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• Custom Segmentation Guide : How it Works & Segments to Test

  13 novembre 2023, par Erin — Analytics Tips, Uncategorized

  Struggling to get the insights you’re looking for with premade reports and audience segments in your analytics ?

  Custom segmentation can help you better understand your customers, app users or website visitors, but only if you know what you’re doing.

  You can derive false insights with the wrong segments, leading your marketing campaigns or product development in the wrong direction.

  In this article, we’ll break down what custom segmentation is, useful custom segments to consider, how new privacy laws affect segmentation options and how to create these segments in an analytics platform.

  What is custom segmentation ?

  Custom segmentation is when you divide your audience (customers, users, website visitors) into bespoke segments of your own design, not premade segments designed by the analytics or marketing platform provider.

  To do this, you single out “custom segment input” — data points you will use to pinpoint certain users. For example, it could be everyone who has visited a certain page on your site.

  

  Segmentation isn’t just useful for targeting marketing campaigns and also for analysing your customer data. Creating segments is a great way to dive deeper into your data beyond surface-level insights.

  You can explore how various factors impact engagement, conversion rates, and customer lifetime value. These insights can help guide your higher-level strategy, not just campaigns.

  How custom segments can help your business

  As the global business world clamours to become more “data-driven,” even smaller companies collect all sorts of data on visitors, users, and customers.

  However, inexperienced organisations often become “data hoarders” without meaningful insights. They have in-house servers full of data or gigabytes stored by Google Analytics and other third-party providers.

  

  One way to leverage this data is with standard customer segmentation models. This can help you get insights into your most valuable customer groups and other standard segments.

  Custom segments, in turn, can help you dive deeper. They help you unlock insights into the “why” of certain behaviours. They can help you segment customers and your audience to figure out :

  • Why and how someone became a loyal customer
  • How high-order-value customers interact with your site before purchases
  • Which behaviours indicate audience members are likely to convert
  • Which traffic sources drive the most valuable customers

  This specific insight’s power led Gartner to predict that 70% of companies will shift focus from “big data” to “small and wide” by 2025. The lateral detail is what helps inform your marketing strategy. 

  You don’t need the same volume of data if you’re analysing and segmenting it effectively.

  Custom segment inputs : 6 data points you can use to create valuable custom segments 

  To help you get started, here are six useful data points you can use as a basis to create segments — AKA customer segment inputs :

  

  Visits to certain pages

  A basic data point that’s great for custom segments is visits to certain pages. Create segments for popular middle-of-funnel pages and compare their engagement and conversion rates. 

  For example, if a user visits a case study page, you can compare their likelihood to convert vs. other visitors.

  This is a type of behavioural segmentation, but it is the easiest custom segment to set up in terms of analysis and marketing efforts.

  Visitors who perform certain actions

  The other important type of behavioural segment is visitors or users who take certain actions. Think of things like downloading a file, clicking a link, playing a video or scrolling a certain amount.

  For instance, you can create a segment of all visitors who have downloaded a white paper. This can help you explore, for example, what drives someone to download a white paper. You can look at the typical user journey and make it easier for them to access the white paper — especially if your sales reps indicate many inbound leads mention it as a key driver of their interest.

  User devices

  Device-based segmentation lets you compare engagement and conversion rates on mobile, desktop and tablets. You can also get insights into their usage patterns and potential issues with certain mobile elements.

  

  This is one aspect of technographic segmentation, where you segment based on users’ hardware or software. You can also create segments based on browser software or even specific versions.

  Loyal or high-value customers

  The best way to get more loyal or high-value customers is to explore their journey in more detail. These types of segments can help you better understand your ideal customers and how they act on your site.

  You can then use this insight to alter your campaigns or how you communicate with your target audience.

  For example, you might notice that high-value customers tend to come from a certain source. You can then focus your marketing efforts on this source to reach more of your ideal customers.

  Visitor or customer source

  You need to track the results if you’re investing in marketing (like an influencer campaign or a sponsored post) outside platforms with their own analytics.

  

  Before you can create a reliable segment, you need to make sure that you use campaign tracking parameters to reliably track the source. You can use our free campaign tracking URL builder for that.

  Demographic segments — location (country, state) and more

  Web analytics tools, such as Matomo, use visitors’ IP addresses to pinpoint their location more accurately by cross-referencing with a database of known and estimated IP locations. In addition, these tools can detect a visitor’s location through the language settings in their browser. 

  This can help create segments based on location or language. By exploring these trends, you can identify patterns in behaviour, tailor your content to specific audiences, and adapt your overall strategy to better meet the preferences and needs of your diverse visitor base.

  How new privacy laws affect segmentation options

  Over the past few years, new legislation regarding privacy and customer data has been passed globally. The most notable privacy laws are the GDPR in the EU, the CCPA in California and the VCDPA in Virginia.

  

  For most companies, it can save a lot of work and future headaches to choose a GDPR-compliant web analytics solution not only streamlines operations, saving considerable effort and preventing future headaches, but also ensures peace of mind by guaranteeing the collection of compliant and accurate data. This approach allows companies to maintain compliance with privacy regulations while remaining firmly committed to a data-driven strategy.

  Create your very own custom segments in Matomo (while ensuring compliance and data accuracy)

  Crafting precise marketing messages and optimising ROI is crucial, but it becomes challenging without the right tools, especially when it comes to maintaining accurate data.

