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  • A Guide to App Analytics Tools that Drive Growth

    7 mars, par Daniel Crough — App Analytics

    Mobile apps are big business, generating £438 billion in global revenue between in-app purchases (38%) and ad revenue (60%). And with 96% of apps relying on in-app monetisation, the competition is fierce.

    To succeed, app developers and marketers need strong app analytics tools to understand their customers’ experiences and the effectiveness of their development efforts.

    This article discusses app analytics, how it works, the importance and benefits of mobile app analytics tools, key metrics to track, and explores five of the best app analytics tools on the market.

    What are app analytics tools ?

    Mobile app analytics tools are software solutions that provide insights into how users interact with mobile applications. They track user behaviour, engagement and in-app events to reveal what’s working well and what needs improvement.

    Insights gained from mobile app analytics help companies make more informed decisions about app development, marketing campaigns and monetisation strategies.

    What do app analytics tools do ?

    App analytics tools embed a piece of code, called a software development kit (SDK), into an app. These SDKs provide the essential infrastructure for the following functions :

    • Data collection : The SDK collects data within your app and records user actions and events, like screen views, button clicks, and in-app purchases.
    • Data filtering : SDKs often include mechanisms to filter data, ensuring that only relevant information is collected.
    • Data transmission : Once collected and filtered, the SDK securely transmits the data to an analytics server. The SDK provider can host this server (like Firebase or Amplitude), or you can host it on-premise.
    • Data processing and analysis : Servers capture, process and analyse large stores of data and turn it into useful information.
    • Visualisation and reporting : Dashboards, charts and graphs present processed data in a user-friendly format.
    Schematics of how mobile app analytics tools work

    Six ways mobile app analytics tools fuel marketing success and drive product growth

    Mobile app analytics tools are vital in driving product development, enhancing user experiences, and achieving business objectives.

    #1. Improving user understanding

    The better a business understands its customers, the more likely it is to succeed. For mobile apps, that means understanding how and why people use them.

    Mobile analytics tools provide detailed insights into user behaviours and preferences regarding apps. This knowledge helps marketing teams create more targeted messaging, detailed customer journey maps and improve user experiences.

    It also helps product teams understand the user experience and make improvements based on those insights.

    For example, ecommerce companies might discover that users in a particular area are more likely to buy certain products. This allows the company to tailor its offers and promotions to target the audience segments most likely to convert.

    #2 Optimising monetisation strategies for increased revenue and user retention

    In-app purchases and advertising make up 38% and 60% of mobile app revenue worldwide, respectively. App analytics tools provide insights companies need to optimise app monetisation by :

    • Analysing purchase patterns to identify popular products and understand pricing sensitivities.
    • Tracking in-app behaviour to identify opportunities for enhancing user engagement.

    App analytics can track key metrics like visit duration, user flow, and engagement patterns. These metrics provide critical information about user experiences and can help identify areas for improvement.

    How meaningful are the impacts ?

    Duolingo, the popular language learning app, reported revenue growth of 45% and an increase in daily active users (DAU) of 65% in its Q4 2023 financial report. The company attributed this success to its in-house app analytics platform.

    Duolingo logo showing statistics of growth from 2022 to 2023, in part thanks to an in-house app analytics tool.

    #3. Understanding user experiences

    Mobile app analytics tools track the performance of user interactions within your app, such as :

    • Screen views : Which screens users visit most frequently
    • User flow : How users navigate through your app
    • Session duration : How long users spend in your app
    • Interaction events : Which buttons, features, and functions users engage with most

    Knowing how users interact with your app can help refine your approach, optimise your efforts, and drive more conversions.

    #4. Personalising user experiences

    A recent McKinsey survey showed that 71% of users expect personalised app experiences. Product managers must stay on top of this since 76% of users get frustrated if they don’t receive the personalisation they expect.

    Personalisation on mobile platforms requires data capture and analysis. Mobile analytics platforms can provide the data to personalise the user onboarding process, deliver targeted messages and recommend relevant content or offers.

