How to get complete ReCharge data in Google Analytics [ebook]
It's hard enough for Shopify stores to get accurate sales and marketing data. And if you're selling by subscription, this can seem even more complicated. In fact, 88% of Shopify stores have Google Analytics setup incorrectly, leading to a throughput of less than 90% (for every 100 orders in Shopify, 12 or more go missing in GA). I hate to break it to you, but for subscription merchants the reality is even harsher. Many brands can't even segment out first-time purchases from recurring orders, let alone tie them back to marketing campaigns! Luckily there's now a better way. Top subscription brands use modern data stacks to get the data they need to make informed decisions. This means understanding your checkout flow, yes, but also product lists, subscription bundles, discounts, returns, subscription lifecycle behavior, and top marketing channels for higher LTV customers. In this new ebook on ReCharge analytics, we show you how to do just that -- no developer skills needed! Free ebook on ReCharge analytics best practices Subscription analytics are a beast, and too many brands make one of these three common mistakes: Procrastination. "We know we have a data problem but will fix it next quarter...year...never..."The wrong tools. "We bought a fancy new dashboard, that will solve everything, right?" or "We bought this subscription analytics tool that works really well for SaaS companies. Why isn't it working well for ecommerce?"Completely manual approach. "Excel is my full-time job. I don't have time for data-driven growth." Top brands use modern data tools to tame the beast of analytics. In this new ebook, you'll learn how to get the data you need to accelerate growth. See how to automatically capture data at every turn: Track one-off orders and first-time subscriptionsTrack recurring payments and tie them back to the original marketing channelCalculate customer lifetime value ("CLV" or "LTV") and build more valuable cohortsCapture subscription lifecycle events like "Subscription updated"Get accurate marketing attributionUltimately make better decisions for your store Download the free ebook >>> Learn more about what you can track with Littledata's ReCharge connection. [tip]Advanced users can also now send data directly to Segment (and any connected data warehouse, email marketing platform or reporting tool).[/tip]
Shopify Analytics: Everything You Need to Know
Every good business runs on good data. It doesn’t matter if you’re choosing a store design, analyzing your marketing, or setting revenue targets, it all comes back to what the data tells you. On the flip side, running on bad data can lead to your store whiffing on those big decisions. That’s where, if you’re a Shopify store, Shopify Analytics (and other analytics options) come into play. In this post, we’re going to: Break down what Shopify Analytics does Discuss Shopify Analytics’ limitations Share tools that can give you deep, accurate data and drive revenue Show you how to add powerful data tools to your ecommerce store What does Shopify Analytics do? Built within its platform, Shopify has an analytics tracker that allows you to generate data based on your store’s performance. This data includes high-level metrics like your total store sessions, number of sales, returning customers, and the average value of orders placed. [caption id="attachment_13280" align="aligncenter" width="600"] Shopify Analytics' overview dashboard gives you a snapshot of your store's high-level metrics.[/caption] Metrics like these help you get a snapshot of how visitors are interacting with your store. That way, you can pinpoint elements of your website to tweak or update based on what the data is telling you and continue to improve your metrics overall. Let’s take a closer look at some of the more popular metrics that Shopify Analytics displays within its overview dashboard: Total Sales: This metric displays the total revenue your store has generated over a specific date range minus costs like shipping and taxes. Online Store Sessions: The online store sessions metric counts the total number of customers who visited your site in a given date range, including repeat visitors. Returning Customer Rate: Returning customer rate shows the percentage of customers who have purchased from your store more than once. These customers are valuable due to their loyalty and subsequent higher lifetime value. Online Store Conversion Rate: Conversion rate tracks the number of visits that led to a purchase. Average Order Value (AOV): Average order value is calculated by taking your total order revenue and dividing it by the number of orders. The first step to using these metrics to improve your store is knowing where to find them. How to use Shopify Analytics Shopify displays data and reports about your store’s performance within its “Overview Dashboard.” The Overview Dashboard also allows you to carry out a range of basic data analyses. This includes: Comparing the value of your current sales to a previous date range Tracking how many sales you receive from a variety of marketing channels Generating your AOV Tracking your site trends over time To access this Overview Dashboard, start from your Shopify admin page and go to Analytics > Dashboards. The dashboard will display data generated from today and compare it to the day before. You can change this date range by selecting the date menu. You can also change the comparison period for this data by clicking compare to previous dates, then Apply and your data will be generated. You can then select “View report,” which gives you a more detailed analysis of your chosen metric. Be aware, however, that not all metrics will generate in your report. The metrics you can see will depend on the Shopify plan you are currently on. What analytics are in Shopify If your store uses Shopify Lite, your analytics report will show you a basic range of metrics, including the overview dashboard, finance reports, and analytics about your products. To access detailed reports like visitor behavior analysis or marketing and sales reports, you will need to upgrade to the Basic Shopify plan or higher. Shopify Analytics can generate a few other metrics beyond the most high-level ones mentioned above. Incorporating these into your data strategy is also important to maximize marketing attribution and revenue. Sales Metrics Some of the most valuable sales metrics generated through Shopify Analytics include: Total sales - the amount of revenue that was generated through your online store or your Point Of Sale if you have a physical storefront. Sales Source - this lists the sources from which your sales generated (i.e. social media channels, ads, or direct traffic.) Total orders - this metric displays the total number of orders generated through both your ecommerce store and your physical store. Customer Metrics Top products by units sold - This metric shows the items in your store which sold the most by volume, helping you identify your most popular offerings. Top site landing pages - This indentifies the most frequent landing pages on your site where visitors started a session. Returning customer rate - This gives the percentage of customers who have bought from you repeatedly in a selected time period. Shopify Behavior Reports Shopify also provides behavior reports which record customer actions on your site and allow you to: Track how your online store conversions have changed over time. Determine the top online searches for your product. Track how your product recommendations change over a given period. [caption id="attachment_13295" align="aligncenter" width="600"] Shopify Analytics' behavior reports help you drill down into how key metrics have changed over time.