Category : Data Strategy
The Ultimate Guide to connecting Segment to Redshift (and other powerful analytics tools)
Cloud data warehouses offer a way for ecommerce companies to scale as the size of their data increases, promoting unlimited storage space, cost optimization and analytics horsepower. But where do you start? Are there no-code solutions that are also best-in-class? Segment is an increasingly popular way to connect website data to a data warehouse such as AWS Redshift. In this guide we'll take a close look at exactly how this works, and the pros and cons for your longterm company data needs. Using Segment to connect Shopify to AWS Redshift What is Segment? Segment is a powerful Customer Data Platform (CDP) solution, but it's also much more than that. Segment provides businesses the ability to organize customer activity events from various platforms to a broad range of destinations, One of those destinations can be a data warehouse - an ecosystem that serves as the centralized source of data collection. This includes the big three: BigQuery, Redshift, and Snowflake. The technology focuses on the tasks of collection, storage, and management of business data - with the purpose of turning operational data into meaningful information. For any company looking to harness the value of the activities gathered inside their CDP, it’s a no-brainer that bringing a data warehouse into the mix is the next best step. Amazon Web Services (AWS) and its data warehouse offering, Redshift, remains the market leader in this space because of its compatibility with data integration pipelines and analytics tools. One of your Segment destinations can be a data warehouse such as AWS Redshift For ecommerce sites this can be difficult to implement manually (not to mention maintenance time, costs and complexity!), but Littledata's Shopify source for Segment does this automatically. With Littledata’s capabilities, you have the ability to direct, track, and identify custom events across all critical customer activities, including across your Shopify website, whether that's a simple Shopify instance, a headless Shopify setup or multiple country stores doing international sales. Coupling that with Segment’s unified CDP takes powerful data to activation, and the ability to direct platform data to marketing channels for increased engagement, conversion and retention. Whether you want to use a data warehouse for deep analysis, audience building or real-time recommendations, Littledata + Segment + Redshift is a proven solution for Shopify stores. Setting up your Redshift data warehouse Segment's documentation portal gives a step-by-step breakdown of provisioning a Redshift cluster, configuring a database user, securing data ingestion, and providing a path to data collection into your Redshift instance. Breaking the process down in digestible chunks, here are the necessary steps to go from data to data warehouse: Choose the best instance for your needs: Dense vs. Compute StorageProvision a new Redshift Cluster: 5 simple steps from start to finishCreate a database user: Creating a user to manage your instanceConnect Redshift to Segment: Select sources, credentials, and go Redshift allows users to start small and scale up on-demand as needs grow Collecting events in Segment Event tracking is a critical part of the data collection process. Creating a plan tracking plan associated with measurable business outcomes, such as acquiring new customers, increasing retention and activating new leads, and mapping those outcomes to business goals, is an important step in the data journey. Understanding this relationship will provide guidance to the relevant events or actions that must be configured to successfully track. With Littledata's automated solution, you can avoid the blocking-and-tackling of configuring the best-in-class event strategies surrounding (client side) device-mode and (server side) cloud-mode events: Device-Mode events include Cart Viewed, Page Viewed, Product Clicked, Product Image Clicked, Product List Viewed, Product Shared, Product Viewed, Products Searched, Registration Viewed, Thank you Page Viewed Cloud-Mode events include Checkout Started, Checkout Step Completed, Coupon Applied, Customer Created, Customer Enabled, Fulfillment Created, Fulfillment Updated, Ordered Cancelled, Order Completed, Order Refunded, POS Order Placed, Payment Failure, Payment Info Entered, Product Added, Product Removed To streamline the process for ecommerce sites, Littledata's tracking script automatically sends events to Segment through its analytics.js library, making it easy to collect all the critical event activities associated with a customer’s store journey - from browsing behavior through the checkout funnel and repeat purchases (including recurring billing for stores selling by subscription). Additionally, from every event where this is an identifiable customer (from both device-mode and cloud-mode), Littledata will send an Identify call - the identification of a customer when the customer logs into your storefront, a last step of the checkout process, with the order, and also after a purchase with a customer update. With Littledata’s streamlined modeling, data can be accurately represented and pushed to downstream destinations, such as marketing activation channels and data warehouses. [subscribe heading="Littledata connects Shopify to Segment and your data warehouse" button_text="Book a demo" button_link="https://www.littledata.io/app/enterprise"] Connecting Segment data to your data warehouse Now that your Redshift instance is up and running, the next step is to connect to Segment and start collecting data into your data warehouse. There are two ways to complete this step - one, through Segment’s native migration, and the other, utilizing no-code data pipeline tools (recommended). Whichever process you choose, you will have the opportunity to push data out of Segment into your data warehouse environment and start utilizing it across your business. Option 1: Segment’s native migration As mentioned, Redshift data warehouse is one of the many destinations that Segment can send data to. You can directly connect to Redshift from within Segment to stream event data. Segment’s catalog provides direct integration to best-in-class data warehouses Essentially, it’s as simple as: Login to your Segment App