Third-party cookies are a dying model. Safari and Firefox already block them by default, and even Chrome has moved to an opt-in model. For e-commerce businesses, this means: those still relying on external data pools are losing reach, personalization, and ultimately revenue. The alternative? A well-crafted first-party data strategy built on your own customer data – GDPR-compliant, sustainable, and significantly more effective.
Why Third-Party Cookies Have No Future
Dependency on third-party cookies was the foundation of digital marketing for years. But the rules have fundamentally changed. Apple Safari has completely blocked third-party cookies since 2020 via Intelligent Tracking Prevention (ITP). Mozilla Firefox has used Total Cookie Protection since 2022, isolating third-party cookies per website. And Google Chrome? After six direction changes since 2020, Google finally abandoned deprecation in April 2025 – but introduced an opt-in model where users must actively consent (Google Privacy Sandbox).
The consequence: a growing share of visits reaches stores without usable third-party data. Safari holds 15.92% of the global browser market, Firefox another 2.98% (StatCounter, August 2026) – both block third-party cookies by default. Relying on third-party data means operating with a shrinking data foundation.
Zero-Party, First-Party, Third-Party: The Differences
Before diving into strategy, let's clarify the terminology. Not all customer data is equal – and the method of collection determines quality, privacy compliance, and usability.
| Property | Zero-Party Data | First-Party Data | Third-Party Data |
|---|---|---|---|
| Collection | Voluntarily shared | Observed behavior | Purchased from third parties |
| Examples | Quizzes, surveys, preferences | Purchase history, browsing, clicks | Aggregated user data |
| Accuracy | Very high (self-reported) | High (directly observed) | Variable (aggregated) |
| GDPR Compliance | Strong (explicit consent) | Strong (consent required) | Risky (origin unclear) |
| Competitive Advantage | Unique to your brand | Unique to your brand | Available to competitors |
| Scalability | Limited | Medium | High but declining |
The term zero-party data was coined by Forrester in 2018 and describes information that customers proactively and voluntarily share with a brand. This can be a completed skin type quiz, a product preference, or a desired email frequency. In contrast, first-party data is collected through interactions – such as browsing behavior, purchase history, or click paths in the store. Both data types belong exclusively to you and thus offer a genuine competitive advantage over third-party data, which your competitors can also purchase.
The ROI of First-Party Data: Facts and Figures
The investment in first-party data pays off twice: the data remains available when third-party signals disappear, and it describes your own customers more precisely than purchased audiences. Whether the effort pays off is something your own store will show – measurable in registration rate, repeat purchase rate, and segment size before and after the switch.
Higher Marketing ROI
Personalized campaigns with first-party data instead of generic mass advertising
Lower acquisition costs
More precise targeting with your own data instead of purchased segments
Better recommendations
Recommendations drawn from observed behavior in your own store
Additionally, consumers prefer to buy from companies that offer personalized experiences and get frustrated when personalization is missing. The demand for individualized shopping experiences is growing – and the data for this must come first-hand. In our article on conversion optimization, we show how personalization directly impacts purchase rates.
6 Methods for Collecting First-Party Data in E-Commerce
A successful first-party data strategy combines multiple collection methods. The key is the value exchange: customers share their data when they receive tangible value in return – be it a personalized recommendation, a discount, or a better shopping experience.
1. Customer Accounts and Order History
The customer account is the most valuable source of first-party data. Every order, every address entry, and every wishlist addition expands the customer profile. In Shopware, customer accounts can be enriched with groups, tags, and custom fields to create detailed segments. The AI-based customer classification in Shopware's AI Copilot automatically analyzes order histories and assigns tags like "Frequent Buyer" or "Premium Customer" (Shopware). The key is making registration attractive: order tracking, wishlists, faster checkout, and exclusive offers are incentives that noticeably increase registration rates.
2. Preference Centers and Progressive Profiling
A preference center is a section in the customer account where users actively specify their interests, communication preferences, and product preferences. These are classic zero-party data: voluntary, explicit, and high-quality. Instead of requesting all information at the first contact, progressive profiling relies on gradual data collection. At the first interaction, name and email suffice. On the second visit, you ask about product interests. On the third, about preferred communication frequency.
This approach reduces abandonment rates: those who ask for too much at first contact lose part of their prospects in the form itself. Progressive profiling builds trust and collects a much more comprehensive profile over time. Important: Transparently explain why you're requesting certain data and what benefit the customer receives – this isn't just relevant for GDPR compliance, but also increases willingness to share data.