[/caption] All these metrics can play a key part in your overall marketing strategy and help you improve marketing attribution. But to make the best decisions for your business, you need truly accurate data — something Shopify Analytics has a spotty record with. Is Shopify Analytics good? Shopify Analytics is a good tool overall for what it is: an out-of-the-box solution for basic analytics tracking on your ecommerce store. Shopify Analytics provides the top-level metrics to give you a broad snapshot of your store’s health and customer behavior. But it lacks the detailed reports of a more robust analytics service like Google Analytics. What is Shopify analytics lacking? Unfortunately, Shopify Analytics also has a poor history when it comes to accuracy. Shopify Analytics’ tracking has shown to be both unreliable and incomplete. In fact, an analysis conducted of Shopify Analytics found that for every 100 orders tracked in Shopify Analytics, 12 go missing. There are a handful of other shortcomings those who rely on Shopify Analytics as their main data source face, as well. These include: Cross-domain tracking being setup incorrectly Server-side tracking is missing Sales data doesn't segment between first-time purchases and recurring transactions (subscriptions) Refunds not included in Google Analytics Many of Shopify Analytics’ shortcomings obscure traffic sources and disrupt attribution tracking. As an example, when customers check out on your Shopify store they’re redirected to a Shopify domain, causing the visitor’s session to end suddenly — even if they are in the process of buying an item. This affects what Shopify Analytics shows as their last click and takes away from the power of the data you’re collecting. So, is there a better way to track referrals sources, collect customer behavior metrics, and ensure accurate analytics? Yes: using a more powerful analytics tool like Google Analytics. Shopify Analytics vs. Google Analytics Google Analytics (GA) is a household name for analytics reporting across nearly every industry. In fact, it’s the world’s most popular marketing analytics platform, used by 98% of online stores. While both Shopify Analytics and GA offer unique benefits, store owners who opt for GA get more data for their dollar. We can see this first hand on a metric like sales by traffic source. [tip]Read our full ebook on why Shopify Analytics and Google Analytics don't match, plus how to fix it for your store.[/tip] Littledata looked at 180,000 orders from 10 Shopify stores, and the marketing channels in Shopify Analytics were as follows: Direct 83.5% Social 9% Search 4.5% Unknown (other websites, not social or search) 3% Email ~0.1% The Direct channel sticks out like a sore thumb, mainly because it dwarfs every other source of traffic. Compare this with the last-click attribution of sales from GA, and the difference in accuracy becomes clear: To put it simply, Shopify Analytics lacks both the accuracy and specificity of data that a tool like GA provides. How to add Google Analytics to Shopify While GA doesn’t work automatically with Shopify, it’s not difficult to set up for your store. There are multiple ways you can add Google Analytics to Shopify, and the method you choose will depend both on your technical skill and the time you have to dedicate to set up. Once you’ve created a Google Analytics property for Shopify, you can follow your preferred method to add GA to your store and start getting full, accurate data. Read on to discover which method will work best for adding GA to your store. For Universal Analytics Before 2020, Universal Analytics was the Google Analytics default. To find out if your store has Universal Analytics, check your web property ID. A universal analytics web property ID will start with ‘UA’. If you’re using Universal Analytics, the two options we’d recommend to connect GA to your Shopify store are: Using Shopify’s built-in tracking, found in-store preferences Using Littledata’s advanced Shopify to Google Analytics app For Google Analytics 4 Since late 2020, GA4 has operated as the default Google Analytics property. There are a handful of benefits to using GA4, not least of which being that it provides more thorough reports delivered within a faster timeline. Shopify does not yet support Google Analytics 4, so the built-in tracking feature is not an option here. However, you can try using GA4 and Shopify Analytics in parallel to test the performance of both and see the differences yourself. The “least hassle” option If you want to add GA to your store and you’re looking to save time and get things done correctly, implementing Littledata is likely your best bet. Littledata provides a Getting Started guide to help you add Google Analytics to your Shopify store. Once connected, the Littledata app gives you a thorough data overview and sends weekly updates as Google and Shopify add new features. [tip]Try Littledata's Google Analytics connection free for 30 days to see how it can fix your tracking while integrating with your other Shopify apps.