    Spotify is a prime example of personalisation done right. A recent case study by Pragmatic Institute attributed the company’s growth to over 500 million active daily users to its ability to capture, analyse and act on :

    • Search behaviour
    • Individual music preferences
    • Playlist data
    • Device usage
    • Geographical location

    The streaming service uses its mobile app analytics software to turn this data into personalised music recommendations for its users. Spotify also has an in-house analytics tool called Spotify Premium Analytics, which helps artists and creators better understand their audience.

    #5. Enhancing app performance

    App analytics tools can help identify performance issues that might be affecting user experience. By monitoring metrics like load time and app performance, developers can pinpoint areas that need improvement.

    Performance optimisation is crucial for user retention. According to Google research, 53% of mobile site visits are abandoned if pages take longer than three seconds to load. While this statistic refers to websites, similar principles apply to apps—users expect fast, responsive experiences.

    Analytics data can help developers prioritise performance improvements by showing which screens or features users interact with most frequently, allowing teams to focus their optimisation efforts where they’ll have the greatest impact.

    #6. Identifying growth opportunities

    App analytics tools can reveal untapped opportunities for growth by highlighting :

    • Features users engage with most
    • Underutilised app sections that might benefit from redesign
    • Common user paths that could be optimised
    • Moments where users tend to drop off

    This intelligence helps product teams make data-informed decisions about future development priorities, feature enhancements, and potential new offerings.

    For example, a streaming service might discover through analytics that users who create playlists have significantly higher retention rates. This insight could lead to development of enhanced playlist functionality to encourage more users to create them, ultimately boosting overall retention.

    Key app metrics to track

    Using mobile analytics tools, you can track dozens of key performance indicators (KPIs) that measure everything from customer engagement to app performance. This section focuses on the most important KPIs for app analytics, classified into three categories :

    • App performance KPIs
    • User engagement KPIs
    • Business impact KPIs

    While the exact metrics to track will vary based on your specific goals, these fundamental KPIs form the foundation of effective app analytics.

    Mobile App Analytics KPIs

    App performance KPIs

    App performance metrics tell you whether an app is reliable and operating properly. They help product managers identify and address technical issues that may negatively impact user experiences.

    Some key metrics to assess performance include :

    • Screen load time : How quickly screens load within your app
    • App stability : How often your app crashes or experiences errors
    • Response time : How quickly your app responds to user interactions
    • Network performance : How efficiently your app handles data transfers

    User engagement KPIs

    Engagement KPIs provide insights into how users interact with an app. These metrics help you understand user behaviour and make UX improvements.

    Important engagement metrics include :

    • Returning visitors : A measure of how often users return to an app
    • Visit duration : How long users spend in your app per session
    • User flow : Visualisation of the paths users take through your app, offering insights into navigation patterns
    • Event tracking : Specific interactions users have with app elements
    • Screen views : Which screens are viewed most frequently

    Business impact KPIs

    Business impact KPIs connect app analytics to business outcomes, helping demonstrate the app’s value to the organisation.

    Key business impact metrics include :

    • Conversion events : Completion of desired actions within your app
    • Goal completions : Tracking when users complete specific objectives
    • In-app purchases : Monitoring revenue from within the app
    • Return on investment : Measuring the business value generated relative to development costs

    Privacy and app analytics : A delicate balance

    While app analytics tools can be a rich source of user data, they must be used responsibly. Tracking user in-app behaviour and collecting user data, especially without consent, can raise privacy concerns and erode user trust. It can also violate data privacy laws like the GDPR in Europe or the OCPA, FDBR and TDPSA in the US.

    With that in mind, it’s wise to choose user-tracking tools that prioritise user privacy while still collecting enough data for reliable analysis.

    Matomo is a privacy-focused web and app analytics solution that allows you to collect and analyse user data while respecting user privacy and following data protection rules like GDPR.

    The five best app analytics tools to prove marketing value

    In this section, we’ll review the five best app analytics tools based on their features, pricing and suitability for different use cases.

    Matomo — Best for privacy-compliant app analytics

    Matomo app analytics is a powerful, open-source platform that prioritises data privacy and compliance.

    It offers a suite of features for tracking user engagement and conversions across websites, mobile apps and intranets.

