The Ultimate Guide to connecting Segment to Redshift (and other powerful analytics tools)
Cloud data warehouses offer a way for ecommerce companies to scale as the size of their data increases, promoting unlimited storage space, cost optimization and analytics horsepower. But where do you start? Are there no-code solutions that are also best-in-class? Segment is an increasingly popular way to connect website data to a data warehouse such as AWS Redshift. In this guide we'll take a close look at exactly how this works, and the pros and cons for your longterm company data needs. Using Segment to connect Shopify to AWS Redshift What is Segment? Segment is a powerful Customer Data Platform (CDP) solution, but it's also much more than that. Segment provides businesses the ability to organize customer activity events from various platforms to a broad range of destinations, One of those destinations can be a data warehouse - an ecosystem that serves as the centralized source of data collection. This includes the big three: BigQuery, Redshift, and Snowflake. The technology focuses on the tasks of collection, storage, and management of business data - with the purpose of turning operational data into meaningful information. For any company looking to harness the value of the activities gathered inside their CDP, it’s a no-brainer that bringing a data warehouse into the mix is the next best step. Amazon Web Services (AWS) and its data warehouse offering, Redshift, remains the market leader in this space because of its compatibility with data integration pipelines and analytics tools. One of your Segment destinations can be a data warehouse such as AWS Redshift For ecommerce sites this can be difficult to implement manually (not to mention maintenance time, costs and complexity!), but Littledata's Shopify source for Segment does this automatically. With Littledata’s capabilities, you have the ability to direct, track, and identify custom events across all critical customer activities, including across your Shopify website, whether that's a simple Shopify instance, a headless Shopify setup or multiple country stores doing international sales. Coupling that with Segment’s unified CDP takes powerful data to activation, and the ability to direct platform data to marketing channels for increased engagement, conversion and retention. Whether you want to use a data warehouse for deep analysis, audience building or real-time recommendations, Littledata + Segment + Redshift is a proven solution for Shopify stores. Setting up your Redshift data warehouse Segment's documentation portal gives a step-by-step breakdown of provisioning a Redshift cluster, configuring a database user, securing data ingestion, and providing a path to data collection into your Redshift instance. Breaking the process down in digestible chunks, here are the necessary steps to go from data to data warehouse: Choose the best instance for your needs: Dense vs. Compute StorageProvision a new Redshift Cluster: 5 simple steps from start to finishCreate a database user: Creating a user to manage your instanceConnect Redshift to Segment: Select sources, credentials, and go Redshift allows users to start small and scale up on-demand as needs grow Collecting events in Segment Event tracking is a critical part of the data collection process. Creating a plan tracking plan associated with measurable business outcomes, such as acquiring new customers, increasing retention and activating new leads, and mapping those outcomes to business goals, is an important step in the data journey. Understanding this relationship will provide guidance to the relevant events or actions that must be configured to successfully track. With Littledata's automated solution, you can avoid the blocking-and-tackling of configuring the best-in-class event strategies surrounding (client side) device-mode and (server side) cloud-mode events: Device-Mode events include Cart Viewed, Page Viewed, Product Clicked, Product Image Clicked, Product List Viewed, Product Shared, Product Viewed, Products Searched, Registration Viewed, Thank you Page Viewed Cloud-Mode events include Checkout Started, Checkout Step Completed, Coupon Applied, Customer Created, Customer Enabled, Fulfillment Created, Fulfillment Updated, Ordered Cancelled, Order Completed, Order Refunded, POS Order Placed, Payment Failure, Payment Info Entered, Product Added, Product Removed To streamline the process for ecommerce sites, Littledata's tracking script automatically sends events to Segment through its analytics.js library, making it easy to collect all the critical event activities associated with a customer’s store journey - from browsing behavior through the checkout funnel and repeat purchases (including recurring billing for stores selling by subscription). Additionally, from every event where this is an identifiable customer (from both device-mode and cloud-mode), Littledata will send an Identify call - the identification of a customer when the customer logs into your storefront, a last step of the checkout process, with the order, and also after a purchase with a customer update. With Littledata’s streamlined modeling, data can be accurately represented and pushed to downstream destinations, such as marketing activation channels and data warehouses. [subscribe heading="Littledata connects Shopify to Segment and your data warehouse" button_text="Book a demo" button_link="https://www.littledata.io/app/enterprise"] Connecting Segment data to your data warehouse Now that your Redshift instance is up and running, the next step is to connect to Segment and start collecting data into your data warehouse. There are two ways to complete this step - one, through Segment’s native migration, and the other, utilizing no-code data pipeline tools (recommended). Whichever process you choose, you will have the opportunity to push data out of Segment into your data warehouse environment and start utilizing it across your business. Option 1: Segment’s native migration As mentioned, Redshift data warehouse is one of the many destinations that Segment can send data to. You can directly connect to Redshift from within Segment to stream event data. Segment’s catalog provides direct integration to best-in-class data warehouses Essentially, it’s as simple as: Login to your Segment App and proceed to the Catalog sectionIn the top menu, choose DestinationsSelect Redshift in the Storage Destinations list After configuring your user permissions and selecting the data sources you would like to sync, you’ll enter in your credentials and connect to your data warehouse. Voila! Data will now be continuously replicated into your Redshift instance based on your plan: Free: Data refreshed (synced) 1x per dayTeam: Data refreshed (synced) 2x per dayBusiness: Data refreshed (synced) as fast as hourly As for historical data, all plans