and proceed to the Catalog sectionIn the top menu, choose DestinationsSelect Redshift in the Storage Destinations list After configuring your user permissions and selecting the data sources you would like to sync, you’ll enter in your credentials and connect to your data warehouse. Voila! Data will now be continuously replicated into your Redshift instance based on your plan: Free: Data refreshed (synced) 1x per dayTeam: Data refreshed (synced) 2x per dayBusiness: Data refreshed (synced) as fast as hourly As for historical data, all plans will allow loading up to 2 months of your historical data, with the Business plan allowing for full historical backfills. Since Segment provides an environment to support many, it requires a premium plan to collect complete history and sync data real-time. Segment’s infrastructure is suitable for instantaneous data collection to downstream points Option 2: Leverage data pipeline services The second way to get data out of Segment into your data warehouse is through data pipeline platforms. Data pipeline or ETL (Extract, Transform, Load) platforms, provide prebuilt integrations to over 100+ enterprise software sources, and focus on a maintenance-free structure where replica data is automatically transformed, standardized, and normalized on collection. The automated adjustment to schema and API changes, allows business users to streamline developer tasks in a no-coding required environment. Companies like Stitchdata ("Stitch") and Fivetran, leaders in the space, provide frictionless, subscription-based memberships that allow integrating data to data warehouse destinations convenient for any business size. ETL platforms streamline data from end-to-end and require limited technical lift To set up, simply sign into your console, click on the Segment icon in the available integrations, and enable. You will automatically be pushed into the Segment tool to confirm authorization and (another voila!) data will begin replicating. Stitchdata’s user-friendly interface for connecting platforms to destinations The benefits of cloud-ETL platforms, not only include their out-of-box integrations, but the list of features included to help visualize, maintain, and support ongoing data integration tasks: Over 100+ database and SaaS platform integrationsIn-app support including email alert monitoring and support SLAs14-day free trial to kick-off and vet the platform prior to fully onboardingSOC2 security compliant, encrypted communication and an AWS cloud backed environment Ecommerce data With the appropriate event tracking configured at data collection by Littledata, your data can be properly analyzed for ecommerce store performance. The downstream output can be properly displayed by: Customer behavior before, during and after purchaseOrder performance relative to average order value, add-to-carts, average order size, and cart abandonmentShopper engagement including product views and purchasesCoupon and discounting activitiesCustomer checkout funnel and stage of drop-offConversion rate and lifetime value With the emphasis on accuracy completed at the inception data collection stage, the ability to produce the above areas of performance becomes that much more straightforward. This means spending more time analyzing and visualizing data, then transforming and modeling data for analytical use. Empowering your data Once your data is available in your data warehouse, replicating frequently, and building history, it’s time to utilize it. That can come in a number of various opportunities, depending on your business needs. Most notably, companies will focus on transforming data into actionable blocks and pushing into business intelligence (BI) tools. Transformation To properly stitch event data together - say in the case to tie all interactions by a site visitor to achieve multi-channel attribution - companies can leverage existing packages that transform, marry and enrich data points. These packages - or prebuilt libraries - produce powerful results that end up restructuring data from their raw state to analysis-ready. Fishtown Analytics’ product dbt does just that, performing user-stitching, simplifying data structures, and speeding up data modeling to use instantly within reporting, analytics, or machine learning applications. Leveraging transformation can streamline data modeling and enrich data for analytical-use BI Tools Companies usually begin the conversation here, “I’d like to see a dashboard like X” or “Can we get a report showing Y?”. In fact, what they are looking for is a way to properly view data in digestible, actionable views. BI (Business Intelligence) tools do just that - whether it’s through data visualizations (dashboards), self-service analytics, or prebuilt reporting. Enterprise BI and SaaS tools like Looker and Tableau (like outlined in the table below) create the speedy path to data viewing. They can be simply connected to a data warehouse and publish dynamic views for instant performance tracking. Data can be presented in dashboards across many dynamic charts, tables, and graphs BI Tools Breakdown CategoryVendorsBreakdownMarket LeadersTableau, Looker, PowerBI, Mode, DatabricksEnterprise tier platforms with extended featuresRisersDomo, Klipfolio, Kissmetrics, SigmaSaaS-oriented products with cost on user and dashboard usePrebuiltGlew, Daasity, Dashthis, Rubix3Ecommerce focused with prebuilt visualsOpenDataStudio, MetabaseOpen-source/no-cost platforms So a straightforward reporting and visualization solution with the setup we've described in this article, would be to connect Shopify to Segment, then Segment to Redshift, then Redshift to Tableau. Learn more about how to connect BI tools to your Shopify data in Segment, whether as a Segment destination using alias calls or a dynamic view pulling from data in your warehouse. Another option is connecting reporting tools directly to Google Analytics data in parallel with your Redshift setup (for example, use Tableau on top of GA for marketing analysis and Looker on top of Redshift for deeper analysis and predictive analytics). Building for the future Companies that put an emphasis on building the foundational components of data ingestion, management and analytics early on see many benefits. Primarily, you are able to increase your ability to measure and understand your business properly. Data warehouses provide an opportunity to collect all of your store, site, customer, marketing, other relational data - all in one place. This creates a centralized view of your business and gives an upper hand to companies looking to take a data-driven approach to growth. Cloud tools and no-code options remove the need for technical resources, freeing up dollars that can go elsewhere without sacrificing the ability to use and analyze data. No matter the size of your business, taking data seriously is the first step to empowering your business for the future. Data warehouses are no longer the property of only mega enterprises. Want to build a modern ecommerce data stack but not sure where to start? Get in touch for a free consultation. [subscribe heading="Littledata connects Shopify to Segment and your data warehouse" button_text="Book a demo" button_link="https://www.littledata.io/app/enterprise"]