    Key features

    • Complete data ownership : Full control over your analytics data with no third-party access
    • User flow analysis : Track user journeys across different screens in your app
    • Custom event tracking : Monitor specific user interactions with customisable events
    • Ecommerce tracking : Measure purchases and product interactions
    • Goal conversion monitoring : Track completion of important user actions
    • Unified analytics : View web and app analytics in one platform for a complete digital picture

    Benefits

    • Eliminate compliance risks without sacrificing insights
    • Get accurate data with no sampling or data manipulation
    • Choose between self-hosting or cloud deployment
    • Deploy one analytics solution across your digital properties (web and app) for a single source of truth

    Pricing

    PlanPrice
    CloudStarts at £19/month
    On-PremiseFree

    Matomo is a smart choice for businesses that value data privacy and want complete control over their analytics data. It’s particularly well-suited for organisations in highly regulated industries, like banking.

    While Matomo’s app analytics features focus on core analytics capabilities, its privacy-first approach offers unique advantages. For organisations already using Matomo for web analytics, extending to mobile creates a unified analytics ecosystem with consistent privacy standards across all digital touchpoints, giving organisations a complete picture of the customer journey.

    Firebase — Best for Google services integration

    Firebase is the mobile app version of Google Analytics. It’s the most popular app analytics tool on the market, with over 99% of Android apps and 77% of iOS apps using Firebase.

    Firebase is popular because it works well with other Google services. It also has many features, like crash reporting, A/B testing and user segmentation.

    Pricing

    PlanPrice
    SparkFree
    BlazePay-as-you-go based on usage
    CustomBespoke pricing for high-volume enterprise users

    Adobe Analytics — Best for enterprise app analytics

    Adobe Analytics is an enterprise-grade analytics solution that provides valuable insights into user behaviour and app performance.

    It’s part of the Adobe Marketing Cloud and integrates easily with other Adobe products. Adobe Analytics is particularly well-suited for large organisations with complex analytics needs.

    Pricing

    PlanPrice
    SelectPricing on quote
    PrimePricing on quote
    UltimatePricing on quote

    While you must request a quote for pricing, Scandiweb puts Adobe Analytics at £2,000/mo–£2,500/mo for most companies, making it an expensive option.

    Apple App Analytics — Best for iOS app analysis

    Apple App Analytics is a free, built-in analytics tool for iOS app developers.

    This analytics platform provides basic insights into user engagement, app performance and marketing campaigns. It has fewer features than other tools on this list, but it’s a good place for iOS developers who want to learn how their apps work.

    Pricing

    Apple Analytics is free.

    Amplitude — Best for product analytics

    Amplitude is a product analytics platform that helps businesses understand user behaviour and build better products.

    It excels at tracking user journeys, identifying user segments and measuring the impact of product changes. Amplitude is a good choice for product managers and data analysts who want to make informed decisions about product development.

    Pricing

    PlanPrice
    StarterFree
    PlusFrom £49/mo
    GrowthPricing on quote

    Choose Matomo’s app analytics to unlock growth

    App analytics tools help marketers and product development teams understand user experiences, improve app performance and enhance products. Some of the best app analytics tools available for 2025 include Matomo, Firebase and Amplitude.

    However, as you evaluate your options, consider taking a privacy-first approach to app data collection and analysis, especially if you’re in a highly regulated industry like banking or fintech. Matomo Analytics offers a powerful and ethical solution that allows you to gain valuable insights while respecting user privacy.

    Ready to take control of your app analytics ? Start your 21-day free trial.

  • A Primer to Ethical Marketing : How to Build Trust in a Privacy-First World

    11 mars, par Alex Carmona — Marketing, Privacy, ethical marketing

    Imagine a marketing landscape where transparency replaces tactics, where consumer privacy is prioritised over exploitation, and where authentic value builds genuine relationships.

    This isn’t just an ideal—it’s the future of marketing. And it starts with ethical marketing practices.

    76% of consumers refuse to buy from companies they do not trust with their data. Ethical marketing has become essential for business survival. As privacy regulations tighten and third-party cookies phase out, marketers face a critical question : how can they balance effective, personalised campaigns whilst respecting privacy ?

    This comprehensive guide explores what ethical marketing is, the key principles behind ethical marketing practices, and practical strategies to implement an ethical approach that builds trust while driving growth.

