Does Littledata work with Google Tag Manager?
How Littledata handles User ID for Shopify and Segment
Is Segment a good customer data platform (CDP) for ecommerce? We hear that question a lot at Littledata, and are always happy to chat about the modern data stack. But the reality is that you should be asking more detailed questions: will your CDP be able to handle both anonymous browsers ("visitors") and customers ("users")? Will it enable both analysis and marketing automation? Will you need an entirely different stack to support your data warehouse? Our DTC ecommerce customers have found Segment to be a powerful solution because it offers a unified approach to customer data. As long as it's set up correctly, that is. Four options for user identity There are many different approaches to user identity, but the most important thing is to be consistent. Make sure the identifier you choose works with your current data destinations and those you know you plan to implement in the future. In Segment, every identify call must have a User ID or an Anonymous ID. Littledata's Shopify source for Segment is an easy way to ensure accurate ecommerce data, rather than building and maintaining the schema yourself to match Segment's detailed ecommerce spec. Our scope includes sales, marketing, and customer data, captured from a combination of client-side and server-side tracking. We agree with Segment's best practices in identifying users, including the use of static IDs whenever possible. To support a broader range of use cases, our app lets you choose which of the following fields you want to send as the userId for known customers: Shopify customer ID (default) – Recommended if you have a simple Shopify setup with minimal integrations. Hashed email – The MD5 email hash is useful if you have other marketing platforms sending traffic where you know the email of the visitor (e.g. email marketing like Bronto or Marketo), but not their Shopify customer ID. Email – Recommended when other platforms use the email and can’t hash it, and you are comfortable with the privacy implications. None (no identifier) – Recommended only if user identity is already handled by your Segment implementation and you only need the extra events powered by Littledata’s Shopify source. Learn more about what you can track with our Segment connection. Since we started offering identifier options beyond Shopify customer ID earlier this quarter, it's been interesting to see the uptake. Perhaps most surprising is that it's not just larger stores on Littledata Plus who are using alternative unique IDs. There are already merchants on our Standard and Pro plans using the option as well. [note]For merchants using Segment Personas, Littledata also sends shopify_customer_id as an External ID for advanced matching[/note] What is your approach to user identity? Are you planning for the future? Let us know in the comments or on Twitter.
Learn more about your ecommerce customers' behavior with advanced checkout funnel analysis [VIDEO]
Ecommerce analytics are tricky to begin with. Add tracking your subscription services on top of that and you’re dealing with a whole other animal! Do you use Google Analytics to report on your Shopify store’s one-off purchases AND recurring orders? Check out our video on Littledata’s advanced checkout funnel analysis to find out how we’ve made subscription analytics easy. https://youtu.be/EU3Cj2Z6AII Traditional ecommerce stores typically track one checkout funnel per property. The benefit is that this makes it easy to analyze the drop-off at each point. But, if you have multiple checkouts to track one-time orders and subscription purchases, important insights might go unnoticed when GA aggregates your data. Littledata automatically differentiates between your checkout funnels to show whether they’re subscription or one-time purchases. That way you know exactly what each funnel’s checkout completion rate is for different order types. This gives you the power to tailor your remarketing strategies for specific checkouts or products, further increasing your ads’ relevance to possible customers. Note: Do you trust your subscription tracking? Get accurate subscription tracking with the ultimate ReCharge guide for Shopify Littledata integrates with the top subscription ecommerce apps—including ReCharge Payments, Bold Commerce, and Ordergroove—and automatically tracks both Shopify and subscription checkouts. “Littledata is a must-have if you’re running Recharge and Shopify; it helped us figure out what channels were getting us our future subscribers and what helped convert them.” —Better Way Health To access your checkout reports in Google Analytics, go to your ecommerce analysis reports. From there, you can view your checkout behavior reports to get a general understanding of when users are dropping off throughout the checkout process. Find out how to segment your data between Shopify and subscription checkouts to measure the exact drop-off rate at each stage of the checkout process for each checkout funnel in our latest learning video. Capture data at every turn In addition to tracking your checkout funnel completion rates for subscription checkouts, Littledata tracks crucial sales and marketing metrics, so you can: Get accurate marketing attribution data for subscription revenue, including first-time payments and recurring chargesUse custom dimensions to measure customer lifetime value (LTV)Track performance by payment source, subscription plan type, and product categoryView complete sales and marketing data with combined server-side and client-side trackingMake better, informed decisions for your Shopify store Resources Watch a quick demo video on how Littledata worksFind out how to calculate LTV with Google AnalyticsDownload the ultimate guide to subscription trackingCheck out our ReCharge FAQSubscribe to our YouTube Channel for more videos about analytics
Why work at Littledata?