What's new in v2 of our Shopify source for Segment
We've a built a loyal following for our Shopify to Segment connection, and this month we've rolled out the next version, v2, with new events and enhanced functionality. As Shopify and Segment both continue to see unprecedented growth, Littledata is here to ensure accurate data at every ecommerce touchpoint. We've seen a surge in DTC and CPG brands on Shopify Plus that rely on Segment to coordinate customer data across marketing, product, and analytics tools. We have continued to develop our Segment integration to fit all of these use cases. [note]If you installed Littledata's Segment connection previously, please contact us to add the v2 events.[/note] About Segment v1 Last year, we worked with Segment to create a robust Shopify source for Segment users. The aim was to make everyone's job easier, from CTOs to ecommerce managers. Littledata's Segment connection v1: Captures all customer touchpoints on your store, both pre and post checkout Sends data to any of Segment’s hundreds of destinations Works seamlessly with Google Analytics Uses a combination of client-side and server-side tracking to capture browsing activity, orders and refunds Sends user fields for calculating customer lifetime value [subscribe] What's new in Segment v2 Since we launched the first Shopify app for Segment in May 2019, we have continued to make improvements based on user feedback and new use cases. The latest version of our Shopify source for Segment offers several updates and enhancements, including support for email marketing around order fulfilment events; tracking for a range of new order and payment events, including POS orders and order cancellations; and alias calls to support additional analytics destinations such as Mixpanel and Kissmetrics. Fulfilment status Many of our customers use Segment events to trigger transactional emails on platforms like Klaviyo and Iterable. One key email that stores want to customize is the 'Your order has shipped' fulfilment email, and so we now trigger a Fulfilment Update event when the fulfilment status of an order changes. This event includes status, tracking_numbers and tracking_urls (where the shipping integration allows), so the transactional email can include actionable details for the end user. These events can also be used in analytics destinations to look at fulfilment trends by product, or see how marketing campaigns around shipping match real-world delivery times. Support for email marketing Email marketing destinations such as Klaviyo, Iterable, and Hubspot, cannot use an anonymous identifier -- so our Segment connection now sends an email property with all events (when it is known), usually from checkout step 2 onwards. Where the email is captured on landing pages (e.g. popup forms) we also send this with the Product Viewed and Product Added events, to make it easier for you to run retargeting and engagement campaigns. Support for Kissmetrics & Mixpanel destinations To support seamless customer tracking in analytics destinations such as Mixpanel, Vero and Kissmetrics, Segment requires an extra alias call. Littledata ensures the pre-checkout anonymousId is added as an alias of the userId (used from checkout step 2 onwards). Learn more in our developer docs. Customer account creation On Shopify, every checkout (even as a guest) creates a customer record. This was already passed on to Segment with an Identify call and a Customer Created event. However, it is useful to know when this customer creates a password and creates a verified account with the store. For example, some brands use this event to trigger welcome emails or offer discounts. With Segment v2, we now send a Customer Enabled event when the user has confirmed their email address and created a Shopify customer account, with verified_email set as true. Payment of draft orders Some stores (especially B2B brands and wholesalers) create draft orders which are later paid. From November 2020, Littledata's Segment connection triggers an Order Completed event whenever these draft orders are paid, linking them back to the user session when they were created. POS orders Previously POS (point-of-sale) orders were excluded from Order Completed, as this polluted the revenue attribution in Google Analytics or other Segment destinations. However, as Shopify POS and other POS orders have become more popular, we now send a separate POS Order Placed event, so you can track the POS orders and choose whether to add them to your web orders. Payment failure After a customer goes through your checkout and completes an order, there is still a chance the payment fails, usually due to fraud checks. A new Payment Failure event allows you to track these failures, and see if they are more associated with particular marketing campaigns, geographies, products, or other factors. Order cancellations If the admin has cancelled an order, perhaps due to the product being unavailable, an Order Cancelled event is now triggered (including the cancel_reason). This is useful for both tracking/analysis and re-engagement campaigns. Product properties Last, but certainly not least, we've expanded the range of product properties sent with every product for better segmentation. Details such as shopify_variant_id, category and brand are sent with all client-side events and most server-side events. For more information, read our developer docs or schedule a demo today with an analytics expert.
