Data Quality

Executive summary 

Zero-party data is information users willingly and proactively share, like their preferences, needs, or purchase intentions, often in exchange for a better, more personalised experience. Unlike data that’s inferred or tracked, zero-party data is direct, accurate, and respects user privacy. For brands, it offers a more transparent window into real customer intent and helps anticipate opportunities (like likely purchases) and risks (like potential churn). 

Zero-party data is activated through a 10-step plan, successfully used by brands like L’Oréal, Guerlain, and Valencia CF. This approach includes interactive formats (quizzes, games, contests, etc.), incentivised data sharing, CRM integration, behavioural segmentation, and personalised messaging. Steps like account creation, omnichannel nurturing, automated conversion workflows, feedback loops, and gamified reward programs complete the strategy.  

A standout example is Visit Andorra, where zero-party data helped drive a 45% increase in site users and boosted engagement. 

Beyond marketing, zero-party data is key in training high-performance, bias-resistant AI models. When users voluntarily share qualitative information, it results in high-quality datasets leading to better personalisation, smarter targeting, and sustainable AI development.  

More broadly, a strong data strategy integrates three pillars: collection, management, and activation. Examples from Sport24, BNP Paribas, and Matas show how combining zero- and first-party data delivers measurable ROI, through better segmentation, improved targeting, and higher revenue.  

The paper concludes with a matrix linking use cases to digital platforms (DCP, MAP, CDP, DXP, COM), illustrating how organisations can align tools with strategic goals and maximise the long-term value of their corporate assets. 

Part 1 –    What is zero-party data and why is it valuable? 

Part 2 –    How can you activate zero-party data? 

Part 3 –    How can you build an integrated data stack? 

Part 4 –   How can quality data turbo charge your AI tools? 

Conclusion – A fundamental shift in data strategy 

Part 1 – What is zero-party data and why is it valuable? 

How do you define zero-party data? 

Zero-party data is information that a user proactively and intentionally shares with a brand. It includes preferences, interests, feedback, or purchase intentions. Unlike first-party data, it’s not inferred from user behaviour but explicitly provided, making it highly accurate, privacy-compliant, and trust-based 

First-party data is information a company collects directly from its audience through owned channels (websites, apps, physical stores, etc.). It includes data based on user behaviours, actions or inferred interests, for example, purchase history, click paths, browsing time, or email engagement. 

Second-party data is another organisation’s first-party data that is shared through a direct partnership, for example, a retailer sharing customer insights with a supplier. 

Third-party data is aggregated from multiple sources by external providers and sold to other companies. Both second- and third-party data offer broad audience reach but are often less accurate, not collected with direct user consent and can raise privacy concerns. 

Why is zero-party data valuable?  

Zero-party data is valuable because it reveals user intent and provides opportunities to influence future behaviour. It empowers brands to deliver personalised experiences built on trust and transparency. 

By understanding what a customer explicitly wants (their preferences, needs, or purchase intentions), brands can predict positive actions, such as the likelihood to buy a specific product, service, or content through a specific channel. 

Vice versa, zero-party data can also signal declining interest in a product or service already consumed. Recognising this allows brands to anticipate and reduce the risk of churn or disengagement and adjust messaging or offerings accordingly. 

Why do you need data sovereignty? 

Data quality goes along with regulatory trust. True data sovereignty means more than simply complying with laws like the GDPR; it means ensuring that data is fully protected from conflicting foreign laws, such as the U.S. CLOUD Act.  

To ensure this, organisations must establish clear legal and operational boundaries between regional entities, particularly between European and non-European operations. This includes:  

• Hosting data locally,  

• Restricting access to local teams only, 

• And ensuring codebases are developed and maintained within the region. 

By securing full control over how and where data is stored, accessed, and processed, businesses not only meet compliance standards but also strengthen customer trust and reinforce the integrity of their brand. 

How can you collect zero-party data? 

You can use multiple formats to collect zero-party data (source: Qualtrix).