Many of us have a similar idea when picturing the perfect job. A role with opportunities to grow, a stimulating work environment, caring coworkers and, of course, a reliable income that we feel meets our value. Finding that ideal fit, however, isn’t easy. That’s true for companies looking to hire the perfect candidate, as well. In the end, it comes down to a focus on company culture. One where employees lift each other up. Where each team member feels valued and sees how their work adds to the company’s overall goals. Our team at Littledata spans across the globe, but we’re still a very tight-knit group. We believe that comes from our commitment to bringing on team members who fit their role both technically and culturally. Finding that perfect fit is challenging when we’re competing against industry giants for our top candidates. There’s no denying that there are lots of perks to working at a big tech company like Apple or Google. But working for a successful analytics startup like Littledata has many special perks of its own. Not least of which is that everyone’s voice is heard, and every team member contributes key ideas to our product growth and partner community. "We work toward shared goals at Littledata, and that's been a key to both customer success and employee happiness," says Littledata co-founder Ari Messer, who leads our remote US team. Any one of our employees could have just as easily joined a bigger company, but chose Littledata instead. And they choose Littledata, again and again, every day. We asked our team why they decided to work at Littledata and what they love most about being a part of our family. Here are some of the top reasons they gave us, in their own words. If Littledata sounds like a team you’d like to be a part of, we want to hear from you. We list our open opportunities on our careers page. Don’t see the right fit? Stay in touch for future roles; we're scaling quickly and new job opportunities pop up almost weekly. Great work begins with great values Our core company values have remained the same since launch and continue to guide our proverbial ship. They weave throughout our day-to-day work, team offsite trips and design sprints, and continue to play a massive role in our success. Littledata founder and CEO Edward Upton defined these values early on, and they remain an essential part of our work culture. 1) New technologies Littledata is a next-gen data connector. We develop super-fast analytics apps using the latest web services and tools. Our apps empower top direct-to-consumer (DTC) brands to use modern data stacks without sacrificing speed or flexibility. 2) Happy people We believe a happy staff translates into happy customers. We employ happy and productive people with flexible working hours, engaged learning plans, and fun outside of work. 3) Collaboration We believe that true innovation comes from an environment marked by challenge, curiosity, and communication. We emphasize cross-team collaboration and share Key Performance Indicators (KPIs) and Objectives and Key Results (OKRs) across the company. Working remotely, together Littledata has had a remote, distributed team since the beginning. When COVID-19 hit, companies all over the world grappled with the sudden transition to working outside the same office. Our team didn’t skip a beat because we’ve been working this way for years. Most importantly, working remotely allows us to be flexible in more ways than one. We encourage our team to work where they want, when they want, and how they want. In fact, we've found that when done right, remote work is more productive. Work where you want Getting the most out of your work comes down to your own productivity and routines. We encourage our team to work wherever they feel the most productive that day—whether that be at home, a coffee shop, a co-working space or a more traditional office. Work when you want Many of us have families to take care of, errands to run, and outside interests to explore. Our team members live dynamic lives. That’s part of what makes them so amazing to be around—inside and outside of the workplace. Work shouldn’t consume your life or dictate how you live each day. Aside from scheduled meetings, at Littledata your time is yours. We encourage our team to work at their own pace, meaning that they can take back ownership of their day-to-day routines. Time is our most valuable resource, it’s best we spend it wisely. Our team works when they feel most productive—which doesn’t have to be from 9 to 5. Work how you want Keeping a strong work-life balance is essential at Littledata. That’s why our remote work culture only helps to promote finding an equilibrium between your work and everything else outside of it. We encourage our team members to find a balance between their work responsibilities and their responsibilities outside of the “office.” We know that life happens, so we give our team the freedom to be present in their personal lives. That’s how we build happy employees empowered to do their best work. Being remote also means that we can hire the best talent from around the world, not just one specific area. Littledata’s international team has members across the U.K., Europe, and the U.S., with hubs in Nashville, New York City, London, Cluj, and Bucharest (plus more cities coming soon!). Completely remote work isn’t for everyone, though. Some people do work best in an office setting with a fixed, "regular" schedule. That’s why we support co-working spaces and collaborative offices as needed. Never stop learning Each month, our employees receive dedicated “learning days” to further develop their skills. This time helps us explore our areas of interest while building up the skills we need to master our work. Those learning days have included all kinds of things: Online courses in Google Analytics, Google Tag Manager, data visualization, data science, and more Project-based learning around new programming languages and tools like Netlify Speaking and participation at conferences such as Google I/O, Shopify Unite and Measurecamp (we're looking forward to the return of in-person events!) By investing