Measurement Protocol connection for Shopify stores
We are excited to announce the beta release of a new Measurement Protocol connection for Shopify stores. As we continue to optimize Littledata for Shopify Plus, our team is always on the lookout for ways to help larger brands ensure a complete data pipeline, whatever your data stack might look like. Being able to send server-side events is one of the core benefits of the Google Analytics Measurement Protocol, so it was a natural next step to extend our advanced tracking for Shopify stores to work in a more flexible way for advanced data teams. With the beta release of this new connection, Littledata is now extensible for a range of ETLs, data collection platforms (like Snowplow) and data warehouses (like Google BigQuery). [subscribe heading="Learn more about Littledata Plus" button_text="learn more" button_link="https://www.littledata.io/app/enterprise"] Our new Measurement Protocol connection makes it easy to get complete sales and marketing data, just as you would with Littledata's Shopify to Google Analytics connection, but in a data warehouse of your choice. Benefits include: Capture and send complete client-side (browser) and server-side events, in a unified format, following the Google Analytics standardSpecify any endpoint for data collectionRelay exactly the same events as you see in Google AnalyticsExport real-time data to Google BigQuery, without paying for GA 360Pipe into a data warehouse using tools such as OWOX and Snowplow Read the developer docs here. The connection is currently in private beta for Littledata Plus customers (Plus and Enterprise Plus plans). Please contact us for early access.
Lunch with Littledata: Q&A with Chad Rubin, CEO of Skubana
This week, we're kicking off a new Q&A-style segment on the blog: Lunch with Littledata! We sat down (virtually) with Chad Rubin, Co-founder and CEO of Skubana, a multi-channel inventory management and ERP software working largely in the Shopify ecosystem. Let's dive right in! Q: How are your customers handling COVID-19? Thriving? In a drought? Somewhere in between? What we're seeing is essentials thrive. Brands that are providing non-discretionary necessities in the household are doing exceptionally well, and that's where we're building our pipeline. But also it's how Skubana has historically been built, through customers selling essential finished goods across multiple channels with multiple warehouses. Overall, what you're seeing in ecommerce is a shift of spending behavior. With quarantine in effect, the only way to purchase right now is online, not in store. So while ecommerce isn't necessarily immune to recessions, given the pandemic, we're seeing customers on the Skubana platform behaving in a way that is inconsistent with what we'd expect in an economic downturn. Q: How has Skubana adapted to the pandemic era? Honestly, as a retail operations platform, we're at the epicenter of this rush to be online and supply this surge in demand. Skubana enables both brick-and-mortar and online purchases, whether that's on Shopify, Amazon, eBay, you name it. As a business, we're also extremely focused on our employees. Once the risk of COVID-19 was made clear in early March, we implemented a company-wide work from home policy. It was the first time we allowed that to happen. And I believe that it's going to become the future of this company, to flourish "remotely." [note]At Littledata, here's why we believe remote work is more productive[/note] We've been able to adapt pretty quickly from a company perspective, but it's not all rosy. We've already had some disappointing casualties from customers who have been on our platform for years. So while there's a lot of momentum and encouragement, there are some cases where customers have closed-up overnight or have sought relief. And we work with those individual customers to help them see this through, given the circumstances. We've been very action-oriented and proactive in our efforts to make sure that they come out of this alive and in business. Q: You also run your own DTC store on Shopify. As a seller, how do you mitigate the costs of unpredictable shopper behavior, both before and after checkout? In addition to co-founding Skubana, I also run a direct-to-consumer home essentials e-commerce business called ThinkCrucial. So it's great that ThinkCrucial is an "essential" business. We supply home appliance parts and accessories. Again, we're right in the epicenter of panic buying, of people stocking up. And a symptom of that could be stock-outs. Luckily, we have Skubana to forecast the demand, to mitigate if we're running low on certain channels, to allow us to be flexible with inventory deployment, and so on. So that's been just an incredible case study for us. It has automated our entire business and allowed us to be more efficient and resilient. I initially built Skubana because of these issues I was experiencing with ThinkCrucial. I was unable to find a solution that could help me with all of these things at once. Another cool thing that we've done is implement the Bold Upsell app. Within the Skubana platform, it's easy to identify high-velocity products that people are buying all the time, especially in this environment. And we've been upselling those people with additional products that they should be buying as well. And that strategy has worked very well for us. That's a simple app that we've installed that we didn't have pre-COVID that has increased AOV for us. [tip]Did you know Littledata has an advanced Google Analytics connection for Shopify and Bold subscriptions?