Category : Data Strategy
3 ways to start using first-party data for ecommerce
First-party data is the buzzword floating all about the ecommerce world—and for good reason. As you probably know already, third-party cookies are soon to be no more. Add in the overhaul that iOS 14's tracking opt-out and other intelligent tracking prevention brought about, and getting accurate metrics on attribution and customer behavior looks a whole lot different to marketers than ever before. That's where first-party data collection comes to the rescue to save your campaign reporting. First-party data is data you collect directly from a user, and it's about to become the standard for data collection across the ecommerce landscape. To help you learn more about first-party data—and start using it yourself—we have three helpful posts covering different first-party data solutions and how they fit into your marketing strategy. 10 reasons to switch to server-side tracking for ecommerce analytics Server-side tracking is a method of collecting first-party data via a cloud-based server rather than by taking data directly from a website visitor's browser (known as client-side tracking). In addition to being a more secure way to process data, server-side tracking complies with new privacy regulations and is not disrupted by ad blockers. There are numerous benefits server-side provides, and we've got 10 of them for you to check out in this blog post. https://blog.littledata.io/2022/07/23/10-reasons-to-switch-to-server-side-tracking-for-ecommerce-analytics/ How to run dynamic Facebook ads with Facebook Conversions API While there are plenty of promotion methods available to ecommerce store owners today, PPC and social ads still reign supreme as the top option. From top DTC brands to small startup stores, ads are a great way to get your product in front of ideal buyers using personalized ads to convert leads into sales. Of course, ad blockers and tracking prevention has changed the way brands can leverage this tool. To help you learn how to keep personalized ads that return on spend, we have a guide on how to create dynamic Facebook ads using Facebook's Conversions API (CAPI). https://blog.littledata.io/2022/03/09/how-to-run-dynamic-facebook-ads-with-facebook-conversions-api/ How to build customer behavior reports in Google Analytics 4 Marketing methods aren't the only things that need changing in our new first-party data world. Reporting on your marketing efforts requires the same overhaul—and we can show you how to do it with the newest version of Google Analytics (GA). GA4 comes with tons of new custom reporting features and advanced capabilities previously only available to paid users. That includes the ability to use more custom dimensions to build detailed reports on customer behavior. One of the more helpful reports we recommend using is behavior reports. They allow you to see what customers are doing once they make it to your store, and what they do when they're at the checkout. Plus, setting these reports up in GA4 only takes a few minutes, as you'll see in our how-to video on creating shopping and checkout behavior reports. https://blog.littledata.io/2022/07/01/how-to-build-customer-behavior-reports-in-google-analytics-4/ [subscribe]
5 apps you need to have in your Shopify Plus tech stack and why you'll love them
As marketers, we are always looking at top tools the pros use—or the ones folks with the little blue checkmarks next to their Twitter handles recommended to the masses. In my experience, while it is crucial to test new tools to help move the needle forward and find new solutions, choosing the right ones can present the biggest challenge. These are the top five tech tools that stand out to me after chatting with merchants, attending conferences, and working in the ecommerce space. Set Up Accurate Tracking Using Littledata (let's start with a shameless plug) Well, you knew this one was coming. Data is not in the WANT category of apps for your Shopify store. It is a NEED. I am all in on making decisions from experience and intuition as a marketer. But you become even more dangerous and equipped when you add accurate data to the mix. Having reliable metrics in your arsenal allows you to tear apart your funnel to see what works and doesn't. Tracking user behavior gives you an up-close look at your customer's needs. Accurate marketing attribution data gives you a predictable revenue forecast using LTV, AOV, and order volume. Before jumping into other apps, set up your tracking in Google Analytics for proper monitoring, reporting, and remarketing. Littledata makes this a breeze taking the average store about 10-mins to set up automatic tracking. [tip]Littledata also offers a 30-day free trial so you can see the difference before you spend a dime![/tip] Master Recurring Orders with Recharge You've probably heard the saying, "it's six times more expensive to win a new customer than to retain an existing one". Many merchants would probably say it's much higher than that. This is where subscription tools like Recharge come into play in a big way. Making it wicked easy for a