Third-party
cookies are ending.
Your data
must outlive them.
40% of users already reject cookies. Only 14% of companies have a complete view of their customers. The shift towards a privacy-first web is structural and irreversible. This guide explains how to build a proprietary data ecosystem that depends on no browser, no regulation and no decision by Google.
The state of data in Italian marketing: the real problem
There is a paradox in Italian digital marketing in 2026: companies collect more data than ever, yet use only a tiny fraction of it. Data is everywhere: in the CRM, in analytics, in email, in the management system, at the point of sale. But it is fragmented, disconnected, often inaccessible without IT support, and therefore unused.
Research by Making Science reveals that more than half of Italian companies do not integrate their data, losing the overall view needed for informed decisions. Figures from Politecnico di Milano reinforce the picture: only 35% of Italian companies had adopted a Customer Data Platform in 2025. And of those that claim a complete view of their customers, just 14% to begin with, 44% admit they cannot access it in a structured way.
The problem is not technological — the solutions exist and are accessible. It is cultural and strategic. Most companies have built their marketing infrastructure around third-party cookies as if they were a vested right. They were not. They will not be. And those who have not begun the transition to a proprietary data model are building up a dependency that will become ever more costly to dismantle.
The data hierarchy: zero-party, first-party, second-party, third-party
Before building a strategy, you need to understand the system it operates in. Marketing data falls into four categories with very different value, ownership and risks. Knowing the differences is not an academic exercise — it shapes technology and budget decisions.
The strategic direction is clear: maximise zero-party and first-party data, and structurally reduce reliance on third-party data. This is not a question of ethical purity — it is a question of resilience. Marketing built on proprietary data is independent of decisions made by Google, Apple, the Italian Data Protection Authority or any browser. Marketing built on third-party cookies is at constant risk of disruption.
Why now: the post-cookie trajectory is irreversible
On 25 April 2025, Google officially abandoned its plan to remove third-party cookies from Chrome — after five years of announcements, three postponements and an advertising ecosystem that had already invested billions in adapting. The news brought immediate relief to the industry. But reading it as a guaranteed reprieve for third-party cookies would be a serious strategic mistake.
The trajectory towards a privacy-first web does not hinge on a single decision by Google. It depends on structural forces that Chrome does not control:
- Safari has blocked third-party cookies by default for years, through Intelligent Tracking Prevention (ITP). Safari accounts for 19% of global desktop traffic and 28% of mobile traffic in Italy.
- Firefox has blocked third-party cookies by default since 2019. A minority but significant share of desktop traffic.
- 40% of users actively reject cookies even on browsers that do not block them by default, a figure that grows every year as privacy awareness increases.
- GDPR and the ePrivacy Regulation continue to narrow the conditions under which profiling cookies can be collected lawfully. The Italian Garante is among the most active in Europe in this respect.
- Google Privacy Sandbox — the alternative system to cookies — is still in development and in any case introduces significant limitations compared with traditional cross-site tracking.
Even if Chrome never removed third-party cookies, their effectiveness would already be compromised. If 40% of users reject them and Safari + Firefox block them by default, your actual third-party cookie coverage is already at most 45-50% of your potential audience — and it falls every year. Building your strategy on such a fragile foundation is a risky choice, whatever Google decides.
The logic is simple: first-party data do not depend on any browser, any external regulation or any platform decision. They are yours. Collected with your users’ explicit consent. And as the external tracking ecosystem narrows further, the competitive gap between those who have invested in proprietary data and those who have not becomes structural.
How to collect first-party data: the 7 owned channels
First-party data collection does not happen by decree — it happens by designing every user touchpoint as an opportunity for value exchange. Users do not “give away” their data: they exchange it for something they perceive as useful, exclusive or advantageous. Designing this exchange is the core competence of a first-party data strategy.
01 — Newsletters and email marketing
The newsletter is the first-party data collection channel with the most favourable effort-to-result ratio of all. A consented email address is direct, named, verifiable data that can be activated on any platform. With an average conversion rate of 4.3% for email marketing (Social Shepherd, 2025), it remains the channel with the highest ROI in the digital mix.
