Category : Segment
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.
Top 7 rule-based audiences for ecommerce marketing
Rule-based audiences are customer groups or segments derived by customer activities. It sounds simple, but rule-based audiences can be a game changer -- and too many DTC brands miss out on the basics of this powerful type of customer segmentation. In ecommerce, rule-based audiences can be made using transactional activities (checkout date, coupon applied, etc.), marketing actions (email opened, promotion entered, etc.) or even product details (eg. type of product, color or type purchased). Ecommerce companies use the intersection of these events to group customers for the purpose of reporting, remarketing, targeting, and other customer enrichment activities. But one size doesn't fit all. Let's take a look at the top rule-based audiences and how they are used in ecommerce marketing. Benefits of rules based segmentation There are a number of benefits to deploying rules based audience recipes in your business. Whether you are a small-to-medium sized business, fast-growing startup, or have been around the block for some time like Littledata customers Dr Squatch and Rothy's, audience recipes are the building blocks for broader, innovative ways to segment your customers. Rule-based audiences can help you increase customer retention while improving product visibility in the crowded ecommerce marketplace Powerful tools like the Adobe Experience Cloud have highlighted rules-based personalization and audience building as a core part of their feature set. As they put it, "With rules-based personalization, you’re in the optimization driver’s seat." We agree, but with traditional enterprise tools that type of personalization can get really expensive. The good news is that brands using a modern data stack don't necessarily need to shell out for Adobe. Rule-based audiences can now be used by any ecommerce store, no matter how big or small. Here are some of the key benefits: Increase personalization through tailor-made product marketingImprove existing products and/or servicesIncrease upgrades and product upsellingEnhance profitability through the targeting of high-value customersIncrease retention with automation and buyer stage recognitionFurther marketing reach of customer types for remarketing, targeting and look-a-like audiencesEnhanced visibility and reporting of customer cohorts for tracking new acquisition and customer lifetime value Rule-based segmentation results in a hyper-personalized approach to directly influencing your customers’ experience. The ability to be attentive during each stage of the customer’s lifecycle allows for a better understanding of what drives good and bad experiences. Recipes for the top 7 rule-based audiences There are tons of different audiences you can build, but 7 always come up for successful DTC brands. In our case, we call them recipes, as they are the right number of ingredients to profile your customer base. X and Y in these examples will depend on your particular business: what you sell, how you sell it, and how often it makes sense for an ideal customer to come back and make a purchase or referral. Audience NameRecipe⭐️ First Time PurchasersCustomers who have made their first purchase in the last [X] number of days⭐️ Repeat PurchasersCustomers who have made at least 2+ purchases in the last [X] number of days⭐️ High SpendersCustomers who have made a purchase with order value greater than [$Y] in the last [X] number of daysAbandoned CheckoutsSite visitors that have added items to their shopping cart, but have not purchased in the last [X] number of daysBargain HuntersSegment of customers that have applied a promotional code on more than 1 purchase in the last [X] number of daysRecent BuyersCustomers who have made a purchase in the last [X] number of days⭐️ Inactive CustomersCustomers who have not made a purchase in the last [X] number of months*Additional segments include Loyal, Cancelled Customers, Location-based, Personalization (age, gender, preferences, income) Three audiences you should build today, with downstream activation examples All of these types of segmentation are potentially useful, even transformational, to your business. So where should you start? Today I will focus on the four most common and effective audience recipes that can generate immediate value to your store’s ability to identify, engage and enrich your customers’ experience. As highlighted above, those are: First-time purchasersInactive customersHigh spendersRepeat buyers To make things even clearer, we'll even combine High spenders and Repeat buyers into a high-LTV segment: your best possible customers, big spenders who are also loyal to your brand. 1. First-time purchasers First Time Purchasers are a good starting point for audience segments. The ability to identify these customers early will pay big dividends into maturing their relationship with your brand and products. Also, first-time customers are always the most likely to engage with your content (for example, opening welcome emails or sharing on social media), which ends up increasing the return on your investment and the potential for longer life cycles. How to Create a Welcome Email Template via Omnisend How to identify? Utilizing Littledata's order event tracking from your Shopify store, you can identify Order Completed in the last [X] number of days with a Customer Created event in the same time frame. How to activate? A great opportunity is through personalized welcome emails. By connecting to your ESP (eg. Klaviyo, MailChimp, Iterable) and building a customized message to all first time customers can be the first step to long-standing customer relationships. 