in our team’s professional development and interests, we’re building the best brand ambassadors Littledata could ask for, who are also experts in their craft. Build something great All of our greatest ideas, updates, and designs are the product of collaboration. Our team members may call different countries home, but we are constantly working together online. The Littledata development team builds the backbone of our data platform, and their work helps power hundreds of ecommerce businesses around the world. Their code ensures the successful delivery of hundreds of millions of essential tracking events to our customers' analytics tools and data warehouses. Through collaboration with our marketing team, customer support team, and operations team, the dev team is able to build off shared ideas to develop cohesive, creative, and innovative solutions. The support, insights, and feedback they receive help them mold Littledata's analytics platform into the best version it can be. Annual offsite meetings It’s important for us to find time each year to put work aside and connect as a team. Our global team gathers annually for an offsite retreat—typically held in Europe. This provides us a great opportunity to collaborate, catch up, and relax alongside all of our team members. During week-long offsites we find a balance between work and leisure, taking advantage of the great opportunity to collaborate and bond as a team. Throughout the week, we run a design sprint. The process helps to spark innovation and align members under a shared vision. This gives us the chance to work in cross-functional teams, and gain a better understanding of the goals of each department. Some of Littledata’s greatest advancements were the result of design sprints, and they've helped place Littledata as the future of ecommerce analytics tools. Work hard, play hard! We find plenty of time to have fun during our offsites, exploring the city we’re visiting, lounging on the beach, and most definitely enjoying the amazing company of our co-workers. And it doesn't stop there. During monthly "sprint retrospectives," every team member has a chance to highlight what's been working best and also suggest improvements to company processes, whether that's about how we make feature requests or how we might improve cross-team communications. At the end of each quarter, we also take time as a company to reflect on the goals we set for the past 3 months, assess our performance, and create specific OKRs for where we want to be and what we want to achieve in the next quarter. Each of these OKRs aligns individual departments toward our overall company objective, guiding our team under common goals and uniting our vision for the future. Join the Littledata family While the greatest resource we can give to our employees may very well be time (and freedom over their time), our greatest resource is our team. Our product would be nothing without the people behind it that shape it every day. Our team is small but mighty, with each member playing an integral part in Littledata’s success. They are the backbone of our product, between our incredible support team to our skillful engineers, and everyone in between. Together we’re able to build a product that each and every one of us is proud to stand behind. Since our team collaborates from across the world, it’s even more important that we invest our time in building inter-team relationships. Something we value most about Littledata is our camaraderie; we support each other in all of our professional and personal endeavors. “We always blame the problem, not the person.” —David Pascu, Head of Client Services Here at Littledata, we’re surrounded by some of the most uplifting people, who encourage us to work harder every day for the betterment of our team as a whole. As David so wisely put it: “We blame the problem, not the person.” We investigate those problems head-on in our design sprints, often solving big problems in a short time. Some days that’s a product improvement for the install flow of a particular Shopify analytics connection. Other days, we’re crafting the perfect answer to the question “Why Littledata?” or prototyping a tool that visualizes analytics throughputs more succinctly. (Yes, those were real design sprint projects!) Our can-do attitude makes any challenge seem possible. Our bond as a team makes working together toward solutions and innovation an exciting task. Work as a team, win as a team As a startup, we understand that each one of our employees is taking a leap of faith in joining our team. That’s also part of what makes our team so strong. Every member of the Littledata team believes in the work that they do and the service they provide. While joining a startup can be a risky decision, great risks yield great rewards. Our team is 100% to thank for Littledata’s growth and success over the years. We’re the first to give thanks where it is due; when we hit milestones and reach our goals each quarter and annually, our team are the first ones rewarded. One of the greatest benefits of being part of a small team like Littledata is the lack of bureaucracy that many encounter in larger corporations. Each of our team members has what we like to call ‘flexible’ roles—and let’s be clear, flexible does not mean multiple. By ‘flexible’ we mean that we encourage our employees to explore other fields that interest them, but might be out of their "job description." Allowing our team to follow their passions, interests, and work in areas that they do best in creates a recipe for success. So, are you in? We’re always looking for motivated and talented team members to become a part of the Littledata family. If you want to be a part of building a market-leading analytics tool while also shaping a truly special team culture, we want to hear from you. Not passionate about ecommerce analytics yet? Join our team and you will be soon :) Check our careers page for the roles we have open. If you don’t see the perfect fit, reach out to us and share your skills and experience. Any of our team members would be happy to hear from you and see if we can make a match.