    What is ethical marketing ? A comprehensive definition

    Ethical marketing places respect for consumer boundaries at its core whilst delivering genuine value. It prioritises transparent practices, honest communication, and fair value exchange with consumers. This approach represents a significant shift from traditional marketing, which often relied on collecting vast amounts of user data through invasive tracking methods and obscure policies.

    The modern approach to ethical marketing creates a foundation built on three key pillars :

    • User Control : Giving people genuine choice and agency over their data
    • Fair Value : Providing clear benefits in exchange for any data shared
    • Transparency : Being honest about how data is collected, used, and protected
    ethical marketing guide ad

    Key principles of ethical marketing

    Transparency

    Transparency means being clear and forthright about your marketing practices, data collection policies, and business operations. It involves :

    • Using plain language to explain how you collect and use customer data
    • Being upfront about pricing, product limitations, and terms of service
    • Disclosing sponsored content and affiliate relationships
    • Making privacy policies accessible and understandable

    When Matomo surveyed 2,000 consumers, 81% said they believe an organisation’s data practices reflect their overall treatment of customers. Transparency isn’t just about compliance—it’s about demonstrating respect.

    Honesty

    While similar to transparency, honesty focuses specifically on truthfulness in communications :

    • Avoiding misleading claims or exaggerations about products and services
    • Not manipulating statistics or research findings to support marketing narratives
    • Representing products accurately in advertisements and marketing materials
    • Acknowledging mistakes and taking responsibility when things go wrong

    Social responsibility

    Ethical marketing requires consideration of a brand’s impact on society as a whole :

    • Considering environmental impacts of marketing campaigns and business practices
    • Promoting diversity and inclusion in marketing representations
    • Supporting social causes authentically rather than through “purpose-washing”
    • Ensuring marketing activities don’t promote harmful stereotypes or behaviours

    Ethical marketing dilemmas : Navigating complex business decisions

    Data privacy concerns

    The digital marketing landscape has been transformed by increasing awareness of data privacy issues and stricter regulations like GDPR, CCPA, and upcoming legislation. Key challenges include :

    • The phase-out of third-party cookies, impacting targeting and measurement
    • Growing consumer resistance to invasive tracking technologies
    • Balancing personalisation with privacy (71% of consumers expect personalised experiences, yet demand privacy)
    • Ensuring compliance across different jurisdictional requirements

    Cultural sensitivity

    Global brands must navigate complex cultural landscapes :

    • Avoiding cultural appropriation in marketing campaigns
    • Understanding varied cultural expectations around privacy
    • Respecting local customs and values in international marketing
    • Adapting messaging appropriately for diverse audiences

    Environmental sustainability

    The environmental impact of marketing activities is under increasing scrutiny :

    • Digital carbon footprints from ad serving and website hosting
    • Waste generated from physical marketing materials
    • Promoting sustainable products honestly without greenwashing
    • Aligning marketing messages with actual business practices

    The benefits of ethical marketing

    For years, digital marketing has relied on third-party data collection and broad-scale tracking. However, new regulations such as GDPR, CCPA, and the end of third-party cookies are pushing brands to adopt ethical data practices.

    Increased customer loyalty

    Ethical marketing fosters deeper relationships with customers by building trust. Research consistently shows that consumers are more loyal to brands they trust, with 71% indicating they would stop buying from a brand if trust is broken.

    These trust-based relationships are more resilient during business challenges. When customers believe in a company’s integrity, they’re more likely to give the benefit of the doubt during controversies or service issues. They’re also more likely to provide constructive feedback rather than simply leaving for competitors.

    Perhaps most importantly, loyal customers become advocates, sharing positive experiences with others and defending the brand against criticism. This organic advocacy is far more powerful than paid promotions and reduces customer acquisition costs significantly over time.

    Enhanced brand reputation

    A strong ethical stance improves overall brand perception across multiple dimensions. Media outlets are increasingly focused on corporate behaviour, providing positive coverage for ethical practices that extends a brand’s reach organically.

    Social conversations about ethical brands tend to be more positive, with consumers sharing experiences and values rather than just discussing products. This creates a halo effect that benefits all aspects of the business.

    This enhanced reputation also provides resilience during public relations challenges. Organisations with strong ethical foundations find it easier to navigate controversies because they’ve built a reservoir of goodwill with customers, employees, and other stakeholders.