customer who loves your product to buy it on a recurring basis can help you achieve increased sales and maintain customer relationships. Recharge works with over 15,000 brands and helps them increase LTV and customer engagement while reducing churn—two things we all talk about in the ecommerce ecosystem. They even offer a fancy-free LTV Calculator so that merchants can get an idea of how they can grow their business using subscriptions. Another perk is that Littledata integrates with Recharge! Customer Success Engaging with your customers and providing first-class support is incredibly important for any business. When you are doing it virtually, though, things can be missed. That's why automating your support workflow the best place to start. We recommend our friends over at Gorgias who pride themselves on helping ecommerce brands with their app. Recently, they worked with popular DTC fashion brand Princess Polly to improve their customer support. Gorgias reports in their recent customer success story that "Princess Polly increased their efficiency by 40%, increased their resolution time by 80%, increased first response time by 95%, and improved one-touch tickets by 15%. This allows the brand to quickly connect with customers on a personal level and strengthen customer loyalty." A foundation built on a great team of people combined with customer success tools can help protect and grow the brand you've worked diligently to create while providing a great customer experience. A solid SMS tool Engaging your prospects and customers using SMS is a must in my opinion. There are many stats on how open rates of SMS far exceed email, but as many marketers know, we use different channels for a range of outcomes and communications. A stat that recently caught my eye was from our friends over at Attentive. Recently they shared a case study reporting a 900% increase in year-over-year SMS-driven revenue for their new client, Thrive Market. The basis for this growth was implementing a few things you can easily try with your ecommerce business: Text to join or sign up Welcome Campaign Free gift with purchase Custom landing pages for direct SMS Check out their integrations page to see how you might be able to leverage their tool for your brand. Drive Reviews for Social Proof Getting reviews can be a huge pain in the neck and often is an afterthought for ecommerce brands. Outlining and creating a “review strategy” is a healthy place to start. Start by asking yourself questions like "What products do I want reviews on?" or "Should I frame the request to highlight a specific product or attribute about the brand?" These are among the most important things to consider when asking for a good review. Once outlined, pair that “review strategy” with Okendo, which is built to capture high-impact customer reviews and showcase them on your site to build trust and drive conversions. These reviews help create social proof, which often means an action taken in light of one seeing the action of another. In this case, a purchase from another would impact the likelihood of someone trusting but then also desiring to make a purchase themselves. Reviews are also an amazing way to secure user-generated content from your customers. Seeing your product in action in everyday life is heartwarming as a merchant, but can also impact those looking to buy—which can lead to better conversion rates. Conclusion The bottom line when it comes to tool selection? Don't stress too much. These are the top tools I've found merchants recommend (and ones I stand by myself), but in the end it's most important to make sure that your tools not only fit your overall product vision, but fit with each other as well. That last point can be a bit of a sticking spot if you aren't using the right connector to bring everything together. Littledata does this very well. In fact, we have a whole case study you can check out to see how apparel brand johnnie-O leveraged our analytics app to do just that.
How Littledata Helps Velir Shorten Time to Value and Improve the Odds of Project Success
Do you need to process customer data in-house to be truly data secure?
Many brands with large customer bases are facing a similar question when it comes to storing data—is it time to bring all data processing in-house? Whether this is prompted by a data security audit, a data breach, or a desire to be more agile with data analysis, it's an important question that thankfully doesn't have a complicated answer. In this article, I’ll explore whether you should outsource or insource customer data processing for your brand. Quick side note—for Littledata’s direct-to-consumer (DTC) brands, customer data is usually first-party data captured as part of the ecommerce checkout process, including post-purchase interactions with the customers and web browsing information such as IP addresses. Why you need first-party data to be secure First-party customer data is data the customer shares with you directly through the server connecting them to your website. By its very nature, first-party data is created by a contract—and more importantly, a bond of