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.

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.[0].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.

At Littledata we know that page load speeds are essential for ecommerce success, and we have made some major improvements to our Shopify apps this month to improve both page speed and data accuracy. Having benchmarked over 20,000 ecommerce sites, and worked closely with larger DTC brands on Littledata Plus plans, we are well aware that technical factors such as page load speed are major drivers of ecommerce conversion rates. We have always had a minimal, super-fast script and GTM data layer, but v9 brings this to a whole new level. [subscribe] What’s new in LittledataLayer v9? The need for speed is driving some of our customers to headless setups, but for many stores there are lots of optimizations to be had from their existing Shopify theme and apps. Littledata’s main advance in this area is our server-side tracking, which means that our app has zero impact on your add to cart, checkout or payment steps. So the changes in v9 are focused on the landing pages, product listing pages and product details pages. The latest update improves both page speed and the accuracy of the data we track Some of the major improvements in LittledataLayer v9 are: Tracking all product list impressions, on whatever pages they are displayedThe correct product variant is tracked, if the listing is for a specific variantProducts loaded after the initial page load (i.e. "lazy-loaded" products) will also be trackedListing pages of more than 50 products (e.g. infinite scroll pages) are tracked In addition we’ve improved how some types of checkout are tracked, to ensure the marketing attribution of the order is correct, for: Buy Now buttons leading to an accelerated checkout (e.g. Paypal, Google Pay)Headless stores leading to a Shopify checkoutCustom checkouts which do not reuse the same Shopify cart token See our help center for more details about how tracking product list views works as the user scrolls down the page. All these changes will be automatically added for current customers, unless you opt out and choose manual updates, in which case you will need to manually upgrade. Please contact your account manager if you are unsure which option to take. [note]Unless you opt for manual updates, we will now automatically update the snippet Littledata adds to your Shopify store[/note] How does v9 of the Littledata tracking script improve page load speed? To send accurate product list views, product list clicks and product detail views, our app builds a data layer containing all the products on the page. This is true for both our Segment app and our Google Analytics app in the Shopify app store. Building this data layer on Shopify’s servers took time before the page was ever seen by a user; in this improved version we get the product data after the user has interacted with the page. This results in almost no impact to page load speeds from adding Littledata’s app, as measured by PageSpeed Insights - improving the score from 62% to 70%. And yes, a score of 73 out of 100 is not very impressive...but for our test store we haven’t done all the good things you should be doing to optimize your store, like compression and lazy-loading of images. So whatever your page speed was before the improvements, it should be up to 10 percentage points higher now. Speed test So how did we make the latest snippet faster? To start, it’s no longer requiring the same liquid code. We can see the difference using Shopify’s speed profiler extension for Chrome. Before the changes Shopify is spending over 80ms (out of 155ms total) processing the LittledataLayer snippet - and this test store does not have a particularly complex list of products. After changing to v9, we see this has dropped to less than 1ms, because now all the product data is fetched asynchronously from Shopify’s APIs as the user interacts with the page. The good news is that this comes at no cost to data accuracy. Our script already tracked the product impressions after the page load - now we wait to get the product data until it is really needed. As a key part of the modern data stack for DTC brands, we are always investing in efficiency and accuracy at Littledata. Schedule a demo to learn more, and let us know if you have suggestions for further technical improvements! [subscribe]