2. Inactive customers Inactive Customers are a great win-back opportunity to gain customers back that have been inactive (or not purchasing) in a particular period of time. When a customer has been deemed inactive it’s too late to start formulating a strategy on returning them to your active customer pool. Instead building a strategy to identify, entice, and track appropriately is a must in any customer-focused business. Drive Repeat Purchases To Your Shopify Store With Automated Emails via Privy How to identify? Utilizing Littledata's order event tracking from your Shopify store, you can identify customers who have (at one-point) had an Order Completed event and with no purchase activities in the last [X] number of days. How to activate? Winback or revive email campaigns catered towards time-sensitive discounts, hyper-personalization (reference specific product categories a customer engaged or purchased in the past), summaries of product improvements, and membership benefits are effective strategies. Utilizing your current ESP, SMS, or retargeting platform alongside these customer groups can push once-active customers to return. 3. Repeat buyers & high spenders Repeat Buyers & High Spenders are the backbone of your business. As the tenured marketer would attest: “It’s easier to keep a happy customer than to find a new one”. Building customer loyalty requires a business to deliver on what is promised and to do so with their highest-value customers in the right channels and messaging. How to identify? Utilizing Littledata's order event tracking from your Shopify store, you can identify customers that have completed Order Completed events and total purchase count, purchase total, and revenue collected, during a [x] period of time and [x] number of times. Google Analytics users can also export data based on specific custom dimensions for LTV: Littledata – Lifetime Revenue Littledata – Purchase Count Littledata – Shopify Customer ID How to activate? There are several options here, including email and SMS (texting). SMS is a great tool to continuously engage with your customers. Invitations for users to sign-up for a loyalty program to provide exclusive offers or to release product updates can come simply through a users’ most desirable medium - their phone. With SMS boasting a +95% open rate, it's the most effective way to have a two-way connection with your customer and showcase value-added services. For Littledata's Shopify Plus customers, the most popular platforms for this type of engagement are Yotpo and Loyalty Lion. Technology for activating rules based segmentation Leveraging modern technology furthers the ability to do so repeatedly and with best-in-class platforms. Here are two examples of leaders in that space: Segment (sometimes called Segment.com) and Hightouch. Hightouch Hightouch syncs the data from your data warehouse to the tools your business relies on. It’s called operational analytics and it allows customers to leverage their existing technology (ie. your data warehouse) to pipe customer data to downstream platforms for activation, engagement, and other business activities. Since Littledata's no-code event collection is captured downstream in your Google Analytics platform, customers can leverage that same data when it is stored in their data warehouse. Modeled inside the platform with out-of-box SQL logic, segments can be then pushed automatically (and scheduled) to deliver on the intended goals. In fact, that's one of Hightouch's taglines: No scripts. No APIs. Just SQL. Segment Segment is a customer data platform (CDP) that integrates cohesively with Littledata's no-code event collection. Segment allows customers to integrate data from a catalog of sources (including the Shopify source, maintained by Littledata) and activate to destinations for customer engagement, activation and reporting. Inside the platform there are features that allow customers to create personas or audience segments, deploy functions, and build out layers of automation to seamlessly leverage their platforms’ source data. [tip]See what's new in Littledata's Shopify source for Segment, including more consistent product properties and enhanced Personas matching [/tip] Littledata Littledata is designed for the modern stack, whether you're using just a couple of tools such as Google Analytics and Data Studio or a whole modern data pipeline (eg. Segment, Fivetran and Redshift). If you're using a Shopify or BigCommerce checkout, you can use Littledata's analytics connectors to capture complete sales and marketing data and send it downstream. It's the easiest way to ingest the data you need to create enriched audience personas, and the only way to get 100% accurate ecommerce data automatically with extensive, ongoing development efforts. Not sure which tools you need? Book a demo with our data experts to discuss your analytics plan.