trust—between your brand and the end customer. Accidentally leaking that data is brand-damaging: 46% of organizations surveyed by Forbes suffered reputational damage after a data breach. In addition, GDPR and similar regulations impose large fines (up to 4% of global revenue) for data breaches—specifically, lax processes leading to a data breach. You might also be concerned about commercial espionage—how valuable could your customer purchase history be in the hands of a competitor or a fraudster? Or maybe your company has been burned by third-party data processors in the past whose security standards did not meet your own. Taking these concerns together, you may be thinking the only way to be truly data secure is to process and store first-party customer data on your own infrastructure. But there are downsides to this. Do you want to own your own data infrastructure? By data infrastructure, I don’t mean owning bare-metal servers that sit in the broom cupboard behind your office. I’ll assume you are comfortable with the concept of hosting data in a public or private cloud environment. However, even maintaining that cloud computing infrastructure brings costs and risks. Your company will be responsible for software patches, updates to use the latest API versions, monitoring for suspicious activity, and handling outages. Data engineering is complex, and great data engineers are in short supply. So, I suggest you are better off licensing a secure data pipeline than building it all yourself. Does your company control the data end-to-end? Frankly, processing company data in-house may be missing the point if you do not control the data processing end-to-end. Many of Littledata’s customers have made a deliberate choice by working with Shopify or BigCommerce to leave purchase and transaction processing to a cloud provider—signing data processing agreements (see DPAs for Shopify and BigCommerce) to store customer data on US cloud servers. Many brands also make a choice to share customer data with Google (pseudo-anonymized) or with Facebook (not anonymized) to improve their customer acquisition and Return on Advertising Spend (ROAS). In effect, these brands are outsourcing the data processing that happens between the ecommerce cloud and the marketing cloud to Littledata. Trying to do this processing in-house makes little sense when the start and end of the data processing chain are third parties. Does EU customer data need to stay in the EU to be secure? You may have read about regional courts in France and Austria ruling against sending EU customer data to Google Analytics—or indeed sending data to any US server. I think these rulings are extreme and will eventually be struck down. There is no practical or legal reason why data processing on servers within the EU is somehow more GDPR compliant than hosting on the cloud in the US. That said, data nationalism as a trend is here to stay, so there may be a future need to keep EU data siloed. All cloud computing networks have EU servers, and tools like Segment make it possible to split EU customer data processing onto EU servers. The limitation is that right now, none of our other partners (especially Shopify, Google, and Facebook) have the same ability to process in the EU. This makes regionalizing only one part of the data processing chain pointless. Is outsourced data GDPR compliant? Yes, you can subcontract data processing to a third party. But to be GDPR compliant, your data processors need to enable the right to rectification, the right to erasure, and the right to restrict processing. All the main partners that Littledata works with (Shopify, Google Analytics, Facebook Ads, etc.) have API endpoints by which your customer can request their data to be updated or erased, and this request can be passed on to the downstream processors. If the customer requests to restrict processing (e.g. opting out of advertising retargeting using a cookie consent banner) your company needs to also pass along that choice to the downstream processors. Littledata’s tracking script makes that easy to do via integration with Shopify’s consent management, and plugins for OneTrust and TrustArc. Can you control outsourced data processing? Yes. Doing so is just a matter of working with a processing partner that a) is transparent on how they process the data, b) follows good practices in data security, and c) provides Service Level Agreements (SLAs) for the processing. At Littledata, we are clear about how we process customer data (and exactly what data points are stored where), have a public data security policy, and provide tight processing SLAs for Plus customers. [tip]Learn more about how Littledata protects your data while giving you 100% accurate analytics by booking a demo with one of our experts.[/tip] Conclusion I believe you can outsource data processing and still be truly data secure. In fact, I believe trying to bring data fully in-house is costly and pointless for most cloud ecommerce brands. Pick trusted partners to ensure your customer data processing is both super reliable and super secure, and get on with scaling your business!