3. Interactive Quizzes and Product Advisors
Interactive quizzes transform data collection into an experience with direct value. A beauty store asks about skin type, care goals, and allergies – and delivers personalized product recommendations in return. A fashion store determines the style type. A supplement store creates an individual needs plan. The side effect: some participants leave their email address at the end of the quiz to receive the result – together with rich preference data. This zero-party data feeds personalized recommendations that keep working further along the customer journey.
This is what your shop with first-party personalization could look like:
Natural Cosmetics
4. Loyalty Programs and Rewards Systems
Loyalty programs are a proven instrument for first-party data collection with a clear value exchange. Customers voluntarily share data in exchange for points, discounts, or exclusive benefits. The prime example is Sephora's Beauty Insider: the program collects detailed preference data and uses it for personalized recommendations. Every redeemed reward and every point balance is also a data point about preferences and purchase rhythm. This active engagement creates natural opportunities to collect additional data: subsequent visits can reward profile completions with bonus points.
5. Newsletter and Email Marketing
Email remains a high-yielding owned channel. For every $1 spent on email marketing, 35% of surveyed marketing leaders receive $10-$36 in return and 30% receive $36–50 (Litmus). Every open, every click, and every response delivers valuable first-party data about customer interests. Segmented and personalized email flows – such as cart abandonment, birthday mailings, or repurchase reminders – address a smaller circle more precisely than mass mailings. The combination of newsletter signup, preference center, and behavior-based automations creates a data cycle that improves with every contact. How to connect this strategy with AI-powered automation is covered in our separate article.
6. On-Site Behavioral Data (With Consent)
Browsing behavior, search queries, click paths, time on page, and product comparisons – all of these are valuable first-party data generated directly in your store. The prerequisite is proper consent via a cookie banner and compliance with applicable privacy regulations. Learn more about privacy-compliant tracking in our article on Server-Side Tracking. The key is not just collecting this data but activating it: combined with a CDP or Shopware's native segmentation features, anonymous data points become usable customer segments for targeted marketing campaigns and personalized shop experiences.
The Role of Customer Data Platforms (CDPs)
As data diversity grows, the question arises: where does all the information converge? Customer Data Platforms (CDPs) create a unified customer data record from various sources – store, email, social media, and customer service. The global CDP market is growing from $7.34 billion (2026) to a projected $14.04 billion by 2031 – a growth rate of 13.8% annually (MarketsandMarkets).
For Shopware stores, there are several integration options: from Custobar as a dedicated CDP integration to Bloomreach for enterprise customers to Shopware's own AI-powered customer classification. A complete 360-degree customer view, however, often stays out of reach because it cannot be reconciled cleanly with data protection requirements. The pragmatic approach: focus on the data points that are actually relevant for your personalization and integrate only the sources you truly use. Our integration experts help you with selection and connection.
Unified Customer Profile
Merge data from store, email, customer service, and social media into a single central profile.
Real-Time Activation
Adjust segments and personalizations in real time – without manual exports or imports.
Privacy-First Architecture
Consent management and data deletion directly in the platform – GDPR-compliant by design.
AI-Powered Segments
Machine learning identifies patterns in customer data and automatically creates value-based segments.
GDPR-Compliant Data Collection: Legal Guardrails
Collecting first-party data doesn't mean you can skip data protection. On the contrary: precisely because this data is so valuable, it must be collected according to GDPR rules. Violations can result in fines of up to 20 million euros or 4% of global annual revenue, whichever is higher (GDPR Art. 83). Privacy and personalization are not mutually exclusive: consent that clearly names the purpose of collection carries both.
- Consent before collection – Active opt-in for all data-collecting measures, no pre-checked boxes
- Purpose limitation – Use data only for the stated purpose, no retrospective purpose changes without new consent
- Data minimization – Only collect data actually needed for the specific purpose
- Transparency – Clearly communicate what data is collected, why, and how long it's stored
- Granular control – Customers must be able to revoke individual consents and view their data
- Documentation – Document all processing activities in the record of processing activities
Transparency in data collection isn't just a legal obligation, it's a competitive advantage: those who explain what each field is needed for and what the customer gets in return receive more complete profiles than those who simply present a form without comment.
Personalization in Practice: Activating Data
Collecting data is only half the battle. The actual value comes from activation – using the data for personalized customer experiences. That is where the effort of collecting pays off. Just how powerful activation is shows in automated email flows: abandoned cart flows are typically among the flow types with the highest placed order rate.