[/tip] Q: What are some "hidden" challenges of cross-border ecommerce? And some underrated solutions? First, I just want to shout out one more app that I think we've been leveraging more heavily during this time which is called Tone. It's a Shopify app that leverages SMS to re-engage customers who abandon their cart. So as people abandon their carts, we've enabled this app to catch that customer that left to get them back into the sales funnel, which also lowers acquisition costs. We've been able to recover lost dollars and lost baskets because of it. [tip]Struggling to reduce cart abandonment? We have you covered[/tip] In terms of cross-border commerce, it's been just business as usual for us. I think everyone's well aware that there are fulfillment delays during this time as warehouse employees are social distancing, and air cargo availability has decreased. The most important thing you can do is make sure you have the infrastructure to enable the movement of parcels. And of course, we use Skubana to make that happen. [tip]4 tips for Shopify Plus merchants selling internationally[/tip] Q: What are some "tricks of the trade" larger stores use (especially those running on Shopify Plus) to handle busy shopping seasons? This virus is preying on weak businesses. We've seen that COVID-19 is having the biggest impact on retailers that don't have their operations buttoned up, and still working with inefficiencies. One of those weaknesses is that people aren't leveraging technology to replace low-value, repetitive tasks. Right now, people should be leveraging any downtime to reinforce and build the foundation of their business with resilient operational software. That means implementing software that is nimble, agile, and not painful to deploy. Software that connects to all of their channels and warehouses to properly forecast and demand plan. That's table stakes right now. On top of that, brands need to focus on technology that facilitates customer connection and retention. You need to reach out to those customers and communicate with them to convert them into buyers. And not just one-time buyers, but consistent repeat buyers, which of course, extends their lifetime value (LTV). We're looking at new apps all the time on Shopify. We already have our foundation built on Skubana, but we're constantly trying to figure out how we "one-up" others and excel or accelerate our progress in this environment. Q: How does ecommerce look different for larger Shopify stores vs. smaller/mid-sized stores right now? So I think this downturn has been beneficial for many small businesses. I see good and bad with these unprecedented circumstances. We know that Shopify stores have been seeing Black Friday traffic every day of this pandemic. Additionally, we saw Amazon restrict certain items to FBA, which ultimately reinforces the need for diversification and a multi-channel strategy. Those that are positioned and diversified across multiple channels that have the right infrastructure to be able to support this uptick have been able to benefit. And a lot of those SMBs have built their sites on Shopify, so I think that's a huge positive for the small to medium-sized businesses. We saw sellers who focused exclusively on Amazon become significantly affected because they couldn't replenish the products during the FBA block. Also, Amazon didn't let you add new listings to their catalog for some time. So actually, we saw sellers move to Walmart and eBay because they were able to accept new products onto their platform. So a lot of new merchants and brands embraced other channels during this period and opened up. Another thing to note is that Google started offering free product listings. So I think that there might be a shift coming out of Coronavirus to expand as an SMB across many other channels. Q: How important is it to have accurate Shopify tracking & reporting? It's essential. If you're using multiple point solutions, like a purchase order app or a forecasting app, and you're just duct-taping them together, but they were never meant to talk to each other, your data is not going to be accurate. If you're using multiple point solutions, and you're just duct-taping them together, but they were never meant to talk to each other, your data is not going to be accurate. I've tried every other software out there. I developed Skubana out of the pain that I've experienced deploying those other point solutions and those fragmented pieces of software. Having everything in one place is vital so that you're able to ensure your products are in-stock and making you money. It means you are not spending your precious time doing manual labor to calculate how much inventory to reorder, when to buy, where to ship that new inventory to, which vendor needs the most lead time, etc. [note]Here's how you can get 100% accurate Shopify tracking[/note] Q: How do Skubana customers (merchants) use tracking to optimize performance? When you have a holistic solution for every part of your business, you're able to make more decisive decisions regarding growth, expansion, replenishment, and even cutting back. When you have a holistic solution for every part of your business, you're able to make more decisive decisions regarding growth, expansion, replenishment, and even cutting back. You need to have accurate data not just on orders coming in but on the inventory available across all warehouses, 3PLs, FBA, and fulfillment operations. Automating that is invaluable. And replacing human labor so you can have your team doing higher-value activities is the name of the game. To survive this, you need a resilient business that can scale as needed. As a retailer, you have to be more efficient with your staff and your business, and that's what Skubana merchants are doing with our platform. Quick links What you can track with Littledata's Google Analytics app for Shopify Littledata's top-rated Google Analytics app for Shopify Try Littledata free for 30 days (full month of accurate Shopify data)
Here's what Shopify merchants need to know about CCPA compliance