    Competitive advantage

    Ethical marketing provides several distinct competitive advantages in modern markets. It helps brands access privacy-conscious consumer segments that actively avoid companies with questionable data practices. These segments often include higher-income, educated consumers who are valuable long-term customers.

    Ethical approaches also reduce vulnerability to regulatory changes and potential penalties. As privacy laws continue to evolve globally, organisations with strong ethical foundations find compliance easier and less disruptive than those scrambling to meet minimum requirements.

    Perhaps most significantly, ethical marketing supports more sustainable growth trajectories. While manipulative tactics might drive short-term results, they typically lead to higher churn rates and increasing acquisition costs. Ethical approaches build foundations for long-term success and stable growth.

    For a detailed roadmap, download the Ethical Marketing Guide.

    Case studies : Ethical marketing in action

    Patagonia : Purpose-driven marketing

    Patagonia integrates sustainability into its marketing, reinforcing its commitment to ethical business practices. By aligning with social causes, the brand strengthens customer loyalty.

    Apple : Privacy as a competitive advantage

    Apple positions itself as a leader in consumer privacy, ensuring data protection remains central to its marketing strategy. This commitment has become a key differentiator in the tech industry.

    Matomo : The ethical analytics tool

    Matomo offers privacy-first analytics that prioritise data ownership and compliance. Businesses using Matomo benefit from accurate insights while respecting user privacy.

    These companies demonstrate that ethical marketing is not just a compliance requirement—it is a long-term competitive advantage.

    Strategies for implementing ethical marketing

    Aligning marketing efforts with brand values

    Consistency between values and actions is essential for ethical marketing. This alignment starts with a clear understanding of what your organisation truly stands for—not just aspirational statements, but genuine commitments that inform daily decisions.

    Implementing this alignment requires cross-functional collaboration. Marketing teams need to work closely with product development, customer service, and leadership to ensure consistency across all touchpoints. When different departments send contradictory messages about company values, trust erodes quickly.

    Clear guidelines help marketing teams apply values in practical decisions, from campaign concepts to media placements. Regular ethical reviews of marketing plans can identify potential issues before campaigns launch, avoiding reactive corrections that damage credibility.

    Privacy-first data strategies

    Developing robust approaches to customer data is fundamental to ethical marketing. This starts with prioritising first-party data (collected directly from your own channels) and zero-party data (actively shared by customers through preference centres, surveys, and similar mechanisms).

    Measuring success doesn’t have to come at the expense of privacy. Ethical analytics provide accurate insights while protecting user data, ensuring compliance, and enhancing customer trust.

    Ethical personalisation approaches focus on using aggregated or anonymised data rather than individual tracking. This allows for relevant experiences without the invasive feeling that erodes trust when consumers feel watched across the internet.

    Most importantly, ethical data strategies create transparent value exchanges where users clearly understand what benefits they receive in return for sharing information. This reciprocity transforms data collection from exploitation to fair exchange.

    Measuring success ethically

    Traditional marketing measurement often relies on individual-level tracking across sites and platforms. Ethical approaches require adapting these frameworks to respect privacy while still demonstrating impact.

    Focusing on aggregate patterns rather than individual behaviour provides valuable insights without privacy invasions. For example, understanding that 30% of visitors to a specific page subsequently make purchases is actionable intelligence that doesn’t require tracking specific people.

    Incrementality testing measures campaign impact by comparing outcomes between exposed and control groups at an aggregate level. This provides more accurate attribution than traditional last-click models while respecting privacy boundaries.

    Server-side conversion tracking offers another ethical measurement approach, collecting necessary data on your servers rather than through client-side scripts vulnerable to blocking. This improves data accuracy while reducing reliance on cookies and browser storage.