[/tip] Using Google Analytics with Shopify Analytics GA and Shopify Analytics can be used in conjunction with one another, as each have their uses. As an example, you could use Shopify Analytics as a quick overview dashboard for store performance while relying on GA for a complete analysis of sales and marketing efforts. In depth data decisionmaking will still most likely be coming from what you see in GA, but you can still rely on Shopify Analytics to capture big picture metrics. Connecting dashboards and reporting tools The most successful modern DTC stores operate not with GA alone, but with a full data stack that helps them cover each step of the customer journey. They increase the scope of their data coverage by connecting other data dashboards and tools. ReCharge A great tool to connect to your store, especially if you offer subscriptions, is the ReCharge Connection. This connection is an advanced GA integration that helps you to track subscription ecommerce behavior. Connecting Shopify and ReCharge with Google Analytics allows you to obtain accurate sales data, including first-time orders, recurring payments, and subscription lifecycle events. It also allows you to obtain accurate marketing attribution for first-time orders, recurring payments, and subscription lifecycle events. Segment A further tool you could use to track your Shopify data is the Segment app connection, which allows you to track each customer touchpoint within your website, including the checkout steps taken by customers, sales information, and the lifetime value of a specific customer. Segment is a Customer Data Platform (CDP) that makes it easy to combine customer data with marketing data, then send that data to other platforms you use, whether that’s a data warehouse or an email marketing tool. As such, Segment isn’t just for analysis. It’s also a popular way to build new marketing audiences, such as building lookalike audiences in Facebook from your highest-spending Shopify customers. Google Ads and Facebook Ads Online advertising is a major source of traffic for modern DTC brands. To ensure your making the best decisions in your advertising strategy, you need accurate data. That’s where the Facebook Ads and Google Ads connections can play a key part in your overall analytics stack. The Facebook Ads connection fixes campaign tagging and allows for importing ad costs so you can drill down marketing attribution costs. The Google Ads connection is ideal for tracking sales expenses in reports and connecting marketing data with ecommerce performance. Wrapping it all up Now that you know exactly what Shopify Analytics can provide for you, what analytics strategy will you implement to ensure you’re making smart business decisions for your store? Using Google Analytics with your Shopify store gives you: a thorough view of the data a complete snapshot of the entire customer journey advanced metrics you need to improve attribution and boost revenue Using these, you can plan changes to your store and product offerings based on accurate data while improving your visibility by taking control of your analytics tracking. And once you’ve connected other powerful reporting tools and dashboards like Littledata’s ReCharge and Segment apps, you’ll have all the information you need to dial up your store’s growth. Take the first step by getting a free data audit when you start your 30-day free trial with Littledata. [subscribe]
Is it possible to track headless Shopify setups?
Headless commerce is not a new concept, but it's an increasingly popular solution. As larger brands continue to move to streamlined ecommerce checkouts such as Shopify and BigCommerce, they look to headless setups as a way to maintain speed or flexibility. An increasing number of those bigger DTC brands are going headless, whether that means a collection of landing pages leading directly to a Shopify checkout, or a full-on headless architecture implementation with a dynamic CMS. The question today is less whether you should consider headless in the first place (everyone is at least considering it), but more about your overall tech stack. When looking at the details of your stack (cost, functionality, maintenance, etc), it's important to consider headless pros and cons in general. But it's often even more useful to highlight specific use cases. We've previously written about how it's now possible to maintain your favorite Shopify Plus tech stack with a headless Shopify architecture. But what about your data stack? Does headless mean that your analysts will be dealing with a snow storm of anonymous IDs? Are there sacrifices to data accuracy, such as marketing attribution for recurring orders? With the right tools and plug-ins, you can still capture the complete headless journey on your headless site. In this post we look at headless Shopify tracking from several different angles and share resources for further reading. Why headless? DTC brands with a headless Shopify Plus setup now include Inkbox, Rothy's, Verishop, Allbirds, Recess, and many more. So why do merchants go headless? [caption id="attachment_10778" align="aligncenter" width="419"] Headless commerce overview from Shopify Plus[/caption] The main reason is speed, or site speed to be precise. When built the right way, modern headless sites are insanely fast. Ballsy increased conversion rates by 28% after going headless, thanks to dramatically faster page load times. (The average Shopify site sees around 4 seconds to full page load). At the same time, as our agency partner We Make Websites has noted, "extreme performance" isn't for everybody. Sometimes it can be like "the difference between buying a BMW or Audi, versus buying a Ferrari". Additional reasons for going headless include flexibility of controlling and customizing the complete frontend (with a CMS or other content framework). Of course, there are also limitations. When it comes to headless Shopify sites specifically, some trade-offs are the need to maintain multiple technologies or platforms, and the fact that Shopify's Storefront API uses GraphQL (there's currently no REST API for Storefront). Without the right tools, the other limitation is data accuracy and completeness. That can include: Marketing channels (paid channels, organic social communities, SEO) Browsing behavior (landing pages, product lists, website, mobile apps) Sales data (checkout behavior; one-off, first-time and repeat purchases) Ecommerce data from additional checkout apps (subscriptions and upsell flows) Headless tracking in Google Analytics / GTM It's no secret that Shopify and GA need some help to play well together. For every 10,000 orders processed on Shopify, 1,200 go missing in Google Analytics. For your average headless site, the stats are even worse. By default, different customer interactions with your brand — ppc campaigns, product lists, adds-to-cart, checkouts, refunds, recurring orders and subscriptions, email campaigns — are often either not tracked at all or not linked to the original user or session. In that way, you can end up with siloed data in different apps and platforms. Or even worse, everything could show up as anonymous activity or "Direct" traffic, even for repeat purchases. This isn't Las Vegas; what happens in the checkout should definitely not stay in the checkout! We have solved this problem by extending Littledata's server-side tracking to stitch sessions together from the client-side events captured on headless frontends . . . which is a rather technical way of saying that our Google Analytics app for Shopify now tracks headless sites automatically, from browsing behavior through the checkout funnel and beyond (we even capture subscriptions such as ReCharge payments!) This guarantees accurate sales and marketing data for any headless Shopify site. Check out Littledata's headless demo to see how our headless Shopify tracking works for Google Analytics. [tip]Using Google Tag Manager? Read more about our GTM / Data Layer spec.