The California Consumer Privacy Act (CCPA) is now in effect, and every serious ecommerce site doing business in the USA should take note. So what do you need to know? The CCPA comes on the heels of a year rocked by privacy scandals and data inhibitions (e.g. Facebook and now Google), and California is the first US state to enact a complex online privacy act that appears to be up-to-date with how businesses actually transact online these days. Other states are expected to follow suit. In the words of the California Department of Justice itself: The California Consumer Privacy Act (CCPA), enacted in 2018, creates new consumer rights relating to the access to, deletion of, and sharing of personal information that is collected by businesses. It also requires the Attorney General to solicit broad public participation and adopt regulations to further the CCPA’s purposes. We certainly aren't lawyers here at Littledata. But we do help Shopify sites audit their analytics and ensure that no personally identifiable information (PII) is collected by Shopify stores in their Google Analytics setups, including Google Tag Manager (GTM). So while we don't have specific features aimed at CCPA compliance, we do have a number of features designed to help Shopify merchants follow best practices for data collection and reporting. Here's a quick guide to what you need to know about CCPA. My first dine-in restaurant CCPA notice. Not sure how I feel about it. pic.twitter.com/vU6ZiTCF8o — Jad Boutros (@secplusplus) January 4, 2020 What is CCPA compliance? In short, the CCPA is an attempt at limiting what can be done with consumer data, and making sure that companies don't use it without consumer knowledge. The media has often described the CCPA as California's version of GDPR, the European regulations that went into effect in 2018 (has it been that long already?), but in my view it's actually quite a bit different — both more comprehensive in terms of targeting what's actually done with consumer data after it's been harvested, and more specifically aimed at larger merchants, which in Shopify's case generally means successful DTC brands and others using Shopify Plus. It's clear that the act was written in a state known for both technical innovation and political hardball, though how it will be enforced is an open question. Initially it looks like civil penalties will be limited to $2,500 USD per 'violation' or $7,500 USD per each 'intentional violation'. The act has continued to go through a number of revisions and clarifications, including a number of new modifications posted for review on February 10th 2020. Some of the most interesting, in my view, are attempts at trying to define a 'household' that uses a website. The recent revisions suggest changing this: “Household” means a person or group of people occupying a singledwelling To this: "Household” means a person or group of people who: (1) reside at the same address,(2) share a common device or the same service provided by a business, and (3) are identified by the business as sharing the same group account or unique identifier. It makes sense that they're trying to clarify the end users here. But I wonder: are we going to get to a place where devices are 'people' under the law, corporations are 'people' under the law, and people are...ones and zeros? But I digress. You can read the complete law text of the CCPA online, and the California DoJ has also posted a legal overview with all versions of the law. But I've also included links to useful summaries below — the written law itself is pretty confusing if you aren't a lawyer! Who needs to comply? In short, if you're a larger ecommerce site with customers in California, you need to pay special attention to the CCPA. You are subject to the CCPA if you meet one of these conditions: Have an annual gross revenue of more than $25 million USD Annually buy, sell, receive for commercial purposes, or share for commercial purposes the personal information of 50,000 or more California consumers, households, or devices Derive 50% or more of your annual revenue from selling California consumers’ personal information (yikes!) And if you're selling globally, as are an increasing number of our larger customers here at Littledata, remember that you need to pay attention to privacy laws everywhere you do business. So if you have customers in the EU, remember to pay attention to GDPR for ecommerce sites too. CCPA for Shopify Plus Shopify has put together a number of resources to explain how Shopify complies with the CCPA, including a timeline and white paper. Here are some of the most useful links from Shopify itself: CCPA timeline CCPA thresholds Shopify’s position on sale of personal information How CCPA affects you Processing CCPA data requests And Segment too! A number of Littledata's enterprise users are also using our Segment connection for more accurate Shopify data. Check out Segment's quick guide to CCPA compliance, including an outline of their privacy portal and an API for user deletion and suppression (to make sure that you honor customer requests about privacy). Again, it's unclear whom they'll be targeting. California is now the world's fifth largest economy, surpassing even the UK, but nobody's sure if the state will be using CCPA to clamp down on successful DTC brands, for example, or if it will be taking a strategic line against larger fish like Facebook and Google (i.e. what happened in 2018 when seven consumer groups filed GDPR complaints against Google in Europe). Confused? You're not alone. The increasing number of cookie popups and disclosures seems to only be confusing consumers, and nobody — including the businesses putting them in place — is interpreting them in a consistent manner. Part of this is being called a 'plague of popups' and (a la GDPR) 'banner blindness'. But even if you aren't doing $20M a year yet, it's worth a read through the law so you can refer to it with your internal team. Just like how Littledata doesn't fix historic data for your Shopify store — only your data collection going forward — it's essential to be forward-thinking about potential privacy regulations that might be enacted in the future, taking steps today to ensure smooth sailing later on. Google Analytics consultants are a good place to start. Plus, sometimes it just comes down to common sense. When you're the consumer, how do you want your data handled?