- Design the lead magnet around a tangible, immediate benefit for the target audience: guides, checklists, early access, an exclusive discount, premium content. The perceived value must justify sharing an email address.
- Implement a welcome sequence that collects additional data in the first few days: preferences, sector, objectives. Every email with a direct question is high-value zero-party data collection.
- Use behavioural segmentation — opens, clicks, downloads — to enrich CRM profiles without explicitly asking for data.
- Refresh consent preferences periodically: a subscriber who actively confirms their preferences is worth ten times one who has never updated their initial consent.
02 — Loyalty programmes
Loyalty programmes are the most powerful data collection engine for consumer brands. Every transaction becomes structured information: what was bought, when, at what price, how often. Sephora, IKEA and the major international retailers have built their personalisation strategies entirely on this foundation.
- Design the programme around frequent micro-goals rather than distant rewards: consumers in 2026 prefer immediate gratification to future rewards.
- Connect the loyalty programme to every channel — online, app, physical — to gain a complete omnichannel view of purchasing behaviour.
- Use programme data to identify churn risk before it happens: patterns of declining frequency are predictive signals that can be acted on through CRM automation.
- Remember that collecting data in a loyalty programme requires explicit consent and a clear GDPR privacy notice — but a user who signs up is already in the right frame of mind to share information in exchange for benefits.
03 — Zero-party data: quizzes, surveys and configurators
Zero-party data are the most valuable because they remove inference: instead of deducing that a user is interested in running shoes because they have visited that section three times, the user states directly “I’m looking for trail running shoes for mixed terrain, budget €150”. The difference in the quality of personalisation is enormous.
- Onboarding quiz: a short quiz (3-5 questions) on arrival at the site or on newsletter sign-up turns the first interaction into structured data. A fashion brand increased conversions by 28% and reduced its reliance on paid media by 35% by implementing a style quiz on entry.
- Product configurators: every choice in the configurator is a zero-party data point. Preferences declared in a configurator are more predictive than any behavioural cluster.
- Post-purchase survey: a short survey after purchase captures motivations, satisfaction and future intentions — information no cookie can infer.
- Email preference centres: letting subscribers choose the content categories they want to receive both collects zero-party data and reduces the unsubscribe rate.
04 — Registered areas and gated content
Requiring registration in exchange for access to valuable content — in-depth guides, tools, calculators, webinars, industry reports — is one of the first-party data collection strategies with the best value-to-cost ratio in the B2B market. A user who registers to download a strategic report is, by definition, highly qualified.
- The gated content must have a perceived value greater than the friction of registering. If the content could be found for free elsewhere, it will not generate conversions.
- Ask only for the data you genuinely need: name, email and one qualifying field (role, sector, company size) are enough to start. Every additional field lowers the conversion rate.
- Use browsing data from the registered area to progressively enrich the profile: which guides they download, which pages they visit, how much time they spend on certain topics.
05 — Proprietary app
For brands with enough traffic and retention to justify the investment, a proprietary app is the richest first-party data collection channel available. In-app behaviour, push notifications, geolocation (with consent), in-app purchases, content interactions: a volume and granularity of data impossible to obtain via the web.
- The prerequisite is a clear value proposition for the user: why should they install your app? Without a convincing answer, the app is not installed and the data does not exist.
- Implement push notifications with granular consent: a user who actively chooses to receive certain types of notification is far more engaged than one who has accepted everything indiscriminately.
- Sync app data with the CRM or CDP to gain a complete omnichannel view.
06 — Physical point of sale
For brands with a retail presence, the physical shop is often the most valuable and least exploited source of data. Every POS transaction is a structured purchase data point. Every interaction with staff is an opportunity for qualitative data collection. Linking online behaviour to in-store purchases — the omnichannel customer journey — is the most advanced frontier of first-party data strategy.
- Connect the loyalty programme to the POS to track in-store purchases with the same granularity as online ones.
- Train staff to gather qualitative feedback that feeds the CRM — not just the name for the receipt, but also preferences and purchase motivations.
- Use in-store data to close the attribution loop: a customer who saw a campaign online and bought in store does not appear in digital analytics without integration across channels.
