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• 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. 

• Revision 33402 : Amélioration du pipeline post édition

  29 novembre 2009, par kent1@… — Log

  Amélioration du pipeline post édition

• What Is Data Ethics & Why Is It Important in Business ?

  9 mai 2024, par Erin

  Data is powerful — every business on earth uses data. But some are leveraging it more than others.

  The problem ?

  Not all businesses are using data ethically.

  You need to collect, store, and analyse data to grow your business. But, if you aren’t careful, you could be crossing the line with your data usage into unethical territories.

  In a society where data is more valuable than ever, it’s crucial you perform ethical practices.

  In this article, we break down what data ethics is, why it’s important in business and how you can implement proper data ethics to ensure you stay compliant while growing your business.

  What is data ethics ?

  Data ethics are how a business collects, protects and uses data.

  It’s one field of ethics focused on organisations’ moral obligation to collect, track, analyse and interpret data correctly.

  

  Data ethics analyses multiple ways we use data :

  • Collecting data
  • Generating data
  • Tracking data
  • Analysing data
  • Interpreting data
  • Implementing activities based on data

  Data ethics is a field that asks, “Is this right or wrong ?”

  And it also asks, “Can we use data for good ?”

  If businesses use data unethically, they could get into serious hot water with their customers and even with the law.

  You need to use data to ensure you grow your business to the best of your ability. But, to maintain a clean slate in the eyes of your customers and authorities, you need to ensure you have strong data ethics.

  Why you need to follow data ethics principles

  In 2018, hackers broke into British Airways’ website by inserting harmful code, leading website visitors to a fraudulent site. 

  The result ? 

  British Airways customers gave their information to the hackers without realising it : credit cards, personal information, login information, addresses and more.

  While this was a malicious attack, the reality is that data is an integral part of everyday life. Businesses need to do everything they can to protect their customers’ data and use it ethically.

  Data ethics is crucial to understand as it sets the standard for what’s right and wrong for businesses. Without a clear grasp of data ethics, companies will willingly or neglectfully misuse data.

  With a firm foundation of data ethics, businesses worldwide can make a collective effort to function smoothly, protect their customers, and, of course, protect their own reputation. 

  3 benefits of leaning into data ethics

  We’re currently transitioning to a new world led by artificial intelligence.

  While AI presents endless opportunities for innovation in the business world, there are also countless risks at play, and it’s never been more important to develop trust with your customers and stakeholders.

  With an influx of data being created and tracked daily, you need to ensure your business is prioritising data ethics to ensure you maintain trust with your customers moving forward.

  

  Here are three benefits of data ethics that will help you develop trust, maintain a solid reputation and stay compliant to continue growing your business :

  1. Compliance with data privacy

  Privacy is everything. 

  In a world where our data is being collected nonstop, and we live more public lives than ever with social media, AI and an influx of recording and tracking in everyday life, you need to protect the privacy of your customers.

  One crucial way to protect that privacy is by complying with major data privacy regulations.

  Some of the most common regulations you need to remain compliant with include :

  • General Data Protection Regulation (GDPR)
  • California Consumer Privacy Act (CCPA)
  • Health Insurance Portability and Accountability Act (HIPAA)
  • General Personal Data Protection Law (LGPD)
  • Privacy and Electronic Communications (EC Directive) Regulations (PECR)

  While these regulations don’t directly address ethics, there’s a core overlap between privacy requirements like accountability, lawfulness and AI ethics.

  Matomo ensures you protect the privacy of your web and app users so you can track and improve your website performance with peace of mind.

  2. Maintain a good reputation

  While data ethics can help you maintain data privacy compliance, it can also help you maintain a good reputation online and offline.

  All it takes is one bad event like the British Airways breach for your company’s reputation to be ruined.

  If you want to keep a solid reputation and maintain trust with your stakeholders, customers and lawmakers, then you need to focus on developing strong data ethics.

  Businesses that invest time in establishing proper data ethics set the right foundation to protect their reputation, develop trust with stakeholders and create goodwill and loyalty.

  3. Increased trust means greater revenue

  What happens when you establish proper data ethics ?

  You’ll gain the trust of your customers, maintain a solid reputation and increase your brand image.

  Customers who trust you to protect their privacy and data want to keep doing business with you.

  So, what’s the end result for a business that values data ethics ?

  You’ll generate more revenue in the long run. Trust is one thing you should never put on the back burner if you have plans to keep growing your business. By leaning more into data ethics, you’ll be able to build that brand reputation that helps people feel comfortable buying your products and services on repeat.

  While spending time and money on data ethics may seem like an annoyance, the reality is that it’s a business investment that will pay dividends for years to come.

  5 core data ethics principles

  So, what exactly is involved in data ethics ?

  For most people, data ethics is a pretty broad and vague term. If you’re curious about the core pillars of data ethics, then keep reading.

  Here are five core data ethical principles you need to follow to ensure you’re protecting your customers’ data and maintaining trust :

  

  1. Data ownership

  The individual owns the data, not you. This is the first principle of data ethics. You don’t have control over someone else’s data. It’s theirs, and they have full ownership over it.

  Just as stealing a TV from an electronics store is a crime, stealing (or collecting) someone’s personal data without their consent is considered unlawful and unethical.

  Consent is the only way to ethically “own” someone’s data.

  How can you collect someone’s data ethically ?

