Recherche avancée

Sur d’autres sites (3824)

• What is Multi-Touch Attribution ? (And How To Get Started)

  2 février 2023, par Erin — Analytics Tips

  Good marketing thrives on data. Or more precisely — its interpretation. Using modern analytics software, we can determine which marketing actions steer prospects towards the desired action (a conversion event). 

  An attribution model in marketing is a set of rules that determine how various marketing tactics and channels impact the visitor’s progress towards a conversion. 

  Yet, as customer journeys become more complicated and involve multiple “touches”, standard marketing reports no longer tell the full picture. 

  That’s when multi-touch attribution analysis comes to the fore. 

  What is Multi-Touch Attribution ?

  Multi-touch attribution (also known as multi-channel attribution or cross-channel attribution) measures the impact of all touchpoints on the consumer journey on conversion. 

  Unlike single-touch reporting, multi-touch attribution models give credit to each marketing element — a social media ad, an on-site banner, an email link click, etc. By seeing impacts from every touchpoint and channel, marketers can avoid false assumptions or subpar budget allocations.

  To better understand the concept, let’s interpret the same customer journey using a standard single-touch report vs a multi-touch attribution model. 

  Picture this : Jammie is shopping around for a privacy-centred web analytics solution. She saw a recommendation on Twitter and ended up on the Matomo website. After browsing a few product pages and checking comparisons with other web analytics tools, she signs up for a webinar. One week after attending, Jammie is convinced that Matomo is the right tool for her business and goes directly to the Matomo website a starts a free trial. 

  • A standard single-touch report would attribute 100% of the conversion to direct traffic, which doesn’t give an accurate view of the multiple touchpoints that led Jammie to start a free trial. 
  • A multi-channel attribution report would showcase all the channels involved in the free trial conversion — social media, website content, the webinar, and then the direct traffic source.

  In other words : Multi-touch attribution helps you understand how prospects move through the sales funnel and which elements tinder them towards the desired outcome. 

  Types of Attribution Models

  As marketers, we know that multiple factors play into a conversion — channel type, timing, user’s stage on the buyer journey and so on. Various attribution models exist to reflect this variability. 

  

  First Interaction attribution model (otherwise known as first touch) gives all credit for the conversion to the first channel (for example — a referral link) and doesn’t report on all the other interactions a user had with your company (e.g., clicked a newsletter link, engaged with a landing page, or browsed the blog campaign).

  First-touch helps optimise the top of your funnel and establish which channels bring the best leads. However, it doesn’t offer any insight into other factors that persuaded a user to convert. 

  Last Interaction attribution model (also known as last touch) allocates 100% credit to the last channel before conversion — be it direct traffic, paid ad, or an internal product page.

  The data is useful for optimising the bottom-of-the-funnel (BoFU) elements. But you have no visibility into assisted conversions — interactions a user had prior to conversion. 

  Last Non-Direct attribution model model excludes direct traffic and assigns 100% credit for a conversion to the last channel a user interacted with before converting. For instance, a social media post will receive 100% of credit if a shopper buys a product three days later. 

  This model is more telling about the other channels, involved in the sales process. Yet, you’re seeing only one step backwards, which may not be sufficient for companies with longer sales cycles.

  Linear attribution model distributes an equal credit for a conversion between all tracked touchpoints.

  For instance, with a four touchpoint conversion (e.g., an organic visit, then a direct visit, then a social visit, then a visit and conversion from an ad campaign) each touchpoint would receive 25% credit for that single conversion.

  This is the simplest multi-channel attribution modelling technique many tools support. The nuance is that linear models don’t reflect the true impact of various events. After all, a paid ad that introduced your brand to the shopper and a time-sensitive discount code at the checkout page probably did more than the blog content a shopper browsed in between. 

  Position Based attribution model allocates a 40% credit to the first and the last touchpoints and then spreads the remaining 20% across the touchpoints between the first and last. 

  This attribution model comes in handy for optimising conversions across the top and the bottom of the funnel. But it doesn’t provide much insight into the middle, which can skew your decision-making. For instance, you may overlook cases when a shopper landed via a social media post, then was re-engaged via email, and proceeded to checkout after an organic visit. Without email marketing, that sale may not have happened.

  Time decay attribution model adjusts the credit, based on the timing of the interactions. Touchpoints that preceded the conversion get the highest score, while the first ones get less weight (e.g., 5%-5%-10%-15%-25%-30%).

  This multi-channel attribution model works great for tracking the bottom of the funnel, but it underestimates the impact of brand awareness campaigns or assisted conversions at mid-stage. 

  Why Use Multi-Touch Attribution Modelling

  Multi-touch attribution provides you with the full picture of your funnel. With accurate data across all touchpoints, you can employ targeted conversion rate optimisation (CRO) strategies to maximise the impact of each campaign. 

  Most marketers and analysts prefer using multi-touch attribution modelling — and for some good reasons.

