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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. 

• 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 data	Name, email address, phone number, etc.
  Behavioural data	Website activity, app usage, wishlist content, purchase history, etc.
  Transactional data	Orders, payments, subscription details, etc.
  Account data	Communication preferences, product interests, wish lists, etc.
  Demographic data	Age, gender, income level, education, etc.
  Geographic Data	Location-based information, such as zip codes or regional preferences.
  Psychographic Data	Interests, 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.

  

  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.

  

  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 activity	forms and surveys, behavioural tracking, cookies, tracking pixels and chatbots
  Mobile app interactions	in-app analytics, push notifications and in-app forms
  Email marketing	newsletter sign-ups, email engagement tracking, promotions, polls and surveys
  Events	registrations, post-event surveys and virtual event analytics
  Social media interaction	polls and surveys, direct messages and social media analytics
  Previous transactions	purchase 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 content	whitepapers, ebooks, podcasts, webinars and video downloads
  Interactive content	quizzes, assessments, calculators and free tools
  CRM platforms	customer profiles and sales data
  Consent management	privacy 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).

  

  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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  Try Matomo for free

• Organic Traffic : What It Is and How to Increase It

  19 septembre 2023, par Erin — Analytics Tips

  Organic traffic can be a website’s most valuable source of visitors. But it can also be the hardest form of traffic to acquire. While paid ads can generate traffic almost instantly, you need to invest time and energy into growing traffic from search engines.

  And it all starts with understanding exactly what organic traffic is. 

  If you want to understand what organic traffic is, how to measure it and how to generate more of it, then this article is for you.

  What is organic traffic ?

  Organic traffic is the visitors your website receives from the unpaid results on search engines like Google, Bing and DuckDuckGo. 

  The higher your website ranks in the search engine results pages and the more search terms your website ranks for, the more organic traffic your site will receive. 

  Organic traffic is highly valued by marketers, partly because it has a much higher clickthrough rate than PPC ads. Research shows the top organic result has a 39.8% CTR compared to just 2.1% for paid ads.

  

  So, while you can pay to appear at the top of search engines (using a platform like Google Ads, for instance), you probably won’t receive as much traffic as you would if you were to rank organically in the same search engine.

  What other types of traffic are there ? 

  Organic traffic isn’t the only type of traffic your website can get. You can also receive traffic from the following channels :

  Direct

  People familiar with your site may visit it directly, either by entering your URL into their browser or accessing it through a bookmarked link ; both scenarios are counted as direct traffic.

  Social

  Social traffic includes visits to your website from a social media platform. For example, if someone shares a link to your website on Facebook, any user who clicks on it will be counted as social traffic. 

  Websites

  Social media isn’t the only way for someone to share a link to your website. Any time a visitor finds your website by clicking on a link on another website, it will be counted as “websites”. This is also known as referral traffic on some analytics platforms. 

  Campaign

  Campaign traffic encompasses both paid and unpaid traffic sources. Paid sources include advertising on search engines and social media (also known as PPC or pay-per-click), as well as collaborations with influencers and sponsorships. Unpaid sources, such as your organisation’s email newsletters, cross-promotions with other businesses and other similar methods, are also part of this mix. 

  In simpler terms, it’s the traffic you deliberately direct to your site, and you utilise campaign tracking URLs to measure how these efforts impact your ROI.

  A word on multi-touch attribution

  If you are interested in learning more about types of traffic to track conversions, then it’s important to understand multi-touch attribution. The truth is most customers won’t just use a single traffic channel to find your website. In reality, the modern customer journey has multiple touchpoints, and customers may first find your site through an ad and then search for more about your brand on Google before going directly to your website. 

  

  You are at risk of under or overestimating the effectiveness of a marketing channel without using multi-touch attribution tracking. With this marketing analytics model, you can accurately weigh the impact of every channel and allocate budgets accordingly. 

  What are the benefits of organic traffic ?

  Getting more organic traffic is a common marketing goal for many companies. And it’s not surprising why. There’s a lot to love about organic traffic. 

  For starters, it’s arguably the most cost-effective traffic your site can receive. You will still need to pay to create and distribute organic content (whether it’s a blog post or product page). You don’t need to pay for it to show up in a search engine. You continue to get value from organic traffic long after you’ve created the page, too. A good piece of organic content can receive high volumes of monthly visitors for years. That’s a stark difference from paid ads, where traffic stops as soon as you turn off the ad. 

  It also puts your website in front of a massive audience, with Google alone processing over 3.5 billion searches every day. There’s a good chance that if your target audience is looking for a solution to their problems, they start with Google. 

  Organic traffic is fantastic at building brand awareness. Usually, users aren’t searching for a specific brand or company. They are searching for informational keywords (“how to brew the perfect cup of coffee”) or unbranded transactional keywords (“best home workout machine”). In both cases, customers can use search engines to become aware of your brand. 

  Finally, organic traffic brings in high-quality leads at every marketing funnel stage. Because users are searching for informational and transactional keywords, your site can receive visits from buyers at every stage of the marketing funnel, giving you multiple chances to convert them and helping to increase the number of touch points you have.

  How to check your website’s organic traffic

  You don’t need to complete complex calculations to determine your site’s organic traffic. A web analytics solution like Matomo will accurately measure your site’s organic traffic. 

  In Matomo, on the left-hand sidebar, you can access organic traffic data by clicking Acquisition and then selecting All Channels.