[/tip] Headless tracking in Segment As mentioned, we have offered server-side tracking for Shopify since the beginning, and automatically linked this with client-side events. Now this is available for any headless setup as well. In theory, it should be easy to send data from additional cloud sources to Segment. Each part of your headless frontend stack can just plug right in. But in practice this means manually adding a hodgepodge of client-side and server-side event tracking, and maintaining this as you scale. If you're using Segment as your CDP — or considering using Segment — rest assured that Littledata's headless tracking now fully supports Segment as a data destination. You can try to set this up yourself, but it's much easier (not to mention cheaper and more reliable) to just use our Shopify source for Segment to track your checkout. With Littledata, you can automatically send sales and marketing data from a headless Shopify site to your Segment workspace. We also recently added more flexibility around which fields to send as the userId for known customers. Check out our headless tracking demo to see how our headless Shopify tracking works for Segment. Tracking landing page builders Not every headless site is using a Content Management System (CMS). For those who do, Contentful is the most popular with straightforward headless Shopify builds. There are also "soft headless" sites that rely on a series of landing pages or similar flows, which then lead to the main Shopify site or even directly to the checkout. In the first case, where the landing pages are truly landing pages and lead to your main site, you can use the default settings in Littledata's Shopify app and generally do not need to take the headless install route. For cases where landing pages go directly to the checkout, see the headless tracking demo linked above. We also need to take landing pages seriously. It can actually be just as difficult to get complete marketing attribution or even to link sessions together and track the purchases customers make after landing on one of these pages. To solve this problem, Littledata's automated tracking now tracks landing pages as "additional apps" on top of our main Shopify connections for Segment and Google Analytics. As long as the Littledata script is loading on those landing pages, everything will link together automatically. We have tested this functionality with three of the most popular landing page builders for Shopify stores: Shogun Pages Zipify Pages Gem Pages Drop us a line if you have any questions about additional apps or special requests for landing page tracking. Preferred headless tech partner: Nacelle Our merchants looking for a complete headless Shopify solution often choose our tech partner Nacelle. Nacelle powers storefronts that stand out from the competition, offering headless website builds backed by a robust data stack. Focused on Progressive Web App (PWA) technology, they build lightning-fast, responsive sites for modern DTC brands. We've been working closely with Nacelle on tracking setup for some initial merchants (many brands you would recognize...) and are excited to now be able to offer headless tracking for any Nacelle customer. Read our shared ebook on going headless Explore our headless tracking demo Check out our NPM package for grabbing client IDs [or forward this to your developer!] Littledata's Nacelle tracking works automatically once you follow a few simple setup steps. Plus, the data can be sent to Segment, Google Analytics, or any connected data warehouse or reporting tool. [subscribe heading="Learn more about headless tracking" button_text="book a demo" button_link="https://www.littledata.io/app/get-free-trial"]
5 Still Effective Tactics to Boost Ecommerce Conversion Rate Optimization
Tracking Subscriptions in Shopify Checkout: Everything You Need to Know
The checkout is one of the most important steps in the ecommerce buying process for merchants. “Of course,” you might say, “it’s where I get paid!” But there’s a lot more to a good checkout strategy than simply completing transactions, especially if you sell products by subscription. Many modern DTC brands sell by subscription. Whether offering everyday items such as deodorant or custom monthly offerings such as fashion boxes or craft beverages, ecommerce businesses use a subscription model to increase customer lifetime value (LTV), referrals, and retention. Shopify noticed this trend and made some major moves this past year to push subscriptions into the native checkout. Most importantly, the change allows Shopify app developers to build tools with greater support for subscription business models. You probably have a lot of questions about what this means for your business, especially if you are focused on data-driven growth. We’re happy to announce that Littledata now offers plug-and-play solutions for tracking subscriptions in the native Shopify checkout, including for headless builds. Our ecommerce data platform works seamlessly with apps like ReCharge, Ordergroove, Smartrr, and Bold, and you can send the data to Segment, Google Analytics (GA), or any connected reporting tool. In this post, we’ll answer common questions about subscriptions in the native Shopify checkout — from what this really means (what is a “unified checkout” anyway?) to what data is available or “exposed” for your ecommerce marketing team. This post covers: I. Why Shopify moved to a unified checkout II. The state of subscription ecommerce III. Customer Lifetime Value (LTV) in the subscription industry IV. Tracking subscriptions in the Shopify checkout V. Subscription apps supported by Littledata I. Why Shopify moved to a unified checkout In the past, Shopify merchants who wanted to offer subscription products had to use third-party apps, such as ReCharge or Bold Subscriptions, where payment data can be stored and subscriptions managed. As a result, customers had to go through a different checkout process for subscriptions versus one-time orders. For example, customers would be redirected away from a Shopify store site to a separate ReCharge checkout, then return to the initial store they were on after completing payment. Last year, Shopify introduced new subscriptions APIs with the aim of