    Implementing ethical marketing strategies : A practical framework

    1. Align marketing with brand values – Ensure campaigns reflect transparency and trust

    2. Leverage first-party data – Collect insights directly from consumers with clear consent

    3. Respect privacy and consent – Give users control over their data and clearly communicate its use

    4. Create value-driven content – Offer educational and relevant resources instead of relying solely on advertising

    5. Use privacy-compliant analytics – Switch to ethical platforms such as Matomo for responsible performance measurement

    For a step-by-step guide to implementing ethical marketing strategies, download the full report here.

    five step ethical marketing framework diagram

    The future of ethical marketing

    With the decline of third-party cookies and the rise of privacy regulations, ethical marketing is no longer optional. Brands that adopt privacy-first practices now will gain a sustainable competitive edge in the long term. The future of marketing belongs to brands that earn consumer trust, not those that exploit it.

    Key trends shaping the future of marketing include :

    • Privacy-first analytics to replace invasive tracking
    • First-party and zero-party data strategies for direct consumer engagement
    • Consent-driven personalisation to balance relevance and privacy
    • Greater emphasis on corporate social responsibility in marketing initiatives

    Companies that proactively address these changes will build stronger customer relationships, enhance brand reputation, and ensure long-term success.

    Take the next step

    Ready to transform your marketing approach for 2025 and beyond ?

    Download Matomo’s comprehensive “2025 Ethical Marketing Field Guide” to get practical frameworks, implementation strategies, and real-world case studies that will help you build trust while driving growth.

    With detailed guidance on first-party data activation, consent-based personalisation techniques, and privacy-preserving analytics methods, this guide provides everything you need to future-proof your marketing strategy in a privacy-first world.

    ethical marketing guide ad

    Download the ethical marketing guide now to start building stronger, more trusted relationships with your customers through ethical marketing practices.

  • Making Your First-Party Data Work for You and Your Customers

    11 mars, par Alex Carmona

    At last count, 162 countries had enacted data privacy policies of one kind or another. These laws or regulations, without exception, intend to eliminate the use of third-party data. That puts marketing under pressure because third-party data has been the foundation of online marketing efforts since the dawn of the Internet.

    Marketers need to future-proof their operations by switching to first-party data. This will require considerable adjustment to systems and processes, but the reward will be effective marketing campaigns that satisfy privacy compliance requirements and bring the business closer to its customers.

    To do that, you’ll need a coherent first-party data strategy. That’s what this article is all about. We’ll explain the different types of personal data and discuss how to use them in marketing without compromising or breaching data privacy regulations. We’ll also discuss how to build that strategy in your business. 

    So, let’s dive in.

    The different data types

    There are four distinct types of personal data used in marketing, each subject to different data privacy regulations.

    Before getting into the different types, it’s essential to understand that all four may comprise one or more of the following :

    Identifying dataName, email address, phone number, etc.
    Behavioural dataWebsite activity, app usage, wishlist content, purchase history, etc.
    Transactional dataOrders, payments, subscription details, etc.
    Account dataCommunication preferences, product interests, wish lists, etc.
    Demographic dataAge, gender, income level, education, etc.
    Geographic DataLocation-based information, such as zip codes or regional preferences.
    Psychographic DataInterests, hobbies and lifestyle preferences.

    First-party data

    When businesses communicate directly with customers, any data they exchange is first-party. It doesn’t matter how the interaction occurs : on the telephone, a website, a chat session, or even in person.

    Of course, the parties involved aren’t necessarily individuals. They may be companies, but people within those businesses will probably share at least some of the data with colleagues. That’s fine, so long as the data : 

    • Remains confidential between the original two parties involved, and 
    • It is handled and stored following applicable data privacy regulations.

    The core characteristic of first-party data is that it’s collected directly from customer interactions. This makes it reliable, accurate and inherently compliant with privacy regulations — assuming the collecting party complies with data privacy laws.

    A great example of first-party data use is in banking. Data collected from customer interactions is used to provide personalised services, detect fraud, assess credit risk and improve customer retention.

    Zero-party data

    There’s also a subset of first-party data, sometimes called zero-party data. It’s what users intentionally and proactively share with a business. It can be preferences, intentions, personal information, survey responses, support tickets, etc.

    What makes it different is that the collection of this data depends heavily on the user’s trust. Transparency is a critical factor, too ; visitors expect to be informed about how you’ll use their data. Consumers also have the right to withdraw permission to use all or some of their information at any time.

    Diagram showing how a first-party data strategy is built on trust and transparency

    Second-party data

    This data is acquired from a separate organisation that collects it firsthand. Second-party data is someone else’s first-party data that’s later shared with or sold to other businesses. The key here is that whoever owns that data must give explicit consent and be informed of who businesses share their data with.