Black Friday discounting increases next season’s purchasing
Black Friday Cyber Monday appears to be big business for ecommerce merchants. But what happens after the promotions? I knew Black Friday had reached ‘late adopter’ stage when a company I’d bought fencing panels from – fencing panels – emailed me their holiday season promotions. But the real question is this: will all these promotions actually drive customer loyalty, or only attract bargain hunters? Looking at the data At Littledata, we looked at aggregate data from 143 retailers who participated most in 2016 Black Friday, versus 143 retailers who did not. For the first 23 days of November 2017 – before Black Friday – the median year-on-year increase in sales was 13% for those pushing discounts the previous year, versus only 1% growth for those avoiding Black Friday discounting *. Our conclusion is that retailers who discounted most heavily on Black Friday 2016 saw a lasting benefit in extra sales a year after the sales period. However, we don’t know whether these extra sales were profitable enough to pay for the seasonal promotions. Another possible explanation is that higher-growth retailers are more active in marketing Black Friday, but in either event the discount season has done them no harm over the following year. Looking at 2016, it seems Black Friday was bigger than the year before for our cohort of 270 UK retailers – but at the expense of sales later in the season. Yet in the UK, we are not close to US levels of hysteria yet, where a much greater proportion of the last quarter’s sales are done on that weekend. What sectors does Black Friday affect? The other interesting question is what sectors does Black Friday affect? It may be a surprise that the biggest boost of over 100% average increase in sales comes for Health & Beauty stores, whereas technology and computer stores saw an average boost of 40% for the week. The graph below shows the difference with the average sales volumes in November & December 2016, by sector, for 3 selected weeks: Perhaps I shouldn’t have been surprised by those fencing panels: business and industrial sites saw a big boost too! Interested in tracking online sales activity for your own site this holiday shopping season? Littledata's ecommerce analytics software provides accurate data and automated reporting to help you track promotions and drive conversions and customer loyalty. [subscribe] *The statistical detail I took a group of 573 retailers we have tracked for at least 2 years, and looked at the ratio of Black Friday weekend sales (Friday, Saturday, Sunday, Monday) to the 2 month average for November and December. Those in the top quartile (trading 2.6 times above average during the Black Friday season) were deemed to have participated; those in the bottom quartile, showing a dip in trading over that weekend were deemed not to have participated. I then looked at the year-on-year growth in revenue between November 2016 (first 23 days) and the same period in November 2017, for the discount versus non-discount group. A t-test between the groups found an 18% probability that the two groups had the same mean, not allowing us to dismiss the null hypothesis. [note]This Black Friday ecommerce strategy post was originally published in November 2017 but has since been updated.[/note]
How much does customer engagement affect conversion rate?
Whether you're using Shopify, BigCommerce, Magento, Salesforce Commerce Cloud or another ecommerce platform, it's crucial to drive high traffic volume to your site. But important as it may be, it's not the deciding factor between a sale and a cart abandonment. If your traffic doesn't convert, the volume of traffic doesn't matter. Customer attraction is only half the battle — customer engagement, however, is what leads to higher conversion rates, which means more product sales for your store. Conversions are the lifeblood of product marketing. So your main goal is not attraction, but persuasion — collecting an email for lead generation or retargeting, completing customer transactions, getting signups up for your newsletter or anything else of measurable value for your store. As a merchant, you know conversions are the name of the game. You'd think every merchant would have it down to a science. In fact, the data suggests otherwise. What's a healthy conversion rate? While your average ecommerce conversion rate will vary by product type, price point, location of sale and other factors, here are some reliable industry benchmarks we've nailed down: Just recently, our team surveyed 1,127 stores and found the average conversion rate for stores was just 1.4%. This means a conversion rate above 3.1% would put your store in the 80th percentile, with a rate higher than 4.8% in the 90th percentile. Our test also found an ecommerce conversion rate (all devices) of less than 0.5% would put your store in the 20th percentile, with a rate of below 0.2% ranking your store among the worst-performing: Converting sales isn't getting easier, either — reaching the 1.4% industry benchmark can be a challenge for online stores, especially those that: don't price competitively (with the help of historical data) don't use conversion rate optimisation best practices don't optimise their store to increase customer engagement Speaking of customer engagement, we'll dive into how to boost your ecommerce conversion rates (here are some bonus tips on improving CRO). But first, let's overview what customer engagement really is. [subscribe] What is customer engagement, really? Customer engagement is the strongest indicator of how a customer feels about your brand, your products and your online shopping experience. There are many conduits for measuring customer engagement (e.g. email open rates, page views, landing page clicks, average time spent on page, bounce rates, etc.). With a 500-person sample of marketers, a Marketo survey found the following: 22% of people thought customer engagement was a brand awareness tool 63% considered it customer retention, repeated purchases and renewal rates 78% thought it was something that occurred in the final stages of the marketing funnel In other words, modern merchants don't exactly have a solid definition of what customer engagement really is. Even as data analytics experts (a.k.a. data geeks), we consider customer engagement to be more than a measurable set of customer data or online actions — it's also an emotional connection to a brand as well as a tool for brand awareness, chiefly driven by data, measured by data and optimised by data. See the pattern? Customer engagement isn't just short-term set of actions. It's a strategic, long-term play that informs product sales performance, marketing attribution and customer delight. Without accurate, reliable data to support decision-making, it's difficult to move the needle for your store — and especially hard to optimise your conversion rate. Luckily, our commerce connections for top platforms like Shopify, Shopify Plus, Magento and BigCommerce are available for merchants of all sizes. And of course, you're free to try our smart analytics app free for 14 days, including our top-rated Google Analytics connection (free) and highly-rated Shopify app.