Introducing Littledata Plus plans for Shopify and Shopify Plus
As Shopify has continued to scale its Shopify Plus plans, Littledata has developed both technology and services to enable customer success. Today, we're pleased to announce new Littledata Plus plans to support modern data stacks for larger direct-to-consumer (DTC) brands. Our enterprise plans have been around in various guises since the beginning. But clients’ data needs—and the DTC market overall—have continued to evolve, from more sophisticated lifetime value analysis to connecting Shopify with data warehouses like Redshift and BigQuery. The coronavirus pandemic also forced many businesses that had been planning to move online to do so sooner than expected. Traditional consumer packaged goods companies (CPGs) needed to try out DTC and ecommerce subscription models. And, to be blunt, they needed to speed up plans for finding ways to compete with Amazon. With more known brands moving to Shopify and BigCommerce, core data needs have skyrocketed. In fact, without Littledata, 12 orders still go missing in Google Analytics for every 100 orders in Shopify! It seems ecommerce in general is finally waking up to the fact that the key to growth is focusing on the right KPIs with accurate data to support them. The renewed focus on data has extended beyond PPC campaigns to channels like social and email marketing, as well. As merchants get "back to the basics", we've also started to see less customization and an increased focus on data accuracy and throughput. That goes for both our Google Analytics and Segment data destinations. All this illustrates what has been our outlook from the beginning: nothing is more important than data accuracy. So we're excited to now be opening up Littledata Plus plans to all DTC brands. Whether you're a recently funded scale-up with a headless Shopify site or you've been on Shopify Plus since the beginning. Options for Littledata Plus plans We have long optimized Littledata for Shopify Plus, from higher service level agreements and throughput metrics to multi-currency tracking for brands with multiple country stores (e.g. see how we handle order names). Our team has experimented with Littledata Plus features, tracking plans, and account management levels to ensure that our tech and support are as effective as possible. We've worked closely with top Shopify brands like Rothy's, Boll & Branch, and Craft Gin Club, as well as agency and tech partners supporting those brands to fine-tune our solutions. We don’t just want to be proactive, we want to be useful. "Don’t mistake the forest for the trees. Our ecommerce customers know that accurate data is essential for real growth." Littledata Plus plans are a must-have for any merchant processing over 10,000 orders per month (including recurring orders or subscriptions). They're also now available to anyone serious about data-driven growth. We now offer two distinct paths within the Littledata Plus journey: Plus: Plus plans give you access to a dedicated account manager to help with onboarding and data audits, and include tracking for any number of country stores. Enterprise Plus: Our higher-tier Enterprise Plus plans allow unlimited data thresholds, and can also include a custom tracking plan, solution engineering, analytics training, or other options to support your in-house team. [subscribe subscribe heading="Learn more about Littledata Plus" button_text="book a demo" button_link="https://www.littledata.io/app/demo"] All Littledata Plus plans include essentials like in-depth data audits and dedicated account management. But with Enterprise Plus, you get a deeper experience, more support time, and a custom tracking plan. We built Littledata around smart connections. A big advantage of using our data connectors is that we keep those connections up to date for you with an in-depth knowledge of APIs, webhooks, properties, and events. For example, our connections now support headless Shopify setups and subscriptions in the Shopify checkout—without any additional coding needed on your website. "All Littledata Plus plans include essentials like in-depth data audits and dedicated account management." Recent updates to our Plus plans include: Advanced headless setup support Unique identifiers Historic data import for Segment users For Google Analytics users, we now offer analytics training and a Measurement Protocol endpoint to make it easy to get complete ecommerce data into Google BigQuery. That said, we have many happy Littledata Plus customers who simply want to ensure accurate Shopify and ReCharge data in Google Analytics. Can you risk making decisions based on bad data? Put another way: how much faster could you scale if your sales and marketing data were accurate, reliable, robust, and complete? Whatever your data goals, Littledata Plus is here to help. Book a demo today and let's start the conversation.