creating a more seamless checkout experience for subscribers. Now, customers can start product subscriptions without leaving the store’s website, while the post-purchase management of the subscription is still handled by the subscription app. These new APIs bring a handful of additional benefits as well: Complete subscription data is stored by Shopify, allowing for improved reporting and analytics A faster, more streamlined checkout process for your customers More flexibility, so you can experiment with new subscription models Native checkout security provided by Shopify Shopify’s payment gateway does come with some limitations around product sales and region-based availability. If your store sells products that are outlawed in certain major markets (like cannabis) Shopify’s payment gateway will not offer support for your store. Likewise, if your store is not based in one of the countries Shopify lists under their umbrella of coverage, you’ll need to use another payment gateway to complete transactions. You can find more information on payment gateways to use by following the directions Shopify provides for stores outside their main regions of coverage. Note: Make sure to read both Shopify’s guide to setting up subscriptions and Littledata’s analytics setup guide for subscriptions in the Shopify checkout. There are several steps you need to take in each of a) Shopify’s admin, b) the subscription app you installed from the Shopify App Store, and c) Littledata in order to track everything correctly. II. The state of subscription ecommerce Not so long ago, ecommerce businesses focused on single transactions to grow their business. But the landscape has changed. Shoppers and brands are now focusing on relationship-driven ecommerce, and subscriptions are at the heart of the change. Many ecommerce customers now see the benefits of becoming a subscriber. It helps them stay ahead on the latest updates related to their favorite products and services. It also gives them flexibility to set up a steady flow of products when they want them, and the option to pause or swap subscriptions from a customer portal. Brands obviously see the value in loyal subscribers. Subscription ecommerce has never been growing so fast. Subscription payments app ReCharge analyzed data on more than 9,000 of their subscription customers and found an average of 90% growth in subscribers across all verticals, with an average LTV growth of 11%. [caption id="attachment_13180" align="aligncenter" width="735"] Source: ReCharge payments State of Subscription Commerce report (2021)[/caption] Growth was not limited to one specific vertical, either. In fact, Recharge’s report shows that nearly every vertical saw subscription merchant growth double in 2020. [caption id="attachment_13181" align="aligncenter" width="606"] Source: ReCharge payments State of Subscription Commerce report (2021)[/caption] Subscription ecommerce growth isn’t simply an effect of buyers worldwide shifting online due to the pandemic, though. A 2019 study from the Subscription Trade Association (SUBTA) found that the ecommerce subscription market experienced annual growth of 17.33% in the last five years. It also predicts three-quarters of DTC brands will offer subscriptions by 2023, while global ecommerce subscriptions will account for 18% of the total market share. Another recent survey by McKinsey showed that there is a 40% increase in consumers’ intent to spend online even after COVID. All this research concludes that the groundwork is set for continual growth in LTV and overall revenue for stores targeting subscription customers instead of maximizing one-time purchases. And those purchases often start with a discount. In a recent study, Bold Commerce found that discounts on subscriptions actually fuel monthly revenue growth, and smaller discounts (not too big and not too small) see the biggest return over time. With great growth comes greater competition The rush of new subscription ecommerce merchants in recent years is of course a huge benefit for buyers. It offers greater product diversity and more flexible buying options. But for sellers both old and new, the increased competition means they have to make smart decisions and truly know their audience to survive. The proven most efficient and powerful way to do that? A promotion strategy founded on accurate data. That’s where crucial metrics like return on ad spend (ROAS), average order value (AOV), and especially customer LTV come into play. III. Customer Lifetime Value (LTV) in the subscription industry Customer LTV, or the value a customer contributes to your business over their lifetime, is the holy grail of ecommerce metrics. This stat begins tracking when a new customer first makes a purchase and ends with the “moment of churn,” when they decide to no longer buy. Focusing on LTV can help you define clear marketing goals and sales strategies to reduce acquisition costs, improve retention, and encourage existing customers to spend more over their lifetime with your business. Subscription customers add more to your store’s overall LTV as they make repeat purchases and can be upsold to add more revenue. Leading ecommerce stores know this, and are enjoying higher LTV as a result. The same ReCharge study referenced earlier found stores activated between 2019 and 2020 realized an average LTV growth of 11%. [caption id="attachment_13182" align="aligncenter" width="485"] Source: ReCharge payments State of Subscription Commerce report (2021)[/caption] Successful stores know to focus on metrics like LTV because it affords them the ability to deeply understand the needs of their customers. To do this well, though, you need accurate data and high engagement with buyers. As for calculating LTV for subscription customers, it isn’t difficult when using a powerful data tool like Google Analytics. In fact, we have a guide you can follow to calculate customer lifetime value in Google Analytics. If you’re looking for a true deep dive into LTV that covers calculation methods, multiple improvement strategies, and roadmaps for Shopify subscription success, jump into our ultimate Shopify guide to LTV tracking. III. Tracking subscriptions in the Shopify checkout Getting accurate data about your customers’ behaviour is especially difficult for subscription commerce. If you’re using Shopify’s default GA tracking, a significant percentage of your orders might be missing. This can lead you to form an incomplete picture of your marketing attribution and sales performance, and a lesser understanding of your customer’s behaviour. After sampling larger merchants on Shopify, we discovered that on average, for every 10,000 orders processed, 1,200 are missing in GA. However, these discrepancies look even worse for recurring orders, with the percentage of orders tracked ranging between 9% and 70%. This happens because recurring orders are processed without the customer interacting with your online store. Fortunately, there is a fix for this issue. Littledata’s Shopify app can repair these tracking disparities automatically upon install. It works by first adding a data layer onto your website containing all Enhanced Ecommerce events. Then, it adds a tracking script to capture each event as it happens. Finally, using robust server-side tracking, the app grabs all transactions and ensures 100% accurate ecommerce data. That allows you to see truly meaningful data that eliminates the worry of making incorrect decisions based on faulty numbers, while giving you the power to make your marketing dollars work better for your store. [tip]Try Littledata’s script on your store free for 30 days. Get a data audit of your current metrics and see the difference you could be missing on marketing attribution.