Surveys: Don’t just drop a generic survey; make it relevant to the user’s current experience. If they just made a purchase, ask them about it

Quizzes: People love quizzes that tell them something about themselves. At the end, ask for an email to send their personalised results, and bam, you’ve got zero-party data.

Forms: Go beyond the typical “name-email-submit” format. Maybe add a few optional fields asking about their preferences, so you can personalise their experience right off the bat.

Interactive tools and funnels: Think mortgage calculators for a home loan website or a skin type assessment on a beauty site. Tools like these not only offer real-world value but can capture details about user preferences.

Transactional data: After a purchase, capture info like “how did you hear about us?” or “would you like to be part of our reward program?”

New registration: Mix up the classic registration form template with optional fields like “what are your interests?” or “how often do you shop X?” 

Part 2 – How can you activate zero-party data? 

Dozens of leading brands have collected and activated zero-party data. Their methodology is summarised in the ten-item action plan below.

Attract users with interactive experiences

Begin the customer journey by engaging audiences with fun and interactive content like quizzes, games, or polls. These experiences not only capture attention but also encourage participation.  

For example, Guerlain used a product-themed quiz to achieve a 52% opt-in rate, while M6 Group’s 15-week contest drove 57,000 games played, significantly increasing return visits and user engagement.

Incentivise data sharing

Encourage users to share their information by offering compelling incentives such as discounts, prizes, or exclusive content.  

LolaLiza ran a “Where’s Wally?” game with a trip to New York as the prize, leading to 6,020 participants and a 67% newsletter opt-in rate. Similarly, Valencia CF achieved 2,907 new opt-ins in 15 days by offering a jersey as a prize in a vote-based campaign.

Collect and store zero-party data 

Zero-party data is gathered through structured forms embedded in interactive experiences, ensuring a seamless flow. 

Brands like Clarins and Decathlon integrate data collection directly into their in-store and online campaigns, enriching CRM profiles with high-quality insights. 

Decathlon saw a 60% account creation rate by pairing data collection with opt-ins for personalised experiences, making the process effective and compliant.

Segment based on preferences

Once data is collected, segment your audience based on preference, behaviour, or demographics.  

For example, RTBF use over 50 audience segments, enabling precise targeting based on content consumption and interaction. L’Oréal capture beauty profiles (like skin or hair type) to refine personalisation strategies across their portfolio.

Personalise communication

Tailor messaging for each user segment to maximise relevance and engagement.  

Clarins reported a 69% open rate for email sent after interactive experiences, showing how personalisation boosts effectiveness. LolaLiza adapted their newsletter subject lines and Facebook ads based on users’ astrological signs, driving higher engagement.

Drive account creation

Once trust is built, encourage users to create accounts to unlock further benefits.  

L’Oréal achieved 60–70% account creation rates through targeted campaigns. RTBF implemented single sign-on (SSO) to unify user identity across its media ecosystem, reducing friction and improving retention.

Nurture with omnichannel campaigns

Maintain continuous engagement across multiple channels.  

Valencia CF combined email and social media to promote a sponsor quiz that attracted over 4,200 participants in just 8 days. Clarins used pop-ups, newsletters, and in-store QR codes to bridge digital and physical interactions.

Trigger conversion scenarios

Use automated workflows based on user behaviour to drive purchases.  

LolaLiza convert 10% of leads acquired via Qualifio into buyers through tailored offers and onboarding sequences. Decathlon’s checklist campaign delivered personalised recommendations, reaching 2.7% conversion rate. During Valentine’s Day, Frenchbee generated 18,000 users, converted 11,000 into accounts and secured 177 flight reservations, driving €150,000 in revenue.

Collect post-conversion feedback

Run surveys after conversion to gather insights and refine future interactions.  

Clarins uses conditional branching surveys to understand customer needs and improve services. Thess insights feed into CRM and segmentation, enhancing the next wave of personalized experiences.

