In this playbook:<\/strong><\/p>\n The surface-level narrative is simple: celebrities and media companies slap their logos on hoodies and sell them online. That is not what is happening here.<\/p>\n Shopify now powers over 5.6 million active stores globally and processed more than $300 billion in gross merchandise volume (GMV) in 2025, according to Shopify’s financial reports. That is more than the GDP of many countries. And the enterprise tier, Shopify Plus, now serves over 47,000 merchants, with brands like Gymshark, Mattel, and Kylie Cosmetics running their entire DTC operations through it.<\/p>\n But the enterprise migration tells a bigger story.<\/strong> Over 42% of new enterprise-level ecommerce launched in the past two years chose Shopify, with more than 1,200 enterprise brands added annually through net migration. Many are leaving legacy platforms like Adobe Commerce and Salesforce Commerce Cloud. This shift is not about commerce infrastructure. It is about data ownership<\/strong>.<\/p>\n None of these brands needed a new revenue stream.<\/strong> They needed a new data stream. When you sell through a retailer or marketplace, you get a sales report. When you sell DTC, you get behavioral data, purchase patterns, email addresses, geographic insights, and the ability to build audience segments that no third-party platform can replicate. For a closer look at the scale and diversity of this ecosystem, explore our breakdown of the top companies that use Shopify<\/a><\/strong>.<\/p>\n Third-party cookies are disappearing. Safari and Firefox block them by default, affecting 35 to 40% of web traffic. Apple’s App Tracking Transparency requires explicit opt-in for tracking, and only 25 to 35% of users comply. For marketers who built their targeting infrastructure on borrowed data, the floor is collapsing.<\/p>\n This is exactly why the biggest brands in the world are building owned ecommerce channels.<\/p>\n Every Shopify transaction generates a first-party data record: email address, purchase history, browsing behavior, geographic location, device type, and engagement patterns. High-growth companies are increasingly prioritizing this data for personalization and retention strategies.<\/p>\n Here is how this plays out in practice:<\/p>\n Netflix<\/strong> collects purchase data tied to specific show preferences. When a fan buys a Stranger Things hoodie, Netflix now knows that person is an engaged viewer who is willing to spend money on IP-related products. That data feeds back into content strategy, merchandising decisions, and audience segmentation for future launches.<\/p>\n Red Bull<\/strong> aligns product drops with major events like racing and music festivals, creating marketing synergy between event attendance and ecommerce behavior. Their store integrates personalized product recommendations based on browsing habits, building a behavioral profile that goes far beyond what an energy drink purchase at a grocery store would reveal.<\/p>\n Taylor Swift’s<\/strong> store uses timed product drops, exclusive bundles, and geo-targeted offers that deliver different merchandise to fans based on their concert locations. This is not just merchandising. This is zero-party data collection at scale, where fans voluntarily reveal their location, preferences, and spending willingness through their purchase behavior.<\/p>\n The pattern is clear: DTC ecommerce has become the single most reliable channel for capturing actionable customer intelligence at sale.<\/strong> According to EMARKETER<\/em><\/strong>, more than 55% of U.S. consumers say they feel more connected to brands when shopping on their websites, and nearly 60% shop directly with brands specifically for exclusive benefits.<\/p>\n For companies selling data, marketing services, or technology solutions to ecommerce and DTC brands, this shift changes the buying landscape entirely.<\/p>\n DTC brands are longer asking: \u201cHow do we get more customers?\u201d They are asking \u201cHow do we use our data to acquire efficiently and retain profitability?\u201d<\/p>\n Customer acquisition costs have risen significantly in recent years, and first purchases are often low-margin or unprofitable. Retention, repeat purchases, and lifecycle optimization drive growth.<\/p>\n This creates a clear demand for:<\/p>\n This is where providers like Span Global Services become critical.<\/p>\n The opportunity is not in offering \u201ca large database.\u201d The opportunity is in delivering a verified, enriched intelligence layer that makes DTC retention and lifecycle marketing actually work.<\/p>\n That distinction fundamentally changes how solutions are positioned, sold, and adopted. For deeper insight into how accurate B2B data transforms marketing outcomes, check out our guide on how a quality B2B email list can transform your marketing strategy<\/a>.<\/strong><\/p>\n The Shopify-powered DTC explosion is not just a trend to observe. It is a signal to act on. Here is a four-step framework for B2B growth teams looking to convert this shift into a qualified pipeline.