[/tip] IV. Subscription apps supported by Littledata Stores using subscription apps to manage recurring orders set up in the Shopify checkout can track their recurring orders using Littledata’s Google Analytics and Segment apps in the Shopify app store. In fact, Littledata works automatically with all subscription apps used by Shopify stores. Here are a few of the most popular subscription apps to consider using for your store. ReCharge ReCharge is a subscription management app designed to let your store offer subscription products with a few clicks. In addition, it helps increase LTV by allowing customers to manage their own subscriptions while setting you up with revenue-boosting tools like upsells, SMS and email notifications, and actionable subscription insights. Bold Subscriptions Bold Subscriptions aims to help you establish predictable recurring revenue via better customer loyalty using customizable subscription programs. The app is compatible with multiple payment gateways, allows API customization, and features checkout integrations that further enhance your customizability, and in turn, the value you can provide to customers. Ordergroove Ordergroove is a tool to help you grow average order value (AOV) and maximize subscriber enrollment through promotions, retention rewards, and the ability to craft a custom subscriber experience. It’s a popular solution for larger brands and offers a range of integrations to help you scale. Smartrr Smartrr’s subscription ecommerce app offers a recurring revenue engine designed to help you offer curated subscriptions to members. That includes through methods like allowing subscribers to manage their recurring orders, gifting options, upsell addons, and even product swaps that increase consumer satisfaction. What’s next? Shopify’s new unified checkout has bolstered app developers to create more innovative products. Those apps in turn help you target subscriptions in your store checkout and use enhanced ecommerce metrics to get a full, accurate picture of your subscriber audience, then customize your checkout and promotion methods to reach your most valuable audience. But how can you scale a subscription store without accurate data? That’s where Littledata comes in. [tip]Take the first step in realizing the true potential of your ecommerce store and get accurate data from Littledata free in our 30-day trial.[/tip]
Segment Recipe: Create Facebook lookalike audiences of your top-spending customers
The promotional power of Facebook Ads and Instagram Ads is no secret. All of our customers use them. Smart ecommerce marketers, however, know that beyond their wide reach, the true value of these ads comes in using them to reach specific buyer personas. Targeting those who are most likely to make a purchase is a great way to boost sales, but how do you reach that audience over time? In short: How do you find more customers like your highest LTV customers? Littledata has worked with top DTC brands using Shopify and Segment, such as Rothy's and Sheertex, to enable data that lets you do exactly that. One key way is lookalike audiences. To help you dive into utilizing these audiences for your store, we've created an analytics recipe along with our partner Segment. The recipe is made to help you stop wasting time building audiences manually while still allowing you to reach your highest-value customers — the ones who are ready to buy and more likely to make bigger purchases over time. It explains step by step how to continuously target a similar audience to your top-spenders, so you'll start getting your ads in front of eager potential buyers. Lookalike audiences such as these are a staple in successful ecommerce brands' promotion strategies, as they widen your audience while ensuring you get the most value out of the advertising dollars you spend. Read the full post on Segment's blog to learn how you can start utilizing this recipe in your Facebook Ad strategy. We look at how to: Create an audience in Segment Personas of highest spending customers Automatically sync that audience with Facebook Ads Create a lookalike audience in Facebook Ads to find more high-value customers If you've wondered how to use rule-based audiences to increase revenue, this is the recipe for you. Do you know how accurate your ecommerce reporting is? Get a clearer picture with a full data audit from Littledata as part of our 30 day free trial to start owning your data and make decisions off truly accurate data. [subscribe]
5 Cool Ways to Convert More with Psychology
Nope, we’re not talking about mind control here or any other Batman-villain-style plots. He did have some sick outfits, though. We won’t be talking about the “psychological tricks” that have gained a bad rep in marketing, either. Using lessons from psychology in your promotion is more about being creative with the sales process — and it can bring fantastic results. If you show truthful information, use data to present customers with relevant products, add gifts to purchases, or lower prices, you create a hassle-free, win-win situation for you and them. The techniques described here can impact the way customers think about their purchase and help them decide in your favor. TL;DR Use the price anchoring technique to improve price perception Curb decision fatigue with data-based product recommendations Create FOMO and feelings of exclusiveness with limited-time and limited-quantity offers Combine bestsellers and frequently-bought-together items to create good bundles and upsells Everybody loves free stuff Now, let’s dive into five ways you can take lessons from psychology and apply them to your promotion. #1 Price Anchoring: put price in perspective People most often determine whether a product is expensive or cheap by comparing it to