Establish reward programs

Build loyalty with gamified programs that reward interaction and encourage repeat behaviour. 

RTBF’s World Cup campaign attracted 18,000 members and over 60,000 participations, with 85% of members remaining active throughout. These programs foster long-term relationships and increase lifetime value. 

Use case – Visit Andorra: Activating zero-party data to drive tourism 

Visit Andorra, the official tourism body of the Principality of Andorra, has embraced a digital transformation strategy to stand out in a highly competitive tourism market. Leveraging a Digital Experience Platform (DXP), Visit Andorra has made zero-party data the cornerstone of their personalisation efforts.

Challenge: Tourism represents 50% of Andorra’s GDP, making visitor attraction a national priority. Visit Andorra needed to better understand their users, improve digital engagement, and boost conversion from casual site visits to real bookings while managing multilingual international campaigns.

Strategy: The key strategy was to collect and activate information users intentionally share (zero-party data), such as travel preferences. Using a gamified travel configurator, users could build their ideal itineraries without registering. When they chose to save or share these plans, Visit Andorra collected rich data profiles linked to their CRM. This setup enabled segmented marketing and a highly tailored user experience.

Execution: Visit Andorra activated this data through DXP’s (Digital Experience Platform) personalisation capabilities. Users received location- and season-specific content, while campaign landing pages were dynamically adjusted to match visitor personas. Editors utilised this zero-party data to create predefined itineraries and deliver more relevant content to each user segment. Integration with booking systems and tour services enabled seamless transitions from browsing to booking.

Conclusion: Visit Andorra’s case proves the value of zero-party data in the tourism sector. By blending voluntary user input, strategic content activation, and a flexible DXP, the organisation has built a scalable and trust-driven personalisation engine that turns casual browsers into loyal visitors.

Results: Zero-party data activation has delivered measurable success: 

• Increased engagement through the Andorra World Fan community. 
• Reduced bounce rates and longer session durations 
• 40% of traffic generated organically through SEO 
• 1.2 million new users in a single year 
• 45% year-over-year increase in site users 

Part 3 – How can you build an integrated data stack? 

An integrated data stack starts with scalable data collection and integrates data management, data activation, data feedback and data enrichment. The diagram below shows integrated data platforms that work together to help collect, manage and activate customer and product data across channels: web, email, SMS, push.​ 

An integrated data stack

Let us review 3 critical components: data collection, management and activation through the lenses of several client success stories and their associated KPIs.  

Step 1 – Collecting zero-party data 

Zero-party data are prime examples of quality data.  

Use case: at L’Oréal EMEA, the data collection platform “is being used in 13 countries by 28 brands representing 70% of the group’s brands.  

The team collects zero-party data such as skin and hair type, preferences, and beauty interests through engaging formats like quizzes, games, and e-sampling campaigns, combining engagement with data capture. 

In just over a year, L’Oréal EMEA has created over 700 campaigns and reached over 5.5 million users. The percentage of accounts created per campaign varies between 60% and 70%. This gives L’Oréal a data collection tool, that helps recruit new customers and enrich data of their existing customers” (Qualifio). 

Step 2 – Managing zero-party and first-party data 

Zero-party and first-party data can help measure and monitor customer behaviour on digital channels (web, app) and physical channels (POS, store). It can segment your audience into many customer segments: brand ambassadors, churning VIPs, potential loyals, low-value loyals, low value churners, serial returners, window shoppers, gift buyers, category affinity, seasonal shoppers, brand lovers, sales lovers, etc. 

Use case: Sport24 (Retail Chain in Denmark), “has added 100,000 new subscribers to their customer loyalty club by working strategically with segments created by their CDP (Customer Data Platform). Sport24 has activated audiences on Facebook channel and achieved a lift of 92% on Return on Assets” (Raptor). 

Step 3 – Activating zero-party and first-party data 

When activated, quality data provides critical KPIs such as the increase in reach, visits or revenue. In turn, these KPIs help measure financial metrics that will drive return on the assets that have been exposed through the campaigns. 