If you’re using Shopify’s default Google Analytics tracking you might have noticed that the revenue in Google Analytics never matches what you see in the Shopify dashboard. This is a big problem: missing orders means orders that can’t be attributed to marketing campaigns, whether those channels are paid or organic. Littledata’s improved Google Analytics app for Shopify increases order throughput to Google Analytics from worse than 90% to better than 99.9% -- and it works automatically in the data layer. How big is the problem? We sampled a set of larger DTC brands on Shopify, together processing 50,000 orders a month through a standard Shopify checkout. Looking at a month of traffic, we compared the paid orders for these Shopify stores with the Thank You pages tracked in Google Analytics. Remarkably, only 88% of orders were tracked on average, ranging from 78% tracked in the worst store setup to 96% in the best store. That is a big loss. For every 10,000 orders processed, 1,200 were going missing. Assuming each of those customers cost $50 to acquire, that is $60,000 of marketing spend which can't be attributed to sales. Whatever the CAC for your ecommerce brand, you can’t afford to miss significant data like this about transactions, not to mention the marketing campaigns that led to those sales in the first place! For every 10,000 orders processed, 1,200 went missing Revenue aside, what about those 1,200 customers who are likely still being retargeted by abandoned checkout campaigns, even though they did complete the checkout process? There is a good case to be made for remarketing to your best customers for upsells, cross-sells, referrals and more. But remarketing to your new customer base as if they never made a purchase is certainly bad business. And it gets worse. When I looked at 10 stores that have non-standard checkout setups, using apps such as ReCharge or CartHook, the percentage of orders tracked (excluding recurring orders) ranged from a pathetic 9% up to a disappointing 70%. Shopify’s order tracking relies on customers seeing the Shopify Thank You page, and many other checkouts do not immediately redirect there. What are the main reasons for missing transactions in Google Analytics? Littledata has had five years of experience debugging GA tracking, so at this point we’ve pretty much seen it all. In fact, it's the most common question our sales team hears: why doesn't my data in Shopify match my data in Google Analytics? The ecommerce ecosystem is constantly evolving, including headless setups and subscriptions in the Shopify checkout. But some things remain the same. The most common problem areas for disappearing orders are: 1. Users not waiting for the Thank You page to load Many tech-savvy buyers know that your store will email them an order confirmation, so if they’re in a hurry - and the thank you page takes a few seconds - why should they wait? This is especially true with payment gateways like PayPal, which have their own payment confirmation page. 2. Thank you page overloaded with marketing tags Most order tracking relies on a script to fire on the thank you page, and if your store has lots of these scripts then it could take 10+ seconds before the crucial Google Analytics script is run. Customers won’t wait 10 seconds to see a page which has no value for them. 3. Draft orders paid at a later date Does your store create draft orders? This is more common for B2B stores, and means the order is completed well after the customer web session finishes. That means no thank you page, so no way to track the orders in a standard GA implementation. 4. Third-party checkouts That Thank You page on Shopify may never appear at all if your store uses third-party checkouts. 5. Recurring orders Like paid draft orders, recurring orders are payments that happen outside of the customer’s web session. The user never goes through a checkout or sees the thank you page. 6. Duplicate tracking Refreshing the order confirmation page, or clicking through on an order confirmation email to view the page again, might cause another transaction event to be fired from the page. [tip]Get the free ebook about why Shopify doesn't match Google Analytics[/tip] How is Littledata’s tracking different? Littledata offers server-side order tracking, hooking into the order creation in Shopify after the payment has been made. That allows us to track draft orders paid after the event, recurring orders, and orders through channels like Amazon that don’t use the Shopify Checkout. It also allows us to add refunds back in real-time, so you can track net sales against marketing channels. Littledata de-duplicates all orders, so an order is only ever reported once - giving a 100% match with what is in Shopify admin. Server-side tracking ensures complete analytics If you want to compare like-for-like, as I did for this article, our app also sends a ‘Thank you page’ event (in the same way the order tracking done in Shopify’s standard setup). This event can also be used to trigger Google Tag Manager tags, using the built-in GTM data layer. Interested in improving your Google Analytics setup? You might be interested in 6 common reasons why GA is not accurate and how Littledata’s Google Analytics app works. [subscribe]

Who's setting the bar for subscription ecommerce in five core industries? Join our free webinar with UWP as we discuss and vote on industry-leading subscription brands, while sharing tips to help you keep up with the best! Five expert panelists from Littledata, LoyaltyLion, Underwaterpistol and ReCharge will do five rounds of website evaluations — one per industry — for fashion, beauty, food & drink, fitness and homeware.  Each audience participant will get the chance to vote, helping our panelists decide on the final winner in each industry! Save your spot now to join the live webinar on the 15th of April, 4-5 PM BST: Save your spot  https://youtu.be/4Q0Q7p03FmM About Littledata Littledata automatically fixes tracking for Shopify stores, offering complete marketing attribution, accurate sales data, and custom dimensions for lifetime value reporting. Littledata has been a leader in the subscription analytics space since we launched our first Shopify app in 2017, so this is an especially exciting opportunity to share not just our favorite subscription brands, but those who have been using data-driven strategies to accelerate growth. We now have advanced integrations with all of the top subscription apps, including ReCharge, Bold and Ordergroove. [tip]Ready for data-driven growth? Download our free ebook on ReCharge analytics[/tip] Whether they have focused on organic marketing and brand building (hello, Instagram!) or used cohorts and daily analysis to optimize paid channels for higher customer lifetime value (LTV), brands like Craft Gin Club and Dry Farm Wines are leaders in the subscription space. We look forward to debating the pros and cons of different subscription setups! Sign up for the free webinar >>> About UWP Underwaterpistol is one of Littledata's leading agency partners for Shopify Plus stores, specializing in design and development, growth marketing and Shopify migration. UWP does more than just launch a shop, they provide hands-on support to maximize their customers' ROI and build proven success strategies for each customer. Sign up for the free webinar >>>

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"]