something else. That’s exactly what price anchoring does — it gives customers a main price (anchor price) they can reference to decide if they like the specific deal you’re offering. You’ll often see this technique used to promote sales — i.e. on a sign saying “$125 NOW $90,” that $125 is the anchor price. Use your anchor price in pricing tiers Another way to use price anchoring to increase sales is to show pricing tiers. If you have differently-priced versions of your product, you can list them side by side on your pricing page. That way, your customers can easily evaluate prices and features without switching between tabs or pages. You can see this full page at Littledata.io/plans Keep in mind: It’s best to set the anchor price as the most expensive option. That way, customers will opt for the cheaper offer — the one you originally intended to increase sales for. Your goal might be to boost sales on cheaper products despite being lower value than the more expensive option (a “you get what you pay for” sort of thing). In that case, people will choose the more expensive one because the perceived value is greater. Compare your product with competitors Before buying, customers will usually investigate what else is on the table; there’s no way to prevent that. So, why not use that to your advantage? Take a good look at a competitor’s offer and adjust yours accordingly to make a better deal whenever possible. Create a dedicated comparison page that shows customers what the benefits and features of your product or service look like side by side with your competition. These comparison pages are usually among the resources customers search for most, making them a great opportunity to improve your website’s ranking in search engine results. Be careful not to focus solely on the financial aspect; show feature differences, best use cases for each product, and their actual value. #2 Eliminate indecisiveness When facing a difficult decision, some people (including yours truly) just… run away. You guess if I'm exaggerating or not. What causes the inability to decide? The main culprits could be: Information overload Lack of information Fearing the consequences of the wrong choice To prevent this, revert to making comparisons and highlighting the exact purpose of items, as suggested above. Another way to help decision-making is to draw attention to specific products with social proof. Listing featured products, highlighting customer reviews, and naming items of the day/week/month are all great ways to suggest other buyers loved your product and help the customer in their buying decision. Utilizing a Recent Sales Notification system adds an element of rush to the buyer's decision. Speaking of... buying behavior analysis is a must! Data capturing capabilities are powerful and can be used to make changes to your store that influence purchase decisions. To do so ethically, use legally obtained data to learn customer preferences and design solutions that fit their needs like a glove. Using this data, you can make tweaks to your store’s appearance — like selecting items most likely to be purchased by certain people and showing them in “Recently Viewed” and “Related Items” sections. [tip]Get inspiration to optimize your store’s design from five successful DTC brands succeeding with Shopify Plus.[/tip] #3 Fear of Missing Out (FOMO) and exclusivity Scarcity marketing relies on people’s fear that items they desire won’t be as cheap (or available at all) if they don’t hurry and buy them while the offer lasts. And it works. It’s science, baby! Scarce items are perceived as more valuable and have an aura of exclusiveness. There’s something about having what few other people have that gets people going — think designer handbags or rare sneakers. There are plenty of well-known ways to create FOMO and make products seem more exclusive: Limited-time offers like “buy X get Y” or free shipping Built-in timers indicating the amount of time left to act; a Cart Reserved Timer can speed things up even more and is incredibly useful for items that sell like hotcakes Low stock alerts — i.e. “Selling out fast” or “only X more left” Don’t rely solely on scarcity tactics, though, as they have limits. Always continue to improve your products and build lasting relationships with customers. Remember to show truthful information only. It’s the right thing to do, and Shopify will penalize the store owners caught embellishing or outright lying about products. #4 Create awesome bundles and upsells Delve into customers’ minds and find out their desires. Or, try a method that actually works and learn from data; it’s simple and feels just as powerful! Here are some foolproof bundle and upsell ideas: Offer bundles of products that are often bought together Combine store-wide best-sellers Offer luxurious and expensive minis Sephora creates great sets for people who are too afraid to commit, so they can try multiple high-end brands without breaking the bank. (Screenshot: sephora.com) Offer an add-on gift-wrapping service to increase the average order value during the holiday season Allow customers to purchase a money-back guarantee or a warranty for items that rarely require customer complaints or returns #5 BOGO deals BOGOs can be summed up with three words: “Hey, free stuff!” They come in handy when some items in stock just refuse to go away, but you need them to, and fast. An excellent example for using BOGO would be as a holiday strategy: “buy one, and we’ll ship the other one as a gift to your mom/pop/friend/loved one.” Then you can charge for shipping and gift wrapping, and the average cart value will grow as well. While we’re on freebies, never forget the power of free shipping! Setting a free shipping threshold is another easy way to increase customer spending without reinventing the wheel. Typically shoppers would rather spend more to get perks like free shipping than pay extra fees which can feel like more spending for little return. Bottom line Your own store’s data reveals what customers want, when they want it, and how they choose to get it. Having a full, accurate picture of that data gives you critical insight into your buyers’ psychology. Using psychology-based marketing means learning about people so you can help them, not exploit them. Customers today are more informed and aware of sneaky tactics than ever before. So, the best course of action is to stay transparent and provide excellent service and products they’ll love. The tactics above tick all the boxes: they make customers happy and bring extra profit. This is a guest post from Jordie Black. Jordie is a content marketer and strategist specializing in B2B, SaaS, and Influencer Marketing. Jordie is currently building her first DTC e-commerce business.