Two ways to calculate customer lifetime value for ecommerce using Google Analytics data
Many of our customers come to us with a similar question: "how do I measure ecommerce lifetime value (LTV)?" The latest episode in our Learning Videos series shows you how to do just that for both your one-off purchasers and subscription customers. Our step-by-step tutorial covers two methods of calculating customer LTV using your Google Analytics (GA) data. You'll get to know Littledata’s custom dimensions in GA and learn how to visualize your calculations in Google Data Studio. During installation, Littledata automatically creates several custom dimensions in your connected Google Analytics property. These custom dimensions include: Lifetime Revenue, the sum total a customer has spent in your Shopify store (including one-time purchases and subscription orders) Shopify Customer ID, the unique identifier Shopify assigns to each customer Last Transaction Date Payment Gateway Purchase Count They offer better data to help you understand your customers' buying behavior, then calculate and visualize their LTV. To kick things off, you'll first need to export your data from GA to Google Sheets or another spreadsheet tool via CSV. Once you’ve enabled the GA add-on in Google Sheets, you're ready to get started. Method 1: Calculate LTV by Lifetime Revenue, Shopify Customer ID, and Transaction Count In the first method of calculating lifetime value, we’ll use Transactions as the metric. The dimensions we'll use—Shopify Customer ID and Lifetime Revenue—correspond with ga:dimension5 and ga:dimension3, respectively. Use the image below as a guide to set up your report: Next, set your Metrics Reference as Transactions and your Dimensions Reference as Custom Dimensions. After you run the report, Google Sheets should look something like this: Finally, use Google Sheets' built-in functions to calculate the average or median LTV of your customers. Method 2: Calculate LTV by Source/Medium, Transaction ID, Shopify Customer ID, and Transaction Revenue This second LTV calculation method helps you track which marketing channels bring in your most valuable customers: the ones who spend the most over time. In this method, use Transaction Revenue as the metric and Source/Medium, Transaction ID, and Shopify Customer ID as the metrics. These correspond with ga:sourceMedium, ga:transactionId, and ga:dimension1 respectively. This method requires the widest date range possible to capture the most transactional data possible—preferably since you started using Littledata. Before running the report, your Google Sheet should appear as follows: After exporting your data, your result will look like this—a list of transactions with source/medium and revenue data: Next, select all the data in your report to create a pivot table, aggregating by source/medium per customer. The result will reveal the total revenue per customer, per source. After completing the pivot table, you're ready to visualize your data in Data Studio. Build Reports in Google Data Studio Google Data Studio is one of our recommended reporting tools for ecommerce sites. Why? Because it's free, powerful, and works really well with Google Analytics. The first step in visualizing your data is to import your data into Google Data Studio by setting Google Sheets as your source. To do this, select your Google Sheets file followed by the pivot table you created in the previous method, and add it to your report in Google Data Studio. Change the data source by setting the aggregation to median so results yield the median lifetime revenue per traffic source. Your report dimension should be set to ga:sourceMedium and your metrics should be set to ga:transactionrevenue and ga:dimension1. Modify Shopify Customer ID from sum to count distinct to reveal the total unique customer IDs, which we'll use to sort our data. Sort by Shopify Customer ID to see the traffic source that brings the most customers to your site. The resulting report shows you the median lifetime revenue per traffic source, sorted by the total customers per source. References Quick Tips for Subscription Stores Using Custom Dimensions in GA 3 Deep Dives into Customer Lifetime Value for Ecommerce Sites LTV from GA vs LTV provided by Littledata How to Calculate Customer Lifetime Value in GA for Shopify Stores Custom Dimensions for Calculating Customer Lifetime Value Subscription Analytics Does Littledata work with my ecommerce reporting tool?
Why doesn't Shopify analytics match Google Analytics? [ebook]
Shopify analytics is fine for what it is: a siloed data source that is good at tracking Shopify orders. But if you want to track the complete customer journey and get accurate marketing data, you need to look elsewhere. Because it's both free and flexible, Google Analytics has become a top choice for a "single source of truth" to supplement Shopify analytics and other tools you might be using. And GA4, the newest version of Google Analytics, promises to be even more powerful. In our experience with hundreds of customers at Littledata we've found that many merchants turn to overblown solutions outside of GA (eg. fancy dashboards and generic data connectors) and then come back around to wanting to just fix the data in Google Analytics. After all, what good is the data if you can't trust it? Free ebook on Shopify and Google Analytics It's well known that Shopify's own analytics connection misses out on key issues like product list views, repeat purchases and marketing attribution. But where exactly does the tracking go wrong? What's going on behind the scenes? This new ebook is an insider's guide to Shopify Analytics vs Google Analytics. You will learn: Why transactions go missing in Google Analytics Common issues for Shopify stores The difference between marketing tags and Google Tag Manager How to set up checkout funnel tracking And all of the main reasons why Shopify doesn't match GA Download the ebook >>> Top brands turn to GA for a single