  Issues multi-touch attribution solves 

  • Funnel visibility. Understand which tactics play an important role at the top, middle and bottom of your funnel, instead of second-guessing what’s working or not. 
  • Budget allocations. Spend money on channels and tactics that bring a positive return on investment (ROI). 
  • Assisted conversions. Learn how different elements and touchpoints cumulatively contribute to the ultimate goal — a conversion event — to optimise accordingly. 
  • Channel segmentation. Determine which assets drive the most qualified and engaged leads to replicate them at scale.
  • Campaign benchmarking. Compare how different marketing activities from affiliate marketing to social media perform against the same metrics.

  How To Get Started With Multi-Touch Attribution 

  To make multi-touch attribution part of your analytics setup, follow the next steps :

  1. Define Your Marketing Objectives 

  Multi-touch attribution helps you better understand what led people to convert on your site. But to capture that, you need to first map the standard purchase journeys, which include a series of touchpoints — instances, when a prospect forms an opinion about your business.

  Touchpoints include :

  • On-site interactions (e.g., reading a blog post, browsing product pages, using an on-site calculator, etc.)
  • Off-site interactions (e.g., reading a review, clicking a social media link, interacting with an ad, etc.)

  Combined these interactions make up your sales funnel — a designated path you’ve set up to lead people toward the desired action (aka a conversion). 

  Depending on your business model, you can count any of the following as a conversion :

  • Purchase 
  • Account registration 
  • Free trial request 
  • Contact form submission 
  • Online reservation 
  • Demo call request 
  • Newsletter subscription

  So your first task is to create a set of conversion objectives for your business and add them as Goals or Conversions in your web analytics solution. Then brainstorm how various touchpoints contribute to these objectives. 

  Web analytics tools with multi-channel attribution, like Matomo, allow you to obtain an extra dimension of data on touchpoints via Tracked Events. Using Event Tracking, you can analyse how many people started doing a desired action (e.g., typing details into the form) but never completed the task. This way you can quickly identify “leaking” touchpoints in your funnel and fix them. 

  2. Select an Attribution Model 

  Multi-attribution models have inherent tradeoffs. Linear attribution model doesn’t always represent the role and importance of each channel. Position-based attribution model emphasises the role of the last and first channel while diminishing the importance of assisted conversions. Time-decay model, on the contrary, downplays the role awareness-related campaigns played.

  To select the right attribution model for your business consider your objectives. Is it more important for you to understand your best top of funnel channels to optimise customer acquisition costs (CAC) ? Or would you rather maximise your on-site conversion rates ? 

  Your industry and the average cycle length should also guide your choice. Position-based models can work best for eCommerce and SaaS businesses where both CAC and on-site conversion rates play an important role. Manufacturing companies or educational services providers, on the contrary, will benefit more from a time-decay model as it better represents the lengthy sales cycles. 

  3. Collect and Organise Data From All Touchpoints 

  Multi-touch attribution models are based on available funnel data. So to get started, you will need to determine which data sources you have and how to best leverage them for attribution modelling. 

  Types of data you should collect : 

  • General web analytics data : Insights on visitors’ on-site actions — visited pages, clicked links, form submissions and more.
  • Goals (Conversions) : Reports on successful conversions across different types of assets. 
  • Behavioural user data : Some tools also offer advanced features such as heatmaps, session recording and A/B tests. These too provide ample data into user behaviours, which you can use to map and optimise various touchpoints.

  You can also implement extra tracking, for instance for contact form submissions, live chat contacts or email marketing campaigns to identify repeat users in your system. Just remember to stay on the good side of data protection laws and respect your visitors’ privacy. 

  Separately, you can obtain top-of-the-funnel data by analysing referral traffic sources (channel, campaign type, used keyword, etc). A Tag Manager comes in handy as it allows you to zoom in on particular assets (e.g., a newsletter, an affiliate, a social campaign, etc). 

  Combined, these data points can be parsed by an app, supporting multi-touch attribution (or a custom algorithm) and reported back to you as specific findings. 

  Sounds easy, right ? Well, the devil is in the details. Getting ample, accurate data for multi-touch attribution modelling isn’t easy. 

  Marketing analytics has an accuracy problem, mainly for two reasons :

  • Cookie consent banner rejection 
  • Data sampling application

  Please note that we are not able to provide legal advice, so it’s important that you consult with your own DPO to ensure compliance with all relevant laws and regulations.

  If you’re collecting web analytics in the EU, you know that showing a cookie consent banner is a GDPR must-do. But many consumers don’t often rush to accept cookie consent banners. The average consent rate for cookies in 2021 stood at 54% in Italy, 45% in France, and 44% in Germany. The consent rates are likely lower in 2023, as Google was forced to roll out a “reject all” button for cookie tracking in Europe, while privacy organisations lodge complaints against individual businesses for deceptive banners. 

  For marketers, cookie rejection means substantial gaps in analytics data. The good news is that you can fill in those gaps by using a privacy-centred web analytics tool like Matomo. 