  • Digital privacy policies
  • Signed, written agreements
  • Popups with checkboxes that allow you to track users’ behaviour

  Essentially, anytime you’re collecting data from your website or app users, you need to ensure you’re asking permission for that data.

  You should never assume a website visitor or customer is okay with you collecting your data automatically. Instead, ask permission to collect, track and use their data to avoid legal and ethical issues.

  2. Transparency

  The second core principle of data ethics within business is transparency. This means you need to be fully transparent on when, where and how you :

  • Collect data
  • Store data
  • Use data

  In other words, you need to allow your customers and website visitors to have a window inside your data activities.

  They need to be able to see exactly how you plan on using the data you’re collecting from them.

  For example, imagine you implemented a new initiative to personalise the website experience for each user based on individual behaviour. To do this, you’ll need to track cookies. In this case, you’d need to write up a new policy stating how this behavioural data is going to be collected, tracked and used.

  It’s within your website visitors’ rights to access this information so they can choose whether or not they want to accept or decline your website’s cookies.

  With any new data collection or tracking, you need to be 100% clear about how you’re going to use the data. You can’t be deceptive, misleading, or withholding any information on how you will use the data, as this is unethical and, in many cases, unlawful.

  3. Privacy

  Another important branch of ethics is privacy. The ethical implications of this should be obvious.

  When your users, visitors, or customers enter your sphere of influence and you begin collecting data on them, you are responsible for keeping that data private.

  When someone accepts the terms of your data usage, they’re not agreeing to have their data released to the public. They’re agreeing to let you leverage that data as their trusted business provider to better serve them. They expect you to maintain privacy.

  You can’t spread private information to third parties. You can’t blast this data to the public. 

  This is especially important if someone allows you to collect and use their personally identifiable information (PII), such as :

  • First and last name
  • Email address
  • Date of birth
  • Home address
  • Phone number

  To protect your audience’s data, you should only store it in a secure database. 

  

  For example, Matomo’s web analytics solution guarantees the privacy of both your users and analytics data.

  With Matomo, you have complete ownership of your data. Unlike other web analytics solutions that exploit your data for advertising purposes, Matomo users can use analytics with confidence, knowing that their data won’t be sold to advertisers.

  Learn more about data privacy with Matomo here.

  Try Matomo for Free

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  4. Intention

  When you collect and store data, you need to tell your users why you’re collecting their data. But there’s another principle of data ethics that goes beyond the reason you give your customers.

  Intention is the reason you give yourself for collecting and using the data.

  Before you start collecting and storing data, you should ask yourself the following :

  • Why you need it
  • What you’ll gain from it
  • What changes you’ll be able to make after you analyse the data

  If your intention is wrong in any way, it’s unethical to collect the data :

  • You’re collecting data to hurt others
  • You’re collecting data to profit from your users’ weaknesses
  • You’re collecting data for any other malicious reason

  When you collect data, you need to have the right intentions to maintain proper data ethics ; otherwise, you could harm your brand, break trust and ruin your reputation.

  5. Outcomes

  You may have the best intentions, but sometimes, there are negative outcomes from data use.

  For example, British Airways’ intention was not to allow hackers to gain access and harm their users. But the reality is that their customers’ data was stolen and used for malicious purposes. While this isn’t technically unlawful, the outcome of collecting data ended badly.

  To ensure proper data ethics, you must have good standing with your data. This means protecting your users at all costs, maintaining a good reputation and ensuring proper privacy measures are set up.

  How to implement data ethics as a business leader

  As a business leader, CTO or CEO, it’s your responsibility to implement data ethics within your organisation. Here are some tips to implement data ethics based on the size and stage of your organisation :

  Startups

  If you’re a startup, you need to be mindful of which technology and tools you use to collect, store and use data to help you grow your business.

  It can be a real challenge to juggle all the moving parts of a startup since things can change so quickly. However, it’s crucial to establish a leader and allow easy access to ethical analysis resources to maintain proper data ethics early on.

  Small and medium-sized businesses

  As you begin scaling, you’ll likely be using even more technology. With each new business technique you implement, there will be new ways you’ll be collecting user data. 

  One of the key processes involved in managing data as you grow is to hire engineers who build out different technologies. You must have protocols, best practices and management overseeing the new technologies being built to ensure proper data ethics.

  Global businesses

  Have you scaled internationally ?

  There will be even more rules, laws, regulations and organisations to answer to if you start managing data unethically.

  You should have established teams or departments to ensure you follow proper privacy and data protocols worldwide. When you have a large organisation, you have more money and vast amounts of data. This makes you a bigger target for leaks, ransomware and hackers.

  You should ensure you have cross-departmental groups working to establish ongoing protocols and training to keep your data management in good standing.

  Leverage data ethically with Matomo

  Data is powerful.

  It’s a crucial point of leverage that’s required to stay competitive.

  However, improper use and management of data can give you a bad reputation, break trust and even cause you legal trouble.

  That’s why you must maintain good data ethics within your organisation.

  One of the most important places to set up proper data ethics and privacy measures is with your website analytics.

  Matomo is the leading, privacy-friendly web analytics solution in the world. It automatically collects, stores, and tracks data across your website ethically.

  With over 1 million websites using Matomo, you get to take full control over your website performance with :

  • Accurate data (no data sampling)
  • Privacy-friendly and GDPR-compliant analytics
  • Open-source for transparency and to create a custom solution for you

  Try Matomo free for 21-days. No credit card required.

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