Use case: BNP Paribas Private Banking wanted “to position itself as a “Conversational Bank”. The relational data model adopted by BNP Paribas Private Bank has enabled it to achieve better targeting in its marketing campaigns. As a result, +15% of customers were reached by these new campaigns and +15,000 personalized emailing campaigns” (Actito). 

Use case: Matas (Nordic region’s largest digital beauty success), “new omnichannel strategy and innovative initiatives leveraging E-Commerce have made online revenue grow from €14m to €145m (10x) in 3 years” (Bizzkit). 

Step 4 – Measuring economic returns 

Your data strategy must bring measurable return on investment: it can help power sales prospection, refine marketing segmentation, develop nurturing campaigns, build loyalty campaigns and improve catalogue management. 

KPI’s of successful data stacks 

Part 4 – How can quality data turbocharge your AI strategy?  

Quality data and Machine Learning (ML) models 

We’ve seen it: leading consumer brands like Nestlé or L’Oréal already collect millions of zero-party data from millions of potential customers.  

Such high-quality data can be used to train custom Machine Learning (ML) models, for example for hyper personalisation of experience, product or content recommendation, or efficient targeted advertising campaigns. 

More generally, data collection and data quality were two challenges reported by 57% of Nordic companies in 2024 (source: Silo.ai “Status of AI” report). 

Risks of bias and infringement 

We know it: without quality data, AI models create dangerous hallucinations, nefarious biases, regulatory non-compliance, copyright infringement. 

If a person or community is stigmatised on the public internet, the output of AI models will directly reflect this stigma, it will propagate and reinforce this bias.  

An example of alleged infringement was provided in 2024, when The New York Times sued OpenAI for copyright infringement. 

Sustainable AI 

Without quality data, AI models have also inflated to levels that are not sustainable. A very large model like GPT4 manages over 175 billion parameters (weights attributed to transformer functions in neural networks). Its training has required dozens of millions of dollars and created 12 to 15 tons of CO2 (25,000 Nvidia A100 GPUs for 90-100 days). This has represented 10x the footprint of GPT3 (source: TDS). 

As a result, AI models are downscaling from Large to Small Language Models such as Phi2 from Microsoft. Although the observation is made on a certain type of AI models (Large Language Models), we expect this downscaling to propagate to other AI models. Custom AI models produce high yields with only ten million parameters, at the scale of an individual organization. 

Small models leveraging quality data save large human, financial and carbon resources. Data quality and data efficiency also brings higher yields: tests have shown that language models can perform well with only 10 million parameters. 

Exhaustion of high-quality data 

In the future, we are not guaranteed to own and operate enough high-quality data: a research institute has projected exhaustion of high-quality language data in 2024 for Machine Learning (source: Epoch 2024 AI Index Report).  

Exhaustion could also occur with high-quality customer data. The volume of formal opt-ins one user can provide to brands is limited. The volume of potential consent and hence of zero-party data could at some point also reach exhaustion.  

Conclusion – A fundamental shift in data strategy 

Zero-party data represent a shift in how organisations build trust and drive performance in the digital age. Unlike inferred data, it is voluntarily shared, privacy-compliant, and immensely powerful when activated strategically.  

From enabling hyper-personalised marketing and fueling efficient AI models to anchoring sustainable and ROI-driven data strategies, zero-party data is the cornerstone of customer-centric innovation. 

The opportunity lies not just in collecting such data, but in designing systems and experiences, backed by DXP, MAP, CDP, and COM platforms, that can transform data strategy into sustained value for both brands and consumers. 

Jean-Claude Pitcho is a Vice President at QNTM, a group of MarTech companies embracing this shift towards aggregation by offering best-in-class platforms that work seamlessly together to create total customer solutions. These solutions can include data collection, customer data management, customer experience, online commerce, marketing automation and push notifications: everything that is needed to improve conversion rate, top line and bottom line.