    A good example is the cooperation between hotel chains, car rental companies, and airlines. They share joint customers’ flight data, hotel reservations, and car rental bookings, much like travel agents did before the internet undermined that business model.

    Third-party data

    This type of data is the arch-enemy of lawmakers and regulators trying to protect the personal data of citizens and residents in their country. It’s information collected by entities that have no direct relationship with the individuals whose data it is.

    Third-party data is usually gathered, aggregated, and sold by data brokers or companies, often by using third-party cookies on popular websites. It’s an entire business model — these third-party brokers sell data for marketing, analytics, or research purposes. 

    Most of the time, third-party data subjects are unaware that their data has been gathered and sold. Hence the need for strong data privacy regulations.

    Benefits of a first-party data strategy

    First-party data is reliable, accurate, and ethically sourced. It’s an essential part of any modern digital marketing strategy.

    More personalised experiences

    The most important application of first-party data is customising and personalising customers’ interactions based on real behaviours and preferences. Personalised experiences aren’t restricted to websites and can extend to all customer communication.

    The result is company communications and marketing messages are far more relevant to customers. It allows businesses to engage more meaningfully with them, building trust and strengthening customer relationships. Inevitably, this also results in stronger customer loyalty and better customer retention.

    Greater understanding of customers

    Because first-party data is more accurate and reliable, it can be used to derive valuable insights into customer needs and wants. When all the disparate first-party data points are centralised and organised, it’s possible to uncover trends and patterns in customer behaviour that might not be apparent using other data.

    This helps businesses predict and respond to customer needs. It also allows marketing teams to be more deliberate when segmenting customers and prospects into like-minded groups. The data can also be used to create more precise personas for future campaigns or reveal how likely a customer would be to purchase in response to a campaign.

    Build trust with customers

    First-party data is unique to a business and originates from interactions with customers. It’s also data collected with consent and is “owned” by the company — if you can ever own someone else’s data. If treated like the precious resource, it can help businesses build trust with customers.

    However, developing that trust requires a transparent, step-by-step approach. This gradually strengthens relationships to the point where customers are more comfortable sharing the information they’re asked for.

    However, while building trust is a long and sometimes arduous process, it can be lost in an instant. That’s why first-party data must be protected like the Crown Jewels.

    Image showing the five key elements of a first-party data strategy

    Components of a first-party data strategy

    Security is essential to any first-party data strategy, and for good reason. As Gartner puts it, a business must find the optimal balance between business outcomes and data risk mitigation. Once security is baked in, attention can turn to the different aspects of the strategy.

    Data collection

    There are many ways to collect first-party data ethically, within the law and while complying with data privacy regulations, such as Europe’s General Data Protection Regulation (GDPR). Potential sources include :

    Website activityforms and surveys, behavioural tracking, cookies, tracking pixels and chatbots
    Mobile app interactionsin-app analytics, push notifications and in-app forms
    Email marketingnewsletter sign-ups, email engagement tracking, promotions, polls and surveys 
    Eventsregistrations, post-event surveys and virtual event analytics
    Social media interactionpolls and surveys, direct messages and social media analytics
    Previous transactionspurchase history, loyalty programmes and e-receipts 
    Customer service call centre data, live chat, chatbots and feedback forms
    In-person interactions in-store purchases, customer feedback and Wi-Fi sign-ins
    Gated contentwhitepapers, ebooks, podcasts, webinars and video downloads
    Interactive contentquizzes, assessments, calculators and free tools
    CRM platformscustomer profiles and sales data
    Consent managementprivacy policies, consent forms, preference setting

    Consent management

    It may be the final item on the list above, but it’s also a key requirement of many data privacy laws and regulations. For example, the GDPR is very clear about consent : “Processing personal data is generally prohibited, unless it is expressly allowed by law, or the data subject has consented to the processing.”

    For that reason, your first-party data strategy must incorporate various transparent consent mechanisms, such as cookie banners and opt-in forms. Crucially, you must provide customers with a mechanism to manage their preferences and revoke that consent easily if they wish to.