Product Recommendations
Personalized recommendations based on purchase history, browsing behavior, and zero-party preferences.
Dynamic Content
Customize homepage, category arrangement, and banners individually per customer segment.
Trigger-Based Emails
Cart abandonment, post-purchase sequences, and reactivation campaigns automated and personalized.
Individual Pricing Rules
Segment-specific discounts and offers for VIP customers, new customers, or inactive customers.
Cross- and Upselling
Data-driven additional recommendations that match the customer's purchasing behavior.
Retargeting with 1st-Party
Own audience segments for ads instead of dependency on third-party pixels.
The technical implementation varies depending on the shop system and data volume. Shopware 6 offers native personalization features through Shopping Experiences that can be linked with customer segments. For more demanding scenarios, AI-powered data enrichment and external CDPs can be integrated. Our consulting team analyzes your existing infrastructure and recommends the right solution.
Practical Guide: 5 Steps to Your First-Party Strategy
- Inventory – What customer data are you already collecting? Where does it reside? CRM, shop system, email tool, analytics? Identify data silos and check GDPR compliance of existing collection methods.
- Define value exchange – Establish a clear customer benefit for each data collection point. Why should a customer fill out a quiz? What do they get for the newsletter signup? A clearly named benefit increases the willingness to give honest answers.
- Prioritize data sources – Don't implement everything at once. Start with quick wins: optimize customer accounts, set up a preference center, refine email segmentation. Then gradually add quizzes, loyalty programs, and CDP integration.
- Build technical infrastructure – Configure Shopware customer segmentation, connect email automation with the store, integrate consent management platform. For more complex requirements, evaluate a CDP solution.
- Measure and optimize – Define KPIs: registration rate, profile completeness, segment size, personalization conversion. Run A/B tests for quizzes and preference centers. Continuously optimize.
Requesting too much data at once. Studies show that long forms drastically increase abandonment rates. Use progressive profiling and collect data gradually across multiple touchpoints – this increases both the quantity and quality of data.
Frequently Asked Questions About First-Party Data Strategy
Not necessarily. For smaller and mid-sized stores, the built-in features of Shopware or WooCommerce combined with a good email marketing tool are typically sufficient. A CDP becomes relevant only when you need to merge data from many different sources and require complex real-time personalizations.
Server-Side Tracking and a first-party data strategy complement each other. Server-Side Tracking improves technical data capture by reducing data loss from ad blockers. A first-party data strategy goes beyond: it builds your own data foundation from customer accounts, preferences, and zero-party data that works independently of tracking technologies.
The first quick wins – optimized customer accounts and a preference center – can typically be implemented within 4–8 weeks. A comprehensive strategy with quizzes, loyalty program, and CDP integration is typically a 3–6 month project. We recommend a phased approach.
Yes, it's particularly valuable for smaller stores. A customer account with wishlist, a simple preference center, and segmented email flows can be implemented with manageable effort and typically deliver immediately measurable improvements in repeat purchase rate and average order value.
AI helps on multiple levels: automatic customer segmentation (like Shopware's AI Copilot), predictive analytics (churn prediction, next-best-action), personalization of product recommendations, and automated content creation. What matters: AI is only as good as the data it builds on – without clean first-party data, every recommendation stays guesswork.
Zero-party data is what customers share deliberately and voluntarily – for example through a quiz, a survey, or a preference center. First-party data, by contrast, comes from observed behavior in the store, such as purchase history, browsing, or click paths. Both belong exclusively to you and are well manageable under GDPR as long as consent is in place. In practice they complement each other: zero-party data provides stated preferences, first-party data the actual behavior.
Own Data as a Sustainable Competitive Advantage
The post-cookie era isn't a threat – it's an opportunity. Companies that invest in a solid first-party data strategy now will benefit long-term: through more precise personalization, lower acquisition costs, and a direct customer relationship that no browser update can destroy. The shift to a cookieless future will disrupt operations – but therein lies the advantage for those who are prepared.
Start with quick wins: optimize customer accounts, set up a preference center, and switch your email segmentation to first-party data. Then gradually expand with quizzes, loyalty programs, and AI-powered personalization. We support you at every step – from strategy through technical implementation to ongoing optimization.
This article is based on data from: StatCounter, MarketsandMarkets, Litmus, Shopware, Google Privacy Sandbox, and the wording of the GDPR. The cited figures may vary by industry, region, and time period.