser, which marketing channel (in GA 360) Export the audience to retarget in Google Ads (in GA 360) Export the audience to run a website personalisation for using Google Optimize How do you set the actions up in Flow? Google Analytics customer event – can be used with any customer triggers, such as Customer Created Google Analytics order event – can be used with any order triggers such as Order Fulfilled, Order Paid, How else could I use the events? You can now link any of your favourite Shopify Apps with Flow connectors into Google Analytics. Some examples would be: Analyse if adding a product review leads to higher lifetime value Retarget in Google Ads after a customer's order is fulfilled Set up a landing-page personalisation for loyal customers (using Loyalty Lion connector) How much does this cost? The Flow connectors are included as part of Littledata’s standard subscription plans. You’ll need Littledata’s app to be installed and connected to link the events back to a customer – and to get reliable data for pre-order customer behaviour. [subscribe] Can Littledata set up a flow for a specific app? Our Enterprise Plans offer account management to help you configure the Littledata Shopify connection, including the Shopify Flow connectors. Get in touch if you have a specific app you'll like to make this work with.
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