source of truth, but there are some common things that go wrong. Even if you don't have a custom setup, things go wrong quickly -- including the "basics" like tracking ecommerce orders. We built Littledata to fix these issues automatically, saving you time and money. (Here's a quick demo video and our complete spec). But before you get into the details of the solution, it's important to understand the problem and what might be going wrong for your store in particular, whether you're seeing a lot of traffic that appears to be "Direct" but is actually from marketing channels like Facebook Ads or Klaviyo email marketing, you're missing repeat purchasing data, or your checkout funnel tracking is somehow out of whack. Get the ebook today. How to add Google Analytics to Shopify You can set up Enhanced Ecommerce in Google Analytics and then add Google Analytics to Shopify, but Shopify's default GA integration misses many key elements. [tip]With Shopify's default Google Analytics integration, 12 orders go missing for every 100 in Shopify. We highly recommend using an advanced data connector instead![/tip] If you would rather just get accurate data automatically, check out Littledata's 30-day free trial. It's the easiest way to avoid all of the known issues with Shopify's default Google Analytics integration. Plus, you still own the data in GA, whether or not you continue using our advanced data connections. [subscribe]
Top 7 rule-based audiences for ecommerce marketing
Rule-based audiences are customer groups or segments derived by customer activities. It sounds simple, but rule-based audiences can be a game changer -- and too many DTC brands miss out on the basics of this powerful type of customer segmentation. In ecommerce, rule-based audiences can be made using transactional activities (checkout date, coupon applied, etc.), marketing actions (email opened, promotion entered, etc.) or even product details (eg. type of product, color or type purchased). Ecommerce companies use the intersection of these events to group customers for the purpose of reporting, remarketing, targeting, and other customer enrichment activities. But one size doesn't fit all. Let's take a look at the top rule-based audiences and how they are used in ecommerce marketing. Benefits of rules based segmentation There are a number of benefits to deploying rules based audience recipes in your business. Whether you are a small-to-medium sized business, fast-growing startup, or have been around the block for some time like Littledata customers Dr Squatch and Rothy's, audience recipes are the building blocks for broader, innovative ways to segment your customers. Rule-based audiences can help you increase customer retention while improving product visibility in the crowded ecommerce marketplace Powerful tools like the Adobe Experience Cloud have highlighted rules-based personalization and audience building as a core part of their feature set. As they put it, "With rules-based personalization, you’re in the optimization driver’s seat." We agree, but with traditional enterprise tools that type of personalization can get really expensive. The good news is that brands using a modern data stack don't necessarily need to shell out for Adobe. Rule-based audiences can now be used by any ecommerce store, no matter how big or small. Here are some of the key benefits: Increase personalization through tailor-made product marketingImprove existing products and/or servicesIncrease upgrades and product upsellingEnhance profitability through the targeting of high-value customersIncrease retention with automation and buyer stage recognitionFurther marketing reach of customer types for remarketing, targeting and look-a-like audiencesEnhanced visibility and reporting of customer cohorts for tracking new acquisition and customer lifetime value Rule-based segmentation results in a hyper-personalized approach to directly influencing your customers’ experience. The ability to be attentive during each stage of the customer’s lifecycle allows for a better understanding of what drives good and bad experiences. Recipes for the top 7 rule-based audiences There are tons of different audiences you can build, but 7 always come up for successful DTC brands. In our case, we call them recipes, as they are the right number of ingredients to profile your customer base. X and Y in these examples will depend on your particular business: what you sell, how you sell it, and how often it makes sense for an ideal customer to come back and make a purchase or referral. Audience NameRecipe⭐️ First Time PurchasersCustomers who have made their first purchase in the last [X] number of days⭐️ Repeat PurchasersCustomers who have made at least 2+ purchases in the last [X] number of days⭐️ High SpendersCustomers who have made a purchase with order value greater than [$Y] in the last [X] number of daysAbandoned CheckoutsSite visitors that have added items to their shopping cart, but have not purchased in the last [X] number of daysBargain HuntersSegment of customers that have applied a promotional code on more than 1 purchase in the last [X] number of daysRecent BuyersCustomers who have made a purchase in the last [X] number of days⭐️ Inactive CustomersCustomers who have not made a purchase in the last [X] number of months*Additional segments include Loyal, Cancelled Customers, Location-based, Personalization (age, gender, preferences, income) Three audiences you should build today, with downstream activation examples All of these types of segmentation are potentially useful, even transformational, to your business. So where should you start? Today I will focus on the four most common and effective audience recipes that can generate immediate value to your store’s ability to identify, engage and enrich your customers’ experience. As highlighted above, those are: First-time purchasersInactive customersHigh spendersRepeat buyers To make things even clearer, we'll even combine High spenders and Repeat buyers into a high-LTV segment: your best possible customers, big spenders who are also loyal to your brand. 