<\/p>\n Not every Shopify store is a viable prospect. Focus on Shopify Plus merchants<\/a><\/strong> doing $1M to $500M in annual revenue. These are the brands with real budget, real data challenges, and real urgency around acquisition costs. Shopify Plus merchants report an average 126% year-over-year revenue growth. They are scaling fast, and their data infrastructure is struggling to keep up. To target the broader Shopify ecosystem, access a verified Shopify users email list<\/a><\/strong> for direct outreach to store owners and ecommerce decision-makers.<\/p>\n DTC brands running on Shopify face three recurring data gaps:<\/p>\n DTC operators do not respond to enterprise data solutions messaging. They respond to specifics: “Your Klaviyo flows are underperforming because 12% of your list has decayed contacts. Here is how to fix it before Q3.”<\/p>\n Use the language of their stack: Klaviyo, Gorgias, Recharge, Shopify Flow, Shop Pay. Speak to pipeline velocity, not data quality in the abstract.<\/p>\n The final step is targeting. Do not spray emails at every Shopify merchant. Use intent data and technographic signals<\/a><\/strong> to identify which DTC brands are actively evaluating data solutions, which ones have recently migrated platforms, and which ones are scaling their ad spend (a reliable proxy for data hunger).<\/p>\n The Framework:<\/strong> Identify high-growth Shopify Plus merchants. Map their data pain. Create stack-specific content. Activate with intent signals. This is the DTC-to-Pipeline Method, and it turns the biggest ecommerce trend of the decade into a B2B revenue engine.<\/p>\n Every DTC brand running a Shopify store collects first-party data. That is table stakes. The competitive advantage is in what happens after collection: verification, enrichment, and activation.<\/p>\n Consider the math. Shopify merchants generated $14.6 billion in sales during Black Friday\/Cyber Monday 2025 alone, a 27% increase from the prior year. Behind every one of those transactions is a customer record. But if even 10% of the email addresses in a brand’s post-purchase flow are invalid, that is hundreds of thousands of dollars in unreachable revenue.<\/p>\n Data accuracy is not an option. It is the infrastructure that makes DTC profitable.<\/strong> Without it, email campaigns bounce, sender reputations tank, personalization breaks down, and the 60% of revenue from returning customers starts to evaporate.<\/p>\n This is where B2B data partners become essential. The DTC brand collects the data. The data partner ensures it stays accurate, enriched, and actionable. That is not a vendor relationship. That is an infrastructure partnership.<\/p>\n For B2B companies looking to position themselves as that infrastructure layer, the opportunity has never been larger. The Shopify ecosystem alone processes more GMV than many national economies. The brands operating within it are spending more every year on data services, email marketing, and customer intelligence platforms.<\/p>\n The question is whether you are going to reach those brands with generic buy our data messaging, or whether you will meet them with the verified, intent-enriched intelligence that actually moves the needle on their growth.<\/p>\n The playbook is no longer theoretical. Netflix, Red Bull, and Taylor Swift did not build Shopify stores because they wanted a side hustle. They built them because DTC ecommerce is the most efficient mechanism for capturing first-party data at scale, and first-party data is the single most valuable asset in a post-cookie world.<\/p>\n For B2B marketers, this creates a two-fold opportunity. First, the DTC ecosystem itself is a massive addressable market, with millions of merchants actively seeking data, enrichment, and intelligence services. Second, the same principles that drive DTC success, owning your data, enriching your contacts, and personalizing every touchpoint, apply directly to your own outbound strategy.<\/p>\n To reach these high-growth ecommerce decision-makers with precision, you need the same thing they need: clean, verified, continuously refreshed data. That is what Span Global Services<\/a><\/strong> delivers. Not a list. A revenue intelligence layer built on 296 million B2B contacts, verified across 78 data fields, and compliant with 15+ global regulations.<\/p>\n\n
The Real Reason Enterprise Brands Are Going DTC on Shopify<\/h2>\n
![\"Brands](\"https:\/\/www.spanglobalservices.com\/blog\/wp-content\/uploads\/2026\/04\/Reason-Enterprise-Brands-Are-Going-DTC-on-Shopify-1024x572.webp\")
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The First-Party Data Playbook: What Netflix, Red Bull, and Taylor Swift Actually Collect<\/h2>\n
What This Means for Companies Selling to Ecommerce Brands<\/h2>\n
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The DTC-to-Pipeline Framework: Turning Ecommerce Intelligence Into Revenue<\/h2>\n
![\"DTC-to-Pipeline](\"https:\/\/www.spanglobalservices.com\/blog\/wp-content\/uploads\/2026\/04\/DTC-Pipeline-Framework-1024x572.webp\")
<\/p>\nStep 1: Identify the DTC-First Buyer Profile<\/h3>\n
Step 2: Map Their Data Pain Points<\/h3>\n
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Step 3: Build Content That Speaks Their Language<\/h3>\n
Step 4: Activate With Intent-Enriched Outreach<\/h3>\n
Why Data Accuracy Is the Hidden Moat in DTC Strategy<\/h2>\n
The DTC Data Shift Is Not Slowing Down. Your Pipeline Strategy Should Not Either.<\/h2>\n