Property and destination updates in our Shopify source for Segment
Over the last 6 months, we’ve continued to enhance Littledata’s Shopify source for Segment to work with any modern data stack. We have focused on providing a more comprehensive range of events and properties to sync with any destination in Segment, including email marketing tools, data warehouses, and Segment Personas. Our Segment connection uses a combination of client-side (browser) and server-side tracking to ensure 100% of your Shopify store data is sent to Segment. Littledata automatically integrates with Shopify and Shopify Plus sites to enable complete ecommerce analytics, including sales, marketing, customer, and product performance data. Recent updates include better matching with Personas, more consistent product properties, and more. Here are some highlights. Tracking plan for Segment Protocols We've written a full tracking plan and event schema, which is ready to upload into Protocols to prepare for robust data consistency in your data warehouse. Better matching with Segment Personas You can now choose which userId to use for Segment events from a standard list of common identifiers: Shopify customer ID - This is the default for new installs. Recommended if you have a simple Shopify setup with minimal integrations. Hashed email - The MD5 email hash is useful if you have other marketing platforms sending traffic where you know the email of the visitor (e.g. email marketing like Bronto or Marketo), but not their Shopify customer ID. Email - The email identifier is recommended when other platforms use the email and can’t hash it, and you are comfortable with the privacy implications. None (no identifier) - Choose “none” if user identity is already handled by your Segment implementation and you only need the extra events powered by Littledata's Shopify source. All user traits below are now being sent in the context.traits, and are synced with your CRM destinations every time the customer record in Shopify is updated. Trait Description Type createdAt The date customer record was created Date customerLifetimeValue The total spend of customer on the Shopify store Double default_address.street The customer’s default street address String default_address.city The customer’s city address String default_address.postalCode The customer’s ZIP / post code String default_address.state The customer’s state address String default_adress.country The customer’s country String description The customer notes String email The customer’s email address String firstName The customer’s first name String lastName The customer’s last name String marketingOptIn The marketing_opt_in field from Shopify customer String phone The customer’s phone number String purchaseCount The number of orders by this customer Integer state Whether the customer account is enabled (user has opted in) or disabled String tags The custom tags applied to the customer String userId Chosen user identifier, defaulting to Shopify Customer ID Double verified_email Whether the customer has verified their email Boolean Import historic Shopify orders into Segment For Enterprise Plus customers we can now import orders and refunds from before the date Littledata was connected to Segment. This allows you to build a complete customer record in destinations that support historic events, such as a data warehouse. If you are already a Littledata Plus customer, please contact your account manager to discuss setting up an order import. If you haven't yet tried Littledata or are still investigating solutions for you data stack, book a demo today with one of our data experts. [subscribe] Consistent product properties across all events We understand you need a consistent set of product properties with every ecommerce event to make analysis easier. For example, the product image URL is available within a Product Added event to make it easy to set up dynamic product retargeting campaigns. Previously, we only got the following properties from Shopify’s webhooks: shopify_product_idshopify_variant_idname (title)brand (vendor)sku And now we add these extra product properties for all events: variant (variants.title)image_url (from images..src)cart_id (only with Product Added / Product Removed)urlcompare_at_price (variants.compare_at_price) Extra revenue properties We’ve added more reporting flexibility with how we send revenue data to Segment. Specifically, on Order Completed and all Checkout events, you will now see a subtotal = (product revenue including discounts). For the Order Completed event only, your store can opt in to an additional revenue property (product revenue excluding discounts, shipping and tax) via the Littledata application. Revenue is a reserved property in many Segment destinations. Opting in will override the total property sent to Google Analytics. Supporting the Iterable email destination Iterable is a cross-channel marketing platform that powers unified customer experiences and empowers you to create, optimize and measure every