We are excited to announce a new Ordergroove connection. Any Shopify store using Ordergroove for subscriptions can now take advantage of Littledata's server-side tracking for advanced analytics. The new connection lets you automatically track online sales, marketing, and recurring payments in Segment, Google Analytics, or any connected data warehouse or reporting tool. What's more, it is available on all Littledata plans at no additional cost. Many Shopify stores are finding success with subscriptions, whether that's all or part of their online business. And this year we expect even more brands to move to subscription platforms like Ordergroove rather than trying to build and maintain in-house solutions to manage subscribers. This is especially true for larger DTC brands on Shopify Plus. Ordergroove integration with Google Analytics Ordergroove is a popular subscription solution for larger brands on Shopify, Salesforce, Magento and BigCommerce. Ordergroove offers a single checkout experience for Shopify Plus merchants, and brands like Intelligentsia Coffee and 4Ocean use Ordergroove’s integrated cart experience to maximize recurring revenue. Ordergroove's technology partners offer a range of integrations to help you scale. Littledata's new Ordergroove integration offers a seamless data pipeline for any Shopify store using Ordergroove for subscriptions. (Coming soon for BigCommerce too!) Google Analytics Google Analytics is extremely powerful once you know how to use it. Littledata has long been a leader in subscription analytics, and GA is our tool of choice. We're also especially excited about GA4 these days. But Google Analytics tracking often goes wrong for Shopify stores, resulting in order throughput of less than 90% (we have a good ebook on this). Common issues include: Lots of "Direct" traffic (transactions not linked to browsing behavior)Issues with thank you page tracking (doesn't load completely, too many marketing tags, etc.)Recurring orders either not tracked at all or look like orphan sessionsCustom themes breaking Shopify's default GA integration We built Littledata to fix these issues automatically, especially for subscription stores, where seeing details like LTV by channel can make or break a business. Littledata uses a combination of client-side and server-side tracking to give you one source of truth in Google Analytics: Complete sales data, including subscriptions and refundsAccurate marketing attribution for all transactions, including recurring ordersCustom dimensions for customer lifetime value (LTV/CLTV)Payment gateway trackingAnd much more! The Ordergroove integration works automatically with our Shopify/Shopify Plus to Google Analytics connection. You can install the connection directly from the Shopify app store. After installation, follow this quick guide to our recommended Google Analytics setup, which includes a special View in GA for one-time orders and first-time subscriptions (ie. filtering out recurring payments). [tip]Eager to track subscription lifecycle events? Sign up for beta access to v2 of our Ordergroove connection[/tip] If you are using a headless Shopify setup, please see our guide to headless tracking. Google Tag Manager Ordergroove works directly in the Shopify checkout, and Littledata's GTM and Google Analytics data layer makes it easy to track the pre-checkout journey as well as what happens in the checkout funnel. We add detailed events which you can use to build funnels or trigger other marketing tags in Google Tag Manager (GTM). At the same time, many brands find that our default schema is more than enough to fill their data needs and nothing custom is needed. Either way, our ecommerce tracking is highly scalable and extensible. Book a demo to learn more -- we are happy to chat about your data stack and see if Littledata is a good fit! Ordergroove integration with Segment Littledata also sends complete ecommerce events to Segment to match their ecommerce spec. Whether you are just considering Segment implementation or already far along the journey of using Segment for your data warehouse and marketing destinations, let our Shopify source for Segment do the heavy lifting so you can get back to business. Book a demo to learn more. [subscribe]

By now you know that Littledata sends accurate ecommerce data to Google Analytics. But how does it work? In this new video, we cover Littledata's Enhanced Ecommerce tracking for Shopify stores. Littledata's Google Analytics connection for Shopify stores uses a combination of client-side and server-side tracking to guarantee 100% accurate data. During the automatic installation process, Littledata adds a data layer and tracking script to all your Shopify store pages. We also add a set of webhooks to make sure everything is captured. https://www.youtube.com/watch?v=-c7ULfatrWU There are many advantages to this approach: On the client side... Works with Google Tag Manager (GTM) Faster page speed Consistent journey tracking On the server side... Ensures complete event capture for the checkout flow Safe & secure checkout process All sales & refunds are tracked Works with headless Shopify, multi-currency stores, and more! Accurate marketing attribution for Shopify & any subscription checkout [subscribe] Littledata sends these events to Google Analytics in three categories: Shopify Order Affiliation ReCharge (for stores that have a ReCharge subscription checkout) The Shopify (Littledata) event categories include the combined client-side and server-side tracked event actions, as follows: The Order Affiliation (Littledata) tracks each Shopify order as an event action, with the e-commerce affiliate type as its event label: For Shopify stores that use ReCharge, we send all customer lifecycle events in Google Analytics under the ReCharge (Littledata) event category: Analyze growth rates and subscriber behavior in greater detail. [note]In GA4, the latest version of Google Analytics, there are no default ecommerce reports. Learn more about ecommerce reporting in GA4[/note] Resources Watch a quick demo video Learn how to track the Shopify checkout funnel (and the ReCharge and CartHook checkouts) Check out our Shopify to Google Analytics FAQ  Subscribe to our YouTube Channel for more videos about ecommerce analytics