07 — Server-side tracking
Server-side tracking is the technical answer to the data fragmentation caused by browser-side cookie blocking. Instead of relying on JavaScript scripts — which can be blocked by ad blockers, Safari’s ITP and cookie restrictions — data are sent directly from the company’s server to analytics and advertising platforms.
The practical result: data collected server-side is first-party by definition, more accurate (fewer losses from browser blocking), safer from a GDPR standpoint, and not subject to browsers’ growing restrictions. Tools such as Google Tag Manager Server-Side or solutions such as Stape make implementation accessible even without advanced development skills.
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Request a data audit →The technology infrastructure: CMP, CRM and CDP
Collecting first-party data requires three distinct technology layers working in sequence: consent management, profile unification and audience activation. Choosing the right tools for each layer — and making them talk to each other — is the infrastructure work that determines data quality over the long term.
CMP — Consent Management Platform
The CMP manages users’ consent to data collection. It is the legal layer on which the entire strategy rests: without valid, documented consent, any data collected is a GDPR risk. A well-implemented CMP is not just compliance — it is also a source of data: the type of consent a user gives is in itself information about their willingness to receive personalised communications.
- Common tools: CookieYes, Cookiebot, OneTrust, Axeptio.
- Best practice: implement Google’s Consent Mode v2 to ensure continuity of Analytics and Ads tracking even for users who reject cookies.
- Avoid: dark patterns used to manipulate consent. The Italian Garante actively sanctions this practice.
CRM — Customer Relationship Management
The CRM is the central repository of named customer data: interaction history, transactions, preferences, communications. It is the foundation for any personalisation strategy. The main challenge is not having a CRM — almost every company has one — but using it as a living system, kept up to date and integrated with every contact channel.
- The typical problem: a CRM updated only by the sales team, not integrated with e-commerce, analytics or customer care. The result is partial data that underestimates the customer’s real value.
- The solution: automatic integration with all digital and physical touchpoints — every interaction updates the profile in real time.
- Common tools: HubSpot, Salesforce, Zoho CRM, Microsoft Dynamics.
CDP — Customer Data Platform
The CDP solves the problem that the CRM cannot solve on its own: unifying data from different sources — web, app, email, CRM, physical POS — into a single, persistent profile for each customer. It is not an alternative to the CRM: it is the layer above it, aggregating data from every company system and making it actionable in real time. In 2025 it reaches 35% of Italian companies (Politecnico di Milano).
- When you need it: when your data is fragmented across multiple systems, audiences are inconsistent across channels and measuring campaign value per customer is difficult.
- When you can wait: if you have a single channel and few touchpoints, start with CRM + marketing automation. A CDP creates value only when the use cases justify the complexity.
- Common tools: Segment, Tealium, Adobe Experience Platform, Salesforce Data Cloud.
Activating first-party data: from collection to results
Collecting data without activating it is a waste of resources. The value of first-party data lies not in their volume — but in the ability to turn them into concrete actions that generate revenue, loyalty or marketing efficiency. Collecting is the means. Activating is the end.
On-site experience personalisation
Behavioural data from the website can be used in real time to adapt the browsing experience: showing different content to first-time visitors than to existing customers, tailoring product recommendations to purchase history, changing the homepage message according to traffic source. It is the difference between a catalogue website and an advisor website.
Email segmentation and automation
First-party data turn email marketing from broadcast into a 1:1 conversation. Automations based on real behaviour — cart abandonment, subscription expiry, birthday, first purchase, prolonged inactivity — perform on average 3-5 times better than unsegmented batch campaigns. The prerequisite is an up-to-date CRM integrated with the email marketing platform.
Lookalike audiences and advertising campaigns
First-party data are the best fuel for paid campaigns. Uploading a list of real customers to Google Ads, Meta or LinkedIn to create lookalike audiences produces targeting segments far more precise than standard demographic segments. With the end of third-party cookies, this capability becomes a direct competitive advantage: those with structured proprietary data can target with quality; those without must rely on increasingly noisy signals.