interaction across the entire customer journey. With this update, when an Iterable campaign leads to an Order Completed event the event properties will contain campaignId and templateId. To get these extra properties, you will need to edit the LittledataLayer setup to track the iterableEmailCampaignId and iterableTemplateId cookies. In addition we send an email field with all events linked to a user, so Iterable and other email marketing destinations can use the events. Supporting the Google Analytics destination in Cloud Mode In Cloud Mode, Segment will send event data to Segment’s cloud servers, and from there, we will translate and route that data to Google Analytics. This reduces the amount of third-party code on your site and you will be able to replay historical data in Google Analytics. We are happy to announce that you can now switch Google Analytics connection mode to Cloud Mode to relay events to GA from Segment's servers. This will increase page performance and provide greater control of the schema. More Subscription Event Properties On Subscription Created, Subscription Updated and Subscription Cancelled events we have added: statusproduct_id = shopify_product_idname = product_titlepricequantityskushopify_variant_idvariant = variant_titleorder_interval_frequencyorder_interval_unit On the Subscription Cancelled event only we have: cancellation_reasoncancellation_reason_comments And on the Charge Failed event we added: error_type Change of product ID used in Segment events Previously, we used the product SKU for client-side events to be consistent with the GA destination. From this month, we have changed this to send the Shopify product ID as the product_id field in Segment for all events. Ability to send anonymized IP instead of full IP to Segment Segment’s AnalyticsJS library sends the whole IP address by default in Track and Page events. This is contrary to our GDPR recommendations, and we now set context.ip with the last octet (3 digits) anonymized. This still allows geolocation of the events, but ensures IP addresses are not accidentally captured in end locations.
Optimizing Littledata's Shopify tracking script for speed and accuracy
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]
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"]
How to integrate ReCharge with Segment for advanced analytics and retargeting
Many merchants use Littledata's advanced ReCharge integration to track recurring orders and calculate lifetime value in Google Analytics, but did you know that our ReCharge connection can also send data to Segment? Our Shopify source for Segment makes it easy to push that same customer event data on to hundreds of marketing and data platforms. As an increasing number of top DTC brands on Shopify are building analytics stacks to enable advanced personalization and segmentation in addition to marketing analysis and data warehousing. Subscription analytics has been a core part of our product development since the beginning at Littledata, and the continued development of our Shopify source for Segment has unlocked a new realm of possibilities here. Benefits of integrating ReCharge with Segment Here are some of the ways that Littledata + Segment + ReCharge can improve your event data pipeline and power your analytics. An added benefit from our recent updates (Segment v2) is the ability to improve customer engagement with tags and triggers based on subscriber behavior. Push ReCharge subscription events into your data warehouse Joining your ReCharge and Segment data is a seamless way to get all of your ecommerce data into a data warehouse, automatically cleaned and deduped. Littledata’s Segment connection (combined with our ReCharge connection) syncs a range of common customer events from Shopify and ReCharge to any of Segment’s 34 supported raw data destinations. The events that we send include: Subscription CreatedSubscription UpdatedSubscription CancelledOrder ProcessedCharge FailedCharge Max Tries ReachedPayment Method UpdatedCustomer Updated All of these events are sent with shopifyCustomerId, subscriptionId and other fields to enable them to be aggregated into user-journey reports. So you can build your own data warehouse integration with ReCharge’s APIs and end up dealing with deduplication, high throughput and low latency. Or you can just trust Littledata and Segment’s experience in processing billions of events to handle that for you. Many of our larger customers on Littledata Plus plans are experimenting with data warehouses, and we are happy to discuss our solution to see if it's a good fit with your data needs. Feel free to book a demo to learn more. Track recurring orders and Customer Lifetime Value (LTV) on any platform Calculating LTV for subscription ecommerce can sound complicated, but it doesn't have to be. Littledata pushes every recurring order processed by ReCharge into the destination of your choice, so you can run analyses of where the long-term, high-value customers came from - and know if those customers interacted