Why Data is Critical to Your DTC Growth Strategy
When it’s time to think about data, our minds can often turn right to dull spreadsheets, dense reports, and stressful conversations around bottom lines. In reality, data and analytics have actually become far more approachable—and even exciting—in recent years, thanks in large part to the introduction of more intuitive reporting tools. From versatile apps like Google Analytics to specific tracking tools like Facebook’s Conversions API, being able to add precise tools to our tech stacks empowers the inner data geek in all of us. With the right setup, we’re able to learn far more about our buyers and their journeys—whether that be the channels that referred them or how many times they’ve come to our site. We can even track actions taken on our stores too and deep dive into what happens at the mighty check out. Ultimately, all this information helps us evaluate where we can improve the customer experience and understand what we need to do to amplify what’s working within our strategies. How data fuels your store’s growth Today, growth marketing takes many different forms, all with the goal to attract, engage, and delight customers. At its core, generating growth comes down to constantly monitoring and evaluating digital metrics—taking a pulse on the day-to-day so you know your business goals are being met and your customers are being heard. This is where Littledata swoops in to become your team’s ecommerce data platform and a single source of truth. It’s the central piece of your stack that brings everything together, letting you develop and implement sound growth strategies on Shopify and Big Commerce. Growth marketing can only work at its best with accurate and reliable data. An example from the real world Recently, I was chatting with a store owner for a Shopify DTC brand selling baby products. They were doing over $50,000 a month in sales on average in 2021—not a small brand by any means. When I asked about their tech stack and how the company monitors analytics, the owner told me, “(We have) Google Analytics, yes, but I have not learned how to analyze my business. Simple as that.” I shared how data is a journey for every store that helps store owners understand what customers are doing and where to spend to engage them. The store owner replied, “Totally, I was just in Google Analytics, and none of my AOVs match up with my channels. Good to know there are tools at least”. We see this every day from all-size brands—companies need to resolve these unhealthy errors in their reporting. How to fix your analytics Littledata got its start consulting for brands just like the one I spoke with. In doing so, we discovered a major problem with their reporting and analytics. Since then our mission has been to make it ridiculously easy to connect sales, marketing, and customer data. Top DTC brands around the world trust Littledata’s smart connections for accurate ecommerce analytics. Since launching our first Shopify app in 2017, we have empowered thousands of data-driven brands to make better decisions to accelerate growth. We do this not only through our new integrations, tools, and online resources for stores but also by partnering with notable agencies and tech providers around the globe. One area where data can be critical is the notorious checkout. Take, for example, a scenario where you notice many store visitors are reaching the checkout but seem to drop off during the actual completion or conversion point. Might it be helpful to know exactly where these folks are dropping off in the checkout flow? Let’s take a look at the user journey above. The checkout journey starts when a user clicks the checkout button and Littledata’s connector logs the events and labels them in your Google Analytics Destination. Being able to track these steps can be highly insightful into your customers’ behavior, why they drop off, or even for retargeting based on checkout with Adwords. In the end, all this works to help you make the right moves with your check-out flow for both one-off and recurring orders. Tip: Did you know 12 out of every 100 Shopify orders go missing in Shopify’s own analytics? See how to get them back. So what are some basics we can do to get started? How can we really grow our business with data? Do you start with AOV, LTV, CAC, or one of the many other ecommerce acronyms that keep us up at night? Littledata is here to serve you. Just as it did for the store owner I mentioned above, the solution starts with showing you if the data you’re using is valid or a dumpster fire. Here are a few resources to start evaluating and measuring if your data is accurate: Many of our customers start with reviewing their Shopify reporting against Google Analytics—here is an ebook to help you get started on that journey. Subscriptions are paving the way for the hyper-growth of DTC brands. If you’re using Recharge, Smartrr, Bold, or Segment in your stack and want to learn more about attribution to make data-driven decisions, you can learn more here. Bring in the right data from your existing tech stack—check out our integrations and connections. Look at our reviews on Shopify, Big Commerce, and G2. These are responses and insights from real DTC Stores. They might have a helpful perspective or have solved a problem using Littledata that you are facing now. Book a demo with our experts—we’re friendly, experienced, and have helped thousands of store owners just like you! Want to get started right this second? Easy. Jump in with a 30-Day Free Trial of Littledata. Your accurate data awaits you!