will allow loading up to 2 months of your historical data, with the Business plan allowing for full historical backfills. Since Segment provides an environment to support many, it requires a premium plan to collect complete history and sync data real-time. Segment’s infrastructure is suitable for instantaneous data collection to downstream points Option 2: Leverage data pipeline services The second way to get data out of Segment into your data warehouse is through data pipeline platforms. Data pipeline or ETL (Extract, Transform, Load) platforms, provide prebuilt integrations to over 100+ enterprise software sources, and focus on a maintenance-free structure where replica data is automatically transformed, standardized, and normalized on collection. The automated adjustment to schema and API changes, allows business users to streamline developer tasks in a no-coding required environment. Companies like Stitchdata ("Stitch") and Fivetran, leaders in the space, provide frictionless, subscription-based memberships that allow integrating data to data warehouse destinations convenient for any business size. ETL platforms streamline data from end-to-end and require limited technical lift To set up, simply sign into your console, click on the Segment icon in the available integrations, and enable. You will automatically be pushed into the Segment tool to confirm authorization and (another voila!) data will begin replicating. Stitchdata’s user-friendly interface for connecting platforms to destinations The benefits of cloud-ETL platforms, not only include their out-of-box integrations, but the list of features included to help visualize, maintain, and support ongoing data integration tasks: Over 100+ database and SaaS platform integrationsIn-app support including email alert monitoring and support SLAs14-day free trial to kick-off and vet the platform prior to fully onboardingSOC2 security compliant, encrypted communication and an AWS cloud backed environment Ecommerce data With the appropriate event tracking configured at data collection by Littledata, your data can be properly analyzed for ecommerce store performance. The downstream output can be properly displayed by: Customer behavior before, during and after purchaseOrder performance relative to average order value, add-to-carts, average order size, and cart abandonmentShopper engagement including product views and purchasesCoupon and discounting activitiesCustomer checkout funnel and stage of drop-offConversion rate and lifetime value With the emphasis on accuracy completed at the inception data collection stage, the ability to produce the above areas of performance becomes that much more straightforward. This means spending more time analyzing and visualizing data, then transforming and modeling data for analytical use. Empowering your data Once your data is available in your data warehouse, replicating frequently, and building history, it’s time to utilize it. That can come in a number of various opportunities, depending on your business needs. Most notably, companies will focus on transforming data into actionable blocks and pushing into business intelligence (BI) tools. Transformation To properly stitch event data together - say in the case to tie all interactions by a site visitor to achieve multi-channel attribution - companies can leverage existing packages that transform, marry and enrich data points. These packages - or prebuilt libraries - produce powerful results that end up restructuring data from their raw state to analysis-ready. Fishtown Analytics’ product dbt does just that, performing user-stitching, simplifying data structures, and speeding up data modeling to use instantly within reporting, analytics, or machine learning applications. Leveraging transformation can streamline data modeling and enrich data for analytical-use BI Tools Companies usually begin the conversation here, “I’d like to see a dashboard like X” or “Can we get a report showing Y?”. In fact, what they are looking for is a way to properly view data in digestible, actionable views. BI (Business Intelligence) tools do just that - whether it’s through data visualizations (dashboards), self-service analytics, or prebuilt reporting. Enterprise BI and SaaS tools like Looker and Tableau (like outlined in the table below) create the speedy path to data viewing. They can be simply connected to a data warehouse and publish dynamic views for instant performance tracking. Data can be presented in dashboards across many dynamic charts, tables, and graphs BI Tools Breakdown CategoryVendorsBreakdownMarket LeadersTableau, Looker, PowerBI, Mode, DatabricksEnterprise tier platforms with extended featuresRisersDomo, Klipfolio, Kissmetrics, SigmaSaaS-oriented products with cost on user and dashboard usePrebuiltGlew, Daasity, Dashthis, Rubix3Ecommerce focused with prebuilt visualsOpenDataStudio, MetabaseOpen-source/no-cost platforms So a straightforward reporting and visualization solution with the setup we've described in this article, would be to connect Shopify to Segment, then Segment to Redshift, then Redshift to Tableau. Learn more about how to connect BI tools to your Shopify data in Segment, whether as a Segment destination using alias calls or a dynamic view pulling from data in your warehouse. Another option is connecting reporting tools directly to Google Analytics data in parallel with your Redshift setup (for example, use Tableau on top of GA for marketing analysis and Looker on top of Redshift for deeper analysis and predictive analytics). Building for the future Companies that put an emphasis on building the foundational components of data ingestion, management and analytics early on see many benefits. Primarily, you are able to increase your ability to measure and understand your business properly. Data warehouses provide an opportunity to collect all of your store, site, customer, marketing, other relational data - all in one place. This creates a centralized view of your business and gives an upper hand to companies looking to take a data-driven approach to growth. Cloud tools and no-code options remove the need for technical resources, freeing up dollars that can go elsewhere without sacrificing the ability to use and analyze data. No matter the size of your business, taking data seriously is the first step to empowering your business for the future. Data warehouses are no longer the property of only mega enterprises. Want to build a modern ecommerce data stack but not sure where to start? Get in touch for a free consultation. [subscribe heading="Littledata connects Shopify to Segment and your data warehouse" button_text="Book a demo" button_link="https://www.littledata.io/app/enterprise"]
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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]
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