with your brand previously, as well as the original marketing channel or touch point. And it's not just about analysis. Integrating ReCharge with Segment allows for more sophisticated cohort-building and retargeting. Imagine you could spot the common patterns that link your top 100 most valuable customers, and then automatically build a lookalike audience to target 10,000 people just like them. That’s exactly what Littledata + Segment’s Facebook Custom Audiences destination allows you to do! [subscribe] Analyze subscription behavior with Kissmetrics or Mixpanel Kissmetrics and Mixpanel made their name as analytics for subscription businesses, with features focussed on analyzing customer churn and retention. Littledata’s connection can push subscription events to either platform, linking them with all the pre-purchase, pre-registration events to understand how the customer was acquired. Combining Shopify and ReCharge events in one analytics platform gives you the complete picture of the customer journey. [note]Wondering which unique identifier to use for your Segment setup? Confused about Cloud Mode vs Device Mode? Check out Littledata's Segment developer docs for Shopify[/note] Build custom email funnels Segment can also send events to email marketing platforms such as Klaviyo and Iterable. You can use recurring order events, or subscription cancellation reasons, to create highly segmented email campaigns. Here’s an example of how you could use those events in a Klaviyo report: Post-purchase events from Shopify like Fulfillment Updated or Order Cancelled could also trigger transactional emails that match your brand messaging. For example, an email could notify a customer of an upcoming delivery and include the tracking number from Shopify’s fulfillment service. Reduce scripts loaded on the ReCharge checkout Adding extra tracking scripts (Google Analytics, Facebook, etc.) to the ReCharge checkout slows down the pages and increases risk of checkout abandonment. Littledata + Segment allows you to have zero tracking scripts on your checkout (we listen out for checkout update webhooks instead) and yet send checkout step events to any of over over 50 advertising and analytics destinations. [tip]Using a headless ReCharge setup? See our headless Shopify tracking demo[/tip] Working with Shopify unified checkout Are you thinking of moving to Shopify’s new unified checkout for a more seamless customer experience? The events we track will work in the same way - and you can track like-for-like checkout funnel drop-off across ReCharge and Shopify checkouts. [subscribe]
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.
Connecting Shopify to Segment: a smarter solution with Littledata
A few months back, we ran down a list of popular ecommerce reporting tools that Littledata integrates with. Today, we'll take a look at one tool in particular: Segment. When it comes to data, one thing is clear: every business should be using more of it. At Littledata, we believe data is your single biggest tool for success, whether it's breaking down your marketing channel attribution or deciding on a new campaign for your repeat buyers. Not only does data help you nail down what's working for your store and what's not right now—it also helps you make decisions for future success. With a flood of data tools on the market for Shopify stores (data lakes, business intelligence and dashboarding, funnels and segments) the search for the perfect data tool to fit within your tech stack can be overwhelming. It can also be tough to find a tool with all the right features for the right price. Fashion stores sell differently than coffee subscription stores, so it can be tempting to either build a custom tool yourself or hire an analytics consultant to do the heavy lifting for you. Maintaining multiple connections and integrations can also become a task in itself. This can lead to data fatigue, causing confusion and even costing you time and money. But whether or not you use an app for better Shopify tracking or you go with a consultant, one thing is clear for Shopify stores: driving your decision-making with data is no longer optional if you want to succeed in the current ecommerce marketplace. Plain and simple, accurate data is the best way to ensure you're getting the maximum ROI for your business. While our Google Analytics connection is popular among Shopify stores, thousands of Shopify stores (and Littledata customers) use Segment as their main tracking tool, including brands like Nuun, ROMWOD, Kin, Cellucor, and more. Why do Shopify sellers use Segment? Segment is a streamlined way to clean, collect, push and pull customer data. The company has raised over $280 million and it continues to grow especially fast in the commerce vertical. Segment's Customer Data Infrastructure (CDI) is built around connections, protocols and personas (single user views), and the platform organizes connections in terms of sources and destinations. In other words, you can think about Segment as a single API for all of your customer data. [subscribe heading="Try the only recommended Shopify app for Segment" background_color="grey" button_text="Learn more" button_link="https://apps.shopify.com/segment-com-by-littledata?