  

  You’ll find a detailed breakdown of all traffic sources, including organic traffic, within the specified timeframe. The report is set to the current day by default, but you can view organic traffic metrics over a day, week, month, year or a date range of your choice.

  If you want to take things further, you can get a detailed view of organic visitors by creating a custom report for “Visitors from Search Engines only.” By creating a custom report with the segment “Channel Type is search”, you’ll be able to combine other metrics like average actions per visit, bounce rate, goal conversions, etc., to create a comprehensive report on your organic traffic and the behavior of these visitors.

  Matomo also lets you integrate Google, Bing and Yahoo search consoles directly into your Matomo Analytics to monitor keyword performance.

  How to increase organic traffic

  Follow these six tips if you want to increase the web traffic you get organically from search engines. 

  Create more and better content

  Here’s the reality : Most websites don’t get much traffic from Google. Only 40% of sites rank on the first page, and just 23% sit in the top three results. 

  Let’s take quality first. The best content tends to rise to the top of search engines. That’s because it gets shared more, receives more backlinks and gets more user engagement. So, if you want to appear at the top of Google results, creating mediocre content probably won’t cut it. You need to go above and beyond what is already there. 

  But you can’t just create one fantastic piece of content and expect to receive thousands of visitors. You need multiple pages targeting as many search terms as possible. The more pages search engines index, the more opportunities you have to rank. Or, to put it another way, the more shots you take, the greater your chances of scoring. 

  Use keyword research tools

  While creating great content is essential, you want to ensure that content targets the right keywords. These keywords receive a suitable amount of traffic and are easy to rank for. 

  Keyword research tools like Ahrefs of Semrush are the easiest way to find high-traffic topics to write about. Specifically, you want to aim for long-tail keywords. These are search terms that contain three or more words. Think “Nike men’s basketball shoe” rather than “basketball shoe.”

  

  As you can see, long tail keywords have a lower monthly search volume (250 vs. 1,100 using the example above) than broad terms but are much easier to rank for (14 vs. 41 Keyword Difficulty).

  

  While the above tools can help you find new topics to write about, Matomo’s Search Engine Keywords Performance plugin can help highlight topics you have already covered that could be expanded.

  

  The plugin automatically connects to APIs from all significant search engines and imports all the keywords people search for when clicking on your websites into your Matomo report. 

  If you find a cluster of keywords on the same topic that generates a lot of visitors, it may be worth creating even more content on that topic. Similarly, if there’s a topic you think you have covered but isn’t generating much traffic, you can look at revising and refreshing your existing content to try to rank higher. 

  Build high-quality backlinks

  Backlinks are arguably the most important Google ranking factor and the primary way Google assesses the authoritativeness of your site and content. Backlinks strongly and positively correlate with traffic — at least according to 67.5% of respondents in a uSERP industry survey. 

  There are plenty of ways you can create high-quality backlinks that Google loves. Strategies include :

  • Creating and promoting the best content about a given topic
  • Guest posting on high-authority websites
  • Building relationships with other websites

  Ensure you avoid building low-quality spam links at all costs — such as private blog networks (PBNs), forum and comment spam links and directory links. These links won’t help your content to rank higher, and Google may even penalise your entire site if you build them. 

  Find and fix any technical Search Engine Optimisation (SEO) issues

  Search engines like Google need to be able to quickly and accurately crawl and index your website to rank your content. Unfortunately, many sites suffer from technical issues that impede search engine bots. 

  The good news is that certain tools make these issues easy to spot. Take the Matomo SEO Web Vitals feature, for instance. This lets you track a set of core web vital metrics, including :

  • Page Speed Score
  • First Contentful Paint (FCP)
  • Final Input Delay (FID)
  • Last Contentful Paint (LCP)
  • Cumulative Layout Shift (CLS)

  Take things even further by identifying major bugs and issues with your site. Crashes and other issues that impact user experience can also hurt your SEO and organic traffic efforts — so it’s best to eliminate them as soon as they occur. 

  

  Use Matomo’s Crash Analytics feature to get precise bug location information as well as the user’s interactions that triggered, the device they were using, etc. Scheduled reporting and alerts allow you to automate this task and instantly detect bugs as soon as they occur.

  Improve your on-page SEO

  As well as fixing technical issues, you should spend time optimising specific elements of your website to improve how it ranks in search engines. 

  There are several on-page elements you should optimise :

  • Image alt tags
  • URLs
  • Headings
  • Title tags
  • Internal links

  Your goal should be to include a target keyword in each element above. For example, your URL should be something like yoursite.com/keyword.

  It’s best to err on the side of caution here. Avoid adding too many keywords to each of these elements. This is called keyword stuffing, and Google may slap your site with a penalty. 

  Track your content’s performance

  One final way to increase organic traffic is to use an analytics platform to understand what content needs improving and which pages can be removed.

  

  Use an analytics platform like Matomo to see which pages generate the most organic traffic and which lag behind. This can help you prioritise your SEO efforts while highlighting pages that add no value. These pages can be completely revamped, redirected to another page or removed if appropriate. 

  Conclusion

  Organic traffic is arguably the most valuable traffic source your site can acquire. It is essential to monitor organic traffic levels and take steps to increase your organic traffic. 

  A good analytics platform can help you do both. Matomo’s powerful, open-source web analytics solution protects your data and your users’ privacy, while providing the SEO tools you need to send your organic traffic levels soaring. 

  Start a free 21-day trial now, no credit card required.