1. First-time purchasers First Time Purchasers are a good starting point for audience segments. The ability to identify these customers early will pay big dividends into maturing their relationship with your brand and products. Also, first-time customers are always the most likely to engage with your content (for example, opening welcome emails or sharing on social media), which ends up increasing the return on your investment and the potential for longer life cycles. How to Create a Welcome Email Template via Omnisend How to identify? Utilizing Littledata's order event tracking from your Shopify store, you can identify Order Completed in the last [X] number of days with a Customer Created event in the same time frame. How to activate? A great opportunity is through personalized welcome emails. By connecting to your ESP (eg. Klaviyo, MailChimp, Iterable) and building a customized message to all first time customers can be the first step to long-standing customer relationships. 2. Inactive customers Inactive Customers are a great win-back opportunity to gain customers back that have been inactive (or not purchasing) in a particular period of time. When a customer has been deemed inactive it’s too late to start formulating a strategy on returning them to your active customer pool. Instead building a strategy to identify, entice, and track appropriately is a must in any customer-focused business. Drive Repeat Purchases To Your Shopify Store With Automated Emails via Privy How to identify? Utilizing Littledata's order event tracking from your Shopify store, you can identify customers who have (at one-point) had an Order Completed event and with no purchase activities in the last [X] number of days. How to activate? Winback or revive email campaigns catered towards time-sensitive discounts, hyper-personalization (reference specific product categories a customer engaged or purchased in the past), summaries of product improvements, and membership benefits are effective strategies. Utilizing your current ESP, SMS, or retargeting platform alongside these customer groups can push once-active customers to return. 3. Repeat buyers & high spenders Repeat Buyers & High Spenders are the backbone of your business. As the tenured marketer would attest: “It’s easier to keep a happy customer than to find a new one”. Building customer loyalty requires a business to deliver on what is promised and to do so with their highest-value customers in the right channels and messaging. How to identify? Utilizing Littledata's order event tracking from your Shopify store, you can identify customers that have completed Order Completed events and total purchase count, purchase total, and revenue collected, during a [x] period of time and [x] number of times. Google Analytics users can also export data based on specific custom dimensions for LTV: Littledata – Lifetime Revenue Littledata – Purchase Count Littledata – Shopify Customer ID How to activate? There are several options here, including email and SMS (texting). SMS is a great tool to continuously engage with your customers. Invitations for users to sign-up for a loyalty program to provide exclusive offers or to release product updates can come simply through a users’ most desirable medium - their phone. With SMS boasting a +95% open rate, it's the most effective way to have a two-way connection with your customer and showcase value-added services. For Littledata's Shopify Plus customers, the most popular platforms for this type of engagement are Yotpo and Loyalty Lion. Technology for activating rules based segmentation Leveraging modern technology furthers the ability to do so repeatedly and with best-in-class platforms. Here are two examples of leaders in that space: Segment (sometimes called Segment.com) and Hightouch. Hightouch Hightouch syncs the data from your data warehouse to the tools your business relies on. It’s called operational analytics and it allows customers to leverage their existing technology (ie. your data warehouse) to pipe customer data to downstream platforms for activation, engagement, and other business activities. Since Littledata's no-code event collection is captured downstream in your Google Analytics platform, customers can leverage that same data when it is stored in their data warehouse. Modeled inside the platform with out-of-box SQL logic, segments can be then pushed automatically (and scheduled) to deliver on the intended goals. In fact, that's one of Hightouch's taglines: No scripts. No APIs. Just SQL. Segment Segment is a customer data platform (CDP) that integrates cohesively with Littledata's no-code event collection. Segment allows customers to integrate data from a catalog of sources (including the Shopify source, maintained by Littledata) and activate to destinations for customer engagement, activation and reporting. Inside the platform there are features that allow customers to create personas or audience segments, deploy functions, and build out layers of automation to seamlessly leverage their platforms’ source data. [tip]See what's new in Littledata's Shopify source for Segment, including more consistent product properties and enhanced Personas matching [/tip] Littledata Littledata is designed for the modern stack, whether you're using just a couple of tools such as Google Analytics and Data Studio or a whole modern data pipeline (eg. Segment, Fivetran and Redshift). If you're using a Shopify or BigCommerce checkout, you can use Littledata's analytics connectors to capture complete sales and marketing data and send it downstream. It's the easiest way to ingest the data you need to create enriched audience personas, and the only way to get 100% accurate ecommerce data automatically with extensive, ongoing development efforts. Not sure which tools you need? Book a demo with our data experts to discuss your analytics plan.