_ga=2.230718111.1271051167.1588608356-1545539486.1571747621"] As Shopify continues to push features for enterprise ecommerce, you don’t have to be front-page news to take advantage of Segment’s functionality; tons of mid-sized Shopify brands currently use Segment together with Shopify. But why? How do Shopify stores benefit from integrating Segment with their store? Benefits of connecting Shopify with Segment 1) Capture every customer touchpoint Littledata's Segment connection lets you use Shopify as Segment source. In other words, merchants can now automatically track every ecommerce touchpoint on your Shopify store, including: User/browsing behaviour Checkout steps Sales & refunds Customer lifetime value (LTV) Marketing metrics like customer acquisition cost (CAC) When merchants integrate Segment with Shopify, no touchpoint in the customer journey goes untracked. This includes multiple checkout steps, sales conversion data and lifetime value (LTV), arguably the holy grail of ecommerce metrics. What about subscriptions? If you are a subscription business using ReCharge for your checkout then you’ll understand how difficult it is to attribute your recurring orders back to the original marketing source. Furthermore it’s hard to keep track of what revenue is coming from first time orders versus recurring revenue. By using Littledata with Segment you can correctly attribute your ReCharge orders including the use of custom dimensions such as order count and customer LTV as well as lifecycle events such as customer created and subscription cancelled. [tip]Learn how to track subscriptions on Shopify with 100% accuracy[/tip] For those running a subscription store, the app integrates with ReCharge and Google Analytics so you can track all your subscription data. It also connects to your Facebook Ads and Google Ads for accurate marketing attribution and customer journey tracking. This way, you know which campaigns are actually working (and maybe more importantly, which ones are not). Tip: Hey, subscription stores! Now you can track all your subscription lifecycle events 2) Server-side tracking for complete accuracy Speaking of tracking, Littledata’s server-side tracking approach within Google Analytics beats out Shopify’s native reporting platform. For Segment users, server-side tracking ensures data is 100% reliable, which means better analysis and decision-making. 3) Quick setup Quick integrations should never be undervalued. Within minutes, Shopify merchants can have their stores armed with a steady data flow in Segment. Automated ecommerce tracking Like the popular Google Analytics connection for Shopify stores, Littledata's Segment connection uses server-side tracking to capture every step in your checkout flow, plus sales, refunds, product variants, and more. It’s the easiest way to ensure accurate, detailed data about sales and shopping behaviour. In fact, Littledata is the only recommended Segment integration for Shopify and Shopify Plus. Benefits include: Works with any Shopify or Shopify Plus store Server-side tracking for 100% accuracy Captures every touch point, including checkout steps, sales data and customer lifetime value (LTV) Analytics audit to check for accurate tracking The connection captures what happens on your Shopify store, then pushes that data to Segment so you can send it to hundreds of Segment destinations: Putting the data to use So what are some ways you can use this raw data as actionable insights? Better marketing automation Personalize and hyper-target your campaigns even more General ecommerce CRO Better reporting and analysis For example, you can push your Shopify data to tools including Hubspot, Salesforce, Mixpanel and Google Analytics. [note]Browse our Segment help guides for details about which events you can track with our Segment connection.[/note] Better actionable insights is really why Littledata built a single Shopify connection to be used as a source for Segment. By centralizing your data with Segment, you can ensure that you have data consistency when using the data across multiple destinations like Google Analytics, Klaviyo, Facebook, Friendbuy and Hotjar. Not only will this save 100s of development hours building and maintaining multiple integrations, but it also frees you to adapt your data stack for any opportunity, like debugging, testing and reviewing your data collection. Welcome to a truly smarter solution! Like we mentioned, Littledata is the only recommended Shopify connector for Segment. Want to give it a try? Our new 30-day free trials will give you a full month of accurate data so you can feel the difference for yourself. Our enterprise plans also include the option for custom Segment data audits, setup and reporting. We’re here to help you scale!
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