Lunch with Littledata: Why a headless build is right for your store with Nacelle
How Littledata’s product sprints fuel innovation
Littledata thrives on innovation. As a top data connector with a complex backend and seamless frontend, we're always looking for ways to innovate faster and smarter. To fuel that innovation, we use focused development sprints to ship high-quality features and updates. Over the years, we’ve learned that: 1) having clear objectives, 2) removing unknowns, and 3) delivering value in smaller chunks is key to an impactful product development process. That's why we start projects by first clarifying our goals, then discussing the scope of features and their impact. That way, we can break them down into meaningful chunks and prioritize them for implementation. Delivering value in small chunks is key to impactful product development We arrived at this process after several trials and errors over many arduous months. Our north star metric all along has been sprint velocity. We measure that metric using total story points, which focus on a task’s worth of value delivered to customers rather than working time spent. We believe teams that most often deliver value to their customers have a higher chance of success in the long run. All that said, we recognize every team dynamic is different. Each team should test what works best for them. Littledata’s process — laid out below — helped us double our velocity per developer, per sprint. We highly recommend it to any product team that wants to try it out. To show you why our process works, let’s dive deeper into it. Choosing Goals and Objectives How to set Annual and Quarterly OKRs (Objectives and Key Results) We begin each year by stating our overall goals and objectives using the OKR framework. These annual OKRs are then broken down into quarterly OKRs and translated to fit each team. Using Team Initiatives / Epics Once each team clearly understands their OKRs for the quarter, they break them down into epics (or initiatives). Epics are bodies of work that, when completed, push the team closer to achieving their goals for the quarter. For example, in one quarter, our product team identified trial conversion rate as a key metric that, if improved, could help Littledata move closer to its business goals. To boost the trial conversion rate, the team used first principles thinking, user research and feedback, and user experimentation to help identify root issues that prevented users from completing the trial. Littledata breaks goals down into epics, which help us work together on clear initiatives Using that data, the team came up with several epics like creating a “getting started” campaign, improving the onboarding experience for users, and launching a feature to educate users about the product. Each epic contained clearly defined user stories (specific tasks) to help resolve the root issues identified. Epics breakdown We want to be able to start delivering value to our users as soon as we can. So, once we have a clear understanding of our target epics (or initiatives) for a quarter, we break them down further into valuable, independently deployable iterations: 1HOUR iteration 1DAY iteration 1SPRINT iteration FINAL iteration Each of these iterations is deployable on its own and adds value to our customers. Work starts using the smallest possible version of the epic that we could build and deploy while still adding value to users. We continue building to reach the final iteration: a fully-featured spec that has all the bells and whistles we’d initially planned for. Breaking an epic down into these iterations means that: We start adding value to our users sooner than later. Instead of waiting for a couple of sprints, we start delivering value in hours (literally.) We can measure impact a lot earlier. This helps keep us agile, letting us shift strategies if our proposed solution or the identified problem is not aligned with our users' needs. We increase perceived velocity. This helps keep team spirits and momentum high. We try to stack a mix of epics in every sprint to continue delivering value to customers across multiple fronts. The full Littledata sprint process Our sprint development cycle begins well before an actual sprint starts — ideally about two sprints in advance. We hold a few planning and estimation sessions beforehand to make sure we’ve clarified all the unknowns and aligned the entire team on the deliverables for the sprint. Then, it’s on to the epic planning. Planning epics We plan epics for a couple of sprints at a time. Each Littledata sprint lasts two weeks, which we’ve found to be short enough to accurately forecast the roadmap, yet long enough to enable us to take on larger features. For each epic planning discussion, we involve the Product Manager (PM), Engineering Manager (EM), and Technical Program Manager (TPM). Writing specs After we’ve aligned the desired outcomes for the PM, EM, and TPM for each epic and prioritised them into the sprint, the TPM works with the engineering team to break the epic down into smaller tickets that make sense from an implementation perspective. Estimating tasks Our EM works with the engineering team on a daily basis to discuss tickets specified by the TPM and estimate their complexity using story points (and following industry best practices.) Although complexity estimation is arbitrary and differs from team to team, as long as the team remains consistent in its estimations, we believe it adds a lot of objectivity to estimating sprint velocity. This further helps us plan each sprint, know the team capacity per developer per sprint, and aids us in our hiring decisions. Pre-sprint planning The PM, EM, and TPM meet again prior to the sprint’s start to discuss the now estimated epics. They negotiate and prioritize work based on the team’s capacity, as well as the value added to our customers and the business. This is where we lock in the work for an upcoming sprint. The entire product team connects at the start of each sprint to align on the epics and their desired outcomes. Ideally, this is more of an alignment meeting. By this point, everyone on the team will have gone through specs and will be quite familiar with the expectations. There should be no unknowns at this stage; the entire focus should be on execution. The sprint At Littledata, we follow an agile, two-week sprint model. We use Jira tickets to track progress, with each ticket flowing through the following stages: TODO: Prioritized ticket, assigned to a particular developer IN PROGRESS: The developer has picked up the ticket and is working on it. Ideally, there shouldn't be more than one ticket per developer in this column at any given point in time. CODE REVIEW: The developer has moved the ticket for peer review to make sure there aren’t any code quality issues. QA: After a ticket passes code review, our QA analyst makes sure the implementation matches the acceptance criteria specified on the ticket. DEPLOYMENT: If there are no dependencies, the ticket gets deployed to production after it passes QA. We try to deploy to production several times in a given sprint. Sprint review When we reach the end of each sprint, we wrap up with a review meeting. We talk through the sprint velocity, discuss what the blockers were, and brainstorm how we can improve in the next sprint. Many key Littledata features and product innovations have come from this sprint process, with sprint reviews feeding directly back into sprint planning for the next cycle. Those innovations include: A complete refresh of our popular ecommerce analytics audit checks Innovation in how Littledata handles userID for Shopify and Segment New transaction monitoring to help our own dev team as well as our customers, such as the uptime and status monitor Rapid iteration around additional app integrations, such as Zipify and Shogun landing page tracking And so much more! Indeed, the cycle continues to work on and on, from the next sprint to the one after... Try our process for yourself Has our product development process piqued your interest? Could you see yourself thriving in a collaborative work environment as part of a growing team dedicated to making a difference in customers’ lives? At Littledata we're building the top ecommerce data platform on the planet, with customers — and teammates — around the world. Take a look at our open positions, and don't forget to follow us on Instagram and Twitter. Plus, if you're using development sprints in an innovative way, let us know and you might even get featured on the blog!
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