AI-driven predictive models
With sufficiently rich proprietary datasets, AI and machine learning models make it possible to anticipate future behaviour: churn risk, likelihood of upgrade, the optimal moment for an offer. AI turns historical data into actionable predictions. A company that knows which customers are about to leave — 30 days in advance — can step in with targeted retention actions instead of winning them back with costly discounts after they have already gone.
A fashion brand implemented a first-party data strategy built on three elements: an interactive quiz to collect style preferences on arrival at the site, a personalised rewards scheme for registered users based on browsing and purchasing behaviour, and an automated series of dynamic emails that adapted offers and content to the data collected.
The result in 6 months: +28% conversion rate and -35% reliance on paid media. Less advertising spend for more sales — because existing customers are engaged more relevantly instead of being constantly replaced with newly acquired paid customers.
New metrics in the privacy-first era
The third-party cookie era had created an illusion of precision: conversion rates to the decimal point, detailed attribution paths, frequency caps on every user. Many of those metrics were already inaccurate because of multi-device usage, but the system worked well enough to be credible. With a privacy-first strategy, some metrics change in nature and need to be reinterpreted.
The most important transition is towards Marketing Mix Modelling (MMM): a statistical approach that measures each channel’s contribution to revenue without relying on individual user tracking. It had been supplanted by hyper-granular cookie-based attribution. With the end of the latter, MMM is returning as a primary tool in the most sophisticated marketing teams, and it becomes far more precise when fed with high-quality first-party data.
First-party data as a structural competitive advantage
Ultimately, a first-party data strategy is not a response to the end of cookies. It is the answer to marketing’s most fundamental question: how well do you know your customers? The answer to that question has always determined the quality of execution. Third-party cookies were a cheap proxy for that knowledge — imprecise, temporary and fundamentally not yours. First-party data is the structural answer: accurate, lasting and owned by you.
In practical terms: an Italian company that over the next 12 months structures consent with a serious CMP, integrates data into a unified CRM, implements server-side tracking and launches a zero-party data collection programme through newsletters and quizzes builds a foundation for personalisation, lookalike audiences and predictive models that competitors without proprietary data simply cannot replicate. It is not a question of budget — it is a question of method and priorities.
ISTAT figures for 2026 confirm it: 16.4% of Italian companies already use AI technologies, double the figure of a year earlier. But AI without high-quality proprietary data is an engine without fuel. The companies that will grow in the coming years are not those that use AI the most, but those that feed it the best data. And the best data is the data you have built yourself, directly, with your customers’ consent.
First-Party Data Strategy FAQs
What are first-party data?
First-party data is information collected directly by a company through its own channels — website, app, CRM, newsletter, physical stores, loyalty programmes. It is owned exclusively by the company and collected with the user’s explicit consent. Its value is twofold: accuracy (a 92% customer recognition rate vs 65% for third-party data) and absolute ownership — it does not depend on any browser or external regulation.
Has Google really abandoned the end of third-party cookies?
On 25 April 2025 Google abandoned its plan to remove third-party cookies from Chrome. But Safari and Firefox already block them by default, 40% of users actively reject them, and GDPR continues to restrict them. The shift towards a privacy-first web is structural and irreversible, regardless of Chrome. Those who build a first-party data strategy do so for structural resilience, not merely in response to Chrome.
What is zero-party data?
Zero-party data are information that users provide intentionally and proactively — stated preferences, answers to quizzes or surveys, choices in a configurator. Unlike first-party data (inferred behaviours), zero-party data are explicitly declared. They are the most valuable because they eliminate inference, maximise personalisation and are GDPR-compliant by definition.
Where do you start with a first-party data strategy?
The starting point is an audit: what is already collected, where it is fragmented, what value it generates. The second step is designing the value exchange: what you offer users in return for their data. The third is choosing the infrastructure: a CMP for consent, a CRM or CDP for unification, server-side tracking for collection. Only then do you move on to activation.
Do you need a CDP, or is a CRM enough?
It depends on complexity. If you have data fragmented across several channels and clear use cases (e.g. e-commerce + physical retail + email), a CDP generates measurable value. If you have a single channel and few touchpoints, start with CRM + marketing automation. A CDP creates value only when it is designed around concrete use cases with solid governance — it is not a passive data repository.
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