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"]
What's new in v2 of our Shopify source for Segment
We've a built a loyal following for our Shopify to Segment connection, and this month we've rolled out the next version, v2, with new events and enhanced functionality. As Shopify and Segment both continue to see unprecedented growth, Littledata is here to ensure accurate data at every ecommerce touchpoint. We've seen a surge in DTC and CPG brands on Shopify Plus that rely on Segment to coordinate customer data across marketing, product, and analytics tools. We have continued to develop our Segment integration to fit all of these use cases. [note]If you installed Littledata's Segment connection previously, please contact us to add the v2 events.[/note] About Segment v1 Last year, we worked with Segment to create a robust Shopify source for Segment users. The aim was to make everyone's job easier, from CTOs to ecommerce managers. Littledata's Segment connection v1: Captures all customer touchpoints on your store, both pre and post checkout Sends data to any of Segment’s hundreds of destinations Works seamlessly with Google Analytics Uses a combination of client-side and server-side tracking to capture browsing activity, orders and refunds Sends user fields for calculating customer lifetime value [subscribe] What's new in Segment v2 Since we launched the first Shopify app for Segment in May 2019, we have continued to make improvements based on user feedback and new use cases. The latest version of our Shopify source for Segment offers several updates and enhancements, including support for email marketing around order fulfilment events; tracking for a range of new order and payment events, including POS orders and order cancellations; and alias calls to support additional analytics destinations such as Mixpanel and Kissmetrics. Fulfilment status Many of our customers use Segment events to trigger transactional emails on platforms like Klaviyo and Iterable. One key email that stores want to customize is the 'Your order has shipped' fulfilment email, and so we now trigger a Fulfilment Update event when the fulfilment status of an order changes. This event includes status, tracking_numbers and tracking_urls (where the shipping integration allows), so the transactional email can include actionable details for the end user. These events can also be used in analytics destinations to look at fulfilment trends by product, or see how marketing campaigns around shipping match real-world delivery times. Support for email marketing Email marketing destinations such as Klaviyo, Iterable, and Hubspot, cannot use an anonymous identifier -- so our Segment connection now sends an email property with all events (when it is known), usually from checkout step 2 onwards. Where the email is captured on landing pages (e.g. popup forms) we also send this with the Product Viewed and Product Added events, to make it easier for you to run retargeting and engagement campaigns. Support for Kissmetrics & Mixpanel destinations To support seamless customer tracking in analytics destinations such as Mixpanel, Vero and Kissmetrics, Segment requires an extra alias call. Littledata ensures the pre-checkout anonymousId is added as an alias of the userId (used from checkout step 2 onwards). Learn more in our developer docs. Customer account creation On Shopify, every checkout (even as a guest) creates a customer record. This was already passed on to Segment with an Identify call and a Customer Created event. However, it is useful to know when this customer creates a password and creates a verified account with the store. For example, some brands use this event to trigger welcome emails or offer discounts. With Segment v2, we now send a Customer Enabled event when the user has confirmed their email address and created a Shopify customer account, with verified_email set as true. Payment of draft orders Some stores (especially B2B brands and wholesalers) create draft orders which are later paid. From November 2020, Littledata's Segment connection triggers an Order Completed event whenever these draft orders are paid, linking them back to the user session when they were created. POS orders Previously POS (point-of-sale) orders were excluded from Order Completed, as this polluted the revenue attribution in Google Analytics or other Segment destinations. However, as Shopify POS and other POS orders have become more popular, we now send a separate POS Order Placed event, so you can track the POS orders and choose whether to add them to your web orders. Payment failure After a customer goes through your checkout and completes an order, there is still a chance the payment fails, usually due to fraud checks. A new Payment Failure event allows you to track these failures, and see if they are more associated with particular marketing campaigns, geographies, products, or other factors. Order cancellations If the admin has cancelled an order, perhaps due to the product being unavailable, an Order Cancelled event is now triggered (including the cancel_reason). This is useful for both tracking/analysis and re-engagement campaigns. Product properties Last, but certainly not least, we've expanded the range of product properties sent with every product for better segmentation. Details such as shopify_variant_id, category and brand are sent with all client-side events and most server-side events. For more information, read our developer docs or schedule a demo today with an analytics expert.
Measurement Protocol connection for Shopify stores
We are excited to announce the beta release of a new Measurement Protocol connection for Shopify stores. As we continue to optimize Littledata for Shopify Plus, our team is always on the lookout for ways to help larger brands ensure a complete data pipeline, whatever your data stack might look like. Being able to send server-side events is one of the core benefits of the Google Analytics Measurement Protocol, so it was a natural next step to extend our advanced tracking for Shopify stores to work in a more flexible way for advanced data teams. With the beta release of this new connection, Littledata is now extensible for a range of ETLs, data collection platforms (like Snowplow) and data warehouses (like Google BigQuery). [subscribe heading="Learn more about Littledata Plus" button_text="learn more" button_link="https://www.littledata.io/app/enterprise"] Our new Measurement Protocol connection makes it easy to get complete sales and marketing data, just as you would with Littledata's Shopify to Google Analytics connection, but in a data warehouse of your choice. Benefits include: Capture and send complete client-side (browser) and server-side events, in a unified format, following the Google Analytics standardSpecify any endpoint for data collectionRelay exactly the same events as you see in Google AnalyticsExport real-time data to Google BigQuery, without paying for GA 360Pipe into a data warehouse using tools such as OWOX and Snowplow Read the developer docs here. The connection is currently in private beta for Littledata Plus customers (Plus and Enterprise Plus plans). Please contact us for early access.
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