Property and destination updates in our Shopify source for Segment
Over the last 6 months, we’ve continued to enhance Littledata’s Shopify source for Segment to work with any modern data stack. We have focused on providing a more comprehensive range of events and properties to sync with any destination in Segment, including email marketing tools, data warehouses, and Segment Personas. Our Segment connection uses a combination of client-side (browser) and server-side tracking to ensure 100% of your Shopify store data is sent to Segment. Littledata automatically integrates with Shopify and Shopify Plus sites to enable complete ecommerce analytics, including sales, marketing, customer, and product performance data. Recent updates include better matching with Personas, more consistent product properties, and more. Here are some highlights. Tracking plan for Segment Protocols We've written a full tracking plan and event schema, which is ready to upload into Protocols to prepare for robust data consistency in your data warehouse. Better matching with Segment Personas You can now choose which userId to use for Segment events from a standard list of common identifiers: Shopify customer ID - This is the default for new installs. Recommended if you have a simple Shopify setup with minimal integrations. Hashed email - The MD5 email hash is useful if you have other marketing platforms sending traffic where you know the email of the visitor (e.g. email marketing like Bronto or Marketo), but not their Shopify customer ID. Email - The email identifier is recommended when other platforms use the email and can’t hash it, and you are comfortable with the privacy implications. None (no identifier) - Choose “none” if user identity is already handled by your Segment implementation and you only need the extra events powered by Littledata's Shopify source. All user traits below are now being sent in the context.traits, and are synced with your CRM destinations every time the customer record in Shopify is updated. Trait Description Type createdAt The date customer record was created Date customerLifetimeValue The total spend of customer on the Shopify store Double default_address.street The customer’s default street address String default_address.city The customer’s city address String default_address.postalCode The customer’s ZIP / post code String default_address.state The customer’s state address String default_adress.country The customer’s country String description The customer notes String email The customer’s email address String firstName The customer’s first name String lastName The customer’s last name String marketingOptIn The marketing_opt_in field from Shopify customer String phone The customer’s phone number String purchaseCount The number of orders by this customer Integer state Whether the customer account is enabled (user has opted in) or disabled String tags The custom tags applied to the customer String userId Chosen user identifier, defaulting to Shopify Customer ID Double verified_email Whether the customer has verified their email Boolean Import historic Shopify orders into Segment For Enterprise Plus customers we can now import orders and refunds from before the date Littledata was connected to Segment. This allows you to build a complete customer record in destinations that support historic events, such as a data warehouse. If you are already a Littledata Plus customer, please contact your account manager to discuss setting up an order import. If you haven't yet tried Littledata or are still investigating solutions for you data stack, book a demo today with one of our data experts. [subscribe] Consistent product properties across all events We understand you need a consistent set of product properties with every ecommerce event to make analysis easier. For example, the product image URL is available within a Product Added event to make it easy to set up dynamic product retargeting campaigns. Previously, we only got the following properties from Shopify’s webhooks: shopify_product_idshopify_variant_idname (title)brand (vendor)sku And now we add these extra product properties for all events: variant (variants.title)image_url (from images..src)cart_id (only with Product Added / Product Removed)urlcompare_at_price (variants.compare_at_price) Extra revenue properties We’ve added more reporting flexibility with how we send revenue data to Segment. Specifically, on Order Completed and all Checkout events, you will now see a subtotal = (product revenue including discounts). For the Order Completed event only, your store can opt in to an additional revenue property (product revenue excluding discounts, shipping and tax) via the Littledata application. Revenue is a reserved property in many Segment destinations. Opting in will override the total property sent to Google Analytics. Supporting the Iterable email destination Iterable is a cross-channel marketing platform that powers unified customer experiences and empowers you to create, optimize and measure every interaction across the entire customer journey. With this update, when an Iterable campaign leads to an Order Completed event the event properties will contain campaignId and templateId. To get these extra properties, you will need to edit the LittledataLayer setup to track the iterableEmailCampaignId and iterableTemplateId cookies. In addition we send an email field with all events linked to a user, so Iterable and other email marketing destinations can use the events. Supporting the Google Analytics destination in Cloud Mode In Cloud Mode, Segment will send event data to Segment’s cloud servers, and from there, we will translate and route that data to Google Analytics. This reduces the amount of third-party code on your site and you will be able to replay historical data in Google Analytics. We are happy to announce that you can now switch Google Analytics connection mode to Cloud Mode to relay events to GA from Segment's servers. This will increase page performance and provide greater control of the schema. More Subscription Event Properties On Subscription Created, Subscription Updated and Subscription Cancelled events we have added: statusproduct_id = shopify_product_idname = product_titlepricequantityskushopify_variant_idvariant = variant_titleorder_interval_frequencyorder_interval_unit On the Subscription Cancelled event only we have: cancellation_reasoncancellation_reason_comments And on the Charge Failed event we added: error_type Change of product ID used in Segment events Previously, we used the product SKU for client-side events to be consistent with the GA destination. From this month, we have changed this to send the Shopify product ID as the product_id field in Segment for all events. Ability to send anonymized IP instead of full IP to Segment Segment’s AnalyticsJS library sends the whole IP address by default in Track and Page events. This is contrary to our GDPR recommendations, and we now set context.ip with the last octet (3 digits) anonymized. This still allows geolocation of the events, but ensures IP addresses are not accidentally captured in end locations.
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