How to fix marketing attribution for iOS 14
The latest version of Safari, and all browsers running on iOS for iPhones or iPads, limit the ability for Google Analytics (and any other marketing tags) to track users across domains, and between visits more than a day apart. Here’s how to get this fixed for your site. This article was updated January 2021 to include the changes for iOS 14 How does this affect my analytics? Safari's Intelligent Tracking Prevention (ITP) dramatically changes how you can attribute marketing on one of the web's most popular browsers, and ITP 2.3 makes this even more difficult. How will the changes affect your analytics? Currently your marketing attribution in Google Analytics (GA) relies on tracking users across different visits on the same browser with a first-party user cookie - set on your domain by the GA tracking code. GA assigns every visitor an anonymous ‘client ID’ so that the user browsing your website on Saturday can be linked to the same browser that comes back on Monday to purchase. In theory this user-tracking cookie can last up to 2 years from the date of the first visit (in practice, many users clear their cookies more frequently than that), but anything more than one month is good enough for most marketing attribution. ITP breaks that user tracking in major ways: Any cookie set by the browser, will be deleted after 7 days (ITP 2.1)Any cookie set by the browser, after the user has come from a cross-domain link, will be deleted after one day (ITP 2.2)Any local storage set when the user comes from a cross domain link is wiped after 7 days of inactivity (ITP 2.3)With Safari 14, any script known to send events about the user is blocked from accessing cookies or any way of identifying the userFrom iOS 14 onwards all browsers will implement these restrictions by default, unless the user opts in to 'allow cross-website tracking'. This will disrupt your marketing attribution. Let’s take two examples. Visitor A comes from an affiliate on Saturday, and then comes back the next Saturday to purchase: Before ITP: sale is attributed to AffiliateAfter ITP: sale is attributed to ‘Direct’Why: 2nd visit is more than one day after the 1st Visitor B comes from a Facebook Ad to your latest blog post on myblog.com, and goes on to purchase: Before ITP: sale is attribute to FacebookAfter ITP: sale is attributed to ‘Direct’Why: the visit to the blog is not linked to the visit on another domain The overall effect will be an apparent increase in users and sessions from Safari or iPhones, as the same number of user journeys are broken in down into more, shorter journeys. How big is the problem? This is a big problem! Depending on your traffic sources it is likely to affect half of all your visits. Apple released iOS 14 and Safari 14 on 16th September 2021, and at the time of writing around 20% of all web visits came from iOS 14, and another 20% of visits from Safari 12 or higher, on a sample of larger sites. The volume for your site may vary; you can apply this Google Analytics segment to see exactly how many iOS users you have. The affected traffic will be greater if you have high mobile use or more usage in the US (where iPhones are more popular). Why is Apple making these changes? Apple has made a strong point of user privacy over the last few years. Their billboard ad at the CES conference in Las Vegas earlier this year makes that point clearly! Although Google Chrome has overtaken Safari, Internet Explorer and Firefox in popularity on the desktop, Safari maintains a very dominant position in mobile browsing due to the ubiquitous iPhone. Apple develops Safari to provide a secure web interface for their users, and with Intelligent Tracking Prevention (ITP) they intended to reduce creepy retargeting ads following you around the web. Genuine web analytics has just been caught in the cross-fire. Unfortunately this is likely not to be the last attack on web analytics, and a permanent solution may not be around for some time. Our belief is that users expect companies to track them across their own branded websites and so the workarounds below are ethical and not violating the user privacy that Apple is trying to protect. How to fix this There is only one fix I would recommend. I’m grateful to Simo Ahava for his research on all the possible solutions. If you’re lucky enough to use Littledata's Shopify app then contact our support team if you'd like to test the private beta of our 'trusted cookie' solution. Server-side cookie service ITP limits the ability of scripts to set cookies lasting for longer than 7 days (or 24 hours in some cases). But this limit is removed if a web server securely sets the HTTPS cookie, rather than via a browser script. This also has the advantage of making sure any cross-domain links tracked using GA's linker plugin can last more than one day after the click-through with ITP 2.3. The downside is this requires either adapting your servers, proxy servers or CDN to serve a cookie for GA and adapt the GA client-side libraries to work on a web server. If your company uses Node.js servers or a CDN like Amazon CloudFront or Cloudflare this may be significantly easier to achieve. If you don’t have direct control of your server infrastructure it’s a non-starter. Also, a caveat is that Apple recommends settings cookies as HttpOnly to be fully future proof - but those would then be inaccessible by the GA client tracking. Full technical details. What about other marketing tags working on Safari? All other marketing tags which track users across more than one session or one subdomain are going to experience the same problem. With Google Ads the best solution is to link your Ad account to Google Analytics, since this enables Google to use the GA cookie to better attribute conversion in Google Ads reporting. Facebook will no doubt provide a solution of their own, but in the meantime you can also attribute Facebook spend in GA using Littledata’s connection for Facebook Ads. Are there any downsides of making these changes? As with any technical solution, there are upsides and downsides. The main downside here is again with user privacy. Legally, you might start over-tracking users. By resetting cookies from the local storage that the user previously requested to be deleted, this could be violating a user’s right to be forgotten under GDPR. The problem with ITP is it is actually overriding the user’s preference to keep the cookie in usual circumstances, so there is no way of knowing the cookie was deleted by the user … or by Safari supposed looking out for the user! Unfortunately as with any customisation to the tracking code it brings more complexity to maintain, but I feel this is well worth the effort to maintain marketing attribution on one of the world's most popular browsers.
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