  Matomo takes extra safeguards to protect user privacy and supports fully cookieless tracking. Because of that, Matomo is legally exempt from tracking consent in France. Plus, you can configure to use our analytics tool without consent banners in other markets outside of Germany and the UK. This way you get to retain the data you need for audience modelling without breaching any privacy regulations. 

  Data sampling application partially stems from the above. When a web analytics or multi-channel attribution tool cannot secure first-hand data, the “guessing game” begins. Google Analytics, as well as other tools, often rely on synthetic AI-generated data to fill in the reporting gaps. Respectively, your multi-attribution model doesn’t depict the real state of affairs. Instead, it shows AI-produced guesstimates of what transpired whenever not enough real-world evidence is available.

  4. Evaluate and Select an Attribution Tool 

  Google Analytics (GA) offers several multi-touch attribution models for free (linear, time-decay and position-based). The disadvantage of GA multi-touch attribution is its lower accuracy due to cookie rejection and data sampling application.

  At the same time, you cannot create custom credit allocations for the proposed models, unless you have the paid version of GA, Google Analytics 360. This version of GA comes with a custom Attribution Modeling Tool (AMT). The price tag, however, starts at USD $50,000 per year. 

  Matomo Cloud offers multi-channel conversion attribution as a feature and it is available as a plug-in on the marketplace for Matomo On-Premise. We support linear, position-based, first-interaction, last-interaction, last non-direct and time-decay modelling, based fully on first-hand data. You also get more precise insights because cookie consent isn’t an issue with us. 

  Most multi-channel attribution tools, like Google Analytics and Matomo, provide out-of-the-box multi-touch attribution models. But other tools, like Matomo On-Premise, also provide full access to raw data so you can develop your own multi-touch attribution models and do custom attribution analysis. The ability to create custom attribution analysis is particularly beneficial for data analysts or organisations with complex and unique buyer journeys. 

  Conclusion

  Ultimately, multi-channel attribution gives marketers greater visibility into the customer journey. By analysing multiple touchpoints, you can establish how various marketing efforts contribute to conversions. Then use this information to inform your promotional strategy, budget allocations and CRO efforts. 

  The key to benefiting the most from multi-touch attribution is accurate data. If your analytics solution isn’t telling you the full story, your multi-touch model won’t either. 

  Collect accurate visitor data for multi-touch attribution modelling with Matomo. Start your free 21-day trial now. 

• avutil : remove deprecated FF_API_PALETTE_HAS_CHANGED

  19 février, par James Almer

  avutil : remove deprecated FF_API_PALETTE_HAS_CHANGED
  Deprecated since 2023-05-18.
  Signed-off-by : James Almer <jamrial@gmail.com>
  

  • [DH] libavcodec/8bps.c
  • [DH] libavcodec/ansi.c
  • [DH] libavcodec/bethsoftvideo.c
  • [DH] libavcodec/bfi.c
  • [DH] libavcodec/bintext.c
  • [DH] libavcodec/bmvvideo.c
  • [DH] libavcodec/brenderpix.c
  • [DH] libavcodec/c93.c
  • [DH] libavcodec/cdgraphics.c
  • [DH] libavcodec/cdtoons.c
  • [DH] libavcodec/cinepak.c
  • [DH] libavcodec/dds.c
  • [DH] libavcodec/dfa.c
  • [DH] libavcodec/dsicinvideo.c
  • [DH] libavcodec/dxa.c
  • [DH] libavcodec/flicvideo.c
  • [DH] libavcodec/gemdec.c
  • [DH] libavcodec/idcinvideo.c
  • [DH] libavcodec/imx.c
  • [DH] libavcodec/interplayvideo.c
  • [DH] libavcodec/jvdec.c
  • [DH] libavcodec/kmvc.c
  • [DH] libavcodec/mscc.c
  • [DH] libavcodec/msrle.c
  • [DH] libavcodec/mss1.c
  • [DH] libavcodec/msvideo1.c
  • [DH] libavcodec/pafvideo.c
  • [DH] libavcodec/pictordec.c
  • [DH] libavcodec/psd.c
  • [DH] libavcodec/qdrw.c
  • [DH] libavcodec/qpeg.c
  • [DH] libavcodec/qtrle.c
  • [DH] libavcodec/rawdec.c
  • [DH] libavcodec/rscc.c
  • [DH] libavcodec/sga.c
  • [DH] libavcodec/smacker.c
  • [DH] libavcodec/smc.c
  • [DH] libavcodec/targa.c
  • [DH] libavcodec/tiertexseqv.c
  • [DH] libavcodec/tmv.c
  • [DH] libavcodec/tscc.c
  • [DH] libavcodec/vb.c
  • [DH] libavcodec/vqavideo.c
  • [DH] libavcodec/yop.c
  • [DH] libavutil/frame.c
  • [DH] libavutil/frame.h
  • [DH] libavutil/version.h

• 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

  

  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.

  

  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.

  

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