    Data management

    Effective first-party data management, mainly its security and storage, is critical. Most data privacy regimes restrict the transfer of personal data to other jurisdictions and even prohibit it in some instances. Many even specify where residents’ data must be stored.

    Consider this cautionary tale : The single biggest fine levied for data privacy infringement so far was €1.2 billion. The Irish Data Protection Commission imposed a massive fine on Meta for transferring EU users’ data to the US without adequate data protection mechanisms.

    Data security is critical. If first-party data is compromised, it becomes third-party data, and any customer trust developed with the business will evaporate. To add insult to injury, data regulators could come knocking. That’s why the trend is to use encryption and anonymisation techniques alongside standard access controls.

    Once security is assured, the focus is on data management. Many businesses use a Customer Data Platform. This software gathers, combines and manages data from many sources to create a complete and central customer profile. Modern CRM systems can also do that job. AI tools could help find patterns and study them. But the most important thing is to keep databases clean and well-organised to make it easier to use and avoid data silos.

    Data activation

    Once first-party data has been collected and analysed, it needs to be activated, which means a business needs to use it for the intended purpose. This is the implementation phase where a well-constructed first-party strategy pays off. 

    The activation stage is where businesses use the intelligence they gather to :

    • Personalise website and app experiences
    • Adapt marketing campaigns
    • Improve conversion rates
    • Match stated preferences
    • Cater to observed behaviours
    • Customise recommendations based on purchase history
    • Create segmented email campaigns
    • Improve retargeting efforts
    • Develop more impactful content

    Measurement and optimisation

    Because first-party data is collected directly from customers or prospects, it’s far more relevant, reliable, and specific. Your analytics and campaign tracking will be more accurate. This gives you direct and actionable insights into your audience’s behaviour, empowering you to optimise your strategies and achieve better results.

    The same goes for your collection and activation efforts. An advanced web analytics platform like Matomo lets you identify key user behaviour and optimise your tracking. Heatmaps, marketing attribution tools, user behaviour analytics and custom reports allow you to segment audiences for better traction (and collect even more first-party data).

    Image showing the five steps to developing a first-party data strategy

    How to build a first-party data strategy

    There are five important and sequential steps to building a first-party data strategy. But this isn’t a one-time process. It must be revisited regularly as operating and regulatory environments change. There are five steps : 

    1. Audit existing data

    Chances are that customers already freely provide a lot of first-party data in the normal course of business. The first step is to locate this data, and the easiest way to do that is by mapping the customer journey. This identifies all the touchpoints where first-party data might be found.

    1. Define objectives

    Then, it’s time to step back and figure out the goals of the first-party data strategy. Consider what you’re trying to achieve. For example :

    • Reduce churn 
    • Expand an existing loyalty programme
    • Unload excess inventory
    • Improve customer experiences

    Whatever the objectives are, they should be clear and measurable.

    1. Implement tools and technology

    The first two steps point to data gaps. Now, the focus turns to ethical web analytics with a tool like Matomo. 

    To further comply with data privacy regulations, it may also be appropriate to implement a Consent Management Platform (CMP) to help manage preferences and consent choices.

    1. Build trust with transparency

    With the tools in place, it’s time to engage customers. To build trust, keep them informed about how their data is used and remind them of their right to withdraw their consent. 

    Transparency is crucial in such engagement, as outlined in the 7 GDPR principles.

    1. Continuously improve

    Rinse and repeat. The one constant in business and life is change. As things change, they expose weaknesses or flaws in the logic behind systems and processes. That’s why a first-party data strategy needs to be continually reviewed, updated, and revised. It must adapt to changing trends, markets, regulations, etc. 

    Tools that can help

    Looking back at the different types of data, it’s clear that some are harder and more bothersome to get than others. But capturing behaviours and interactions can be easy — especially if you use tools that follow data privacy rules.

    But here’s a tip. Google Analytics 4 isn’t compliant by default, especially not with Europe’s GDPR. It may also struggle to comply with some of the newer data privacy regulations planned by different US states and other countries.

    Matomo Analytics is compliant with the GDPR and many other data privacy regulations worldwide. Because it’s open source, it can be integrated with any consent manager.

    Get started today by trying Matomo for free for 21 days,
    no credit card required.