  That’s where Matomo comes in. Our privacy-friendly web analytics platform is GDPR-compliant and ensures accurate data, empowering you to effortlessly create and analyse precise custom segments.

  If you want to improve your marketing campaigns while remaining GDPR-compliant, start your 21-day free trial of Matomo. No credit card required.

• CJEU rules US cloud servers don’t comply with GDPR and what this means for web analytics

  17 juillet 2020, par Jake Thornton
  Breaking news : On July 16, 2020, the Court of Justice of the European Union (CJEU) has ruled that any cloud services hosted in the US are incapable of complying with the GDPR and EU privacy laws.

  In August 2016, the EU-US Privacy Shield framework came into effect, which “protects the fundamental rights of anyone in the EU whose personal data is transferred to the United States for commercial purposes. It allows the free transfer of data to companies that are certified in the US under the Privacy Shield.” – European Commission website

  However after today’s CJEU ruling, this Privacy Shield framework became invalidated due to significant differences between EU and US privacy laws.

  European privacy law activist Max Schrems summarises with “The Court clarified for a second time now that there is a clash between EU privacy law and US surveillance law. As the EU will not change its fundamental rights to please the NSA, the only way to overcome this clash is for the US to introduce solid privacy rights for all people – including foreigners. Surveillance reform thereby becomes crucial for the business interests of Silicon Valley.” – noyb website

  Today’s ruling also continues to spark concern into the legitimacy of US privacy laws which doesn’t fully protect people’s personal data when hosted on cloud servers based in the US.

  

  How will this affect you ?

  For any business operating a website in the EU or if you have traffic coming to your website from EU visitors, you need to know what data you’re capturing and where this data is being stored.

  Here’s what Maja Smoltczyk (Berlin’s Commissioner for Data Protection and Freedom of Information) says :

  Controllers who transfer personal data to the USA, especially when using cloud-based services, are now required to switch immediately to service providers based in the European Union or a country that can
  ensure an adequate level of data protection. The CJEU has made it refreshingly clear that data exports are not just financial decisions, as people’s fundamental rights must also be considered as a matter of priority. This ruling will put
  an end to the transfer of personal data to the USA for the sake of convenience or to cut costs.

  The controller is you (not Google) and by transferring data to the US you are at risk of being fined up to €20 million or 4% of your annual worldwide turnover for not being GDPR compliant. 

  It’s you who has to take action, not Google or other US companies. The court’s decision has immediate effect. While we assume there will be a grace period, companies should act now as finding and implementing alternatives solution can take a while. 

  Can no data be exported outside the EU anymore ?

  Data can still be exported outside the EU if an adequate level of data protection is guaranteed. This is the case for some trading partners of the EU such as New Zealand, Japan, Switzerland, and Canada. They have been certified by the EU as having a comparable level of privacy protection and therefore demonstrate adequacy at a country level.

  Necessary data can still flow to countries like the US too. This is for example the case when someone books a hotel in the US or when sending an email to someone in the US. Backups for disaster recovery and most other reasons don’t qualify as necessary.

  In all other cases you can still send data to countries like the US if you get explicit and informed consent from a user. Meaning the user has been informed about all possible risks of sending the data to the US and who can access the data (for example the US government).

  How this affects Google Analytics and Google Tag Manager users

  If your website is using Google Analytics, the safest bet is to deactivate it immediately. Otherwise, you must ask for consent from everyone who visits your website and inform them that the data will be processed in the United States under less strict privacy laws and all associated risks. If you don’t, you could be liable to privacy law infringements and face being fined for not complying with the GDPR. This also applies to Google Tag Manager as it transfers the IP address to the US which is considered personal data under the GDPR.

  Consent needs to be :

  • Freely given (the user must have a choice to not give consent and be able to opt out at any time) 
  • Informed (you need to disclose who is processing the data, what data is processed, where the data will be stored and how to opt out) 
  • Specific (consent is only valid for the specific informed purpose) 
  • Unambiguous (for example pre-ticked boxes or similar aren’t allowed)

  

  If users don’t give you consent, you are not allowed to track them using Google Analytics or any other US based cloud solution.

  Update August 19, 2020

  A month after this ruling, over 100 complaints have been filed against websites for continuing to send data to the US via Google Analytics or Facebook, by the European privacy campaign group noyb. It’s clear Google and Facebook fall under US surveillance laws such as FISA 702 and the court clearly ruled these companies cannot rely on SCCs to transfer data to the US. Anyone still using Google Analytics is now at risk of facing fines and compensation damages. 

  How this affects Matomo users

  Our cloud servers are based in Germany.

  Matomo On-Premise users choose the location of their data themselves. If the servers are located in the EU nothing changes. If the servers are located outside the EU and the website targets EU users and tracks personal data, then you need to assess whether you are required to ask for tracking consent.

  If the data is stored inside the EU you can use Matomo without asking for any consent and you can continue tracking users even if they reject a consent screen which greatly increases the quality of your data.

  Want to avoid informing users about transferring their data to the US and all associated risks ?

  Try Matomo now for free ! No credit card required.

  Download Matomo

• Is Google Analytics Accurate ? 6 Important Caveats

  8 novembre 2022, par Erin

  It’s no secret that accurate website analytics is crucial for growing your online business — and Google Analytics is often the go-to source for insights. 

  But is Google Analytics data accurate ? Can you fully trust the provided numbers ? Here’s a detailed explainer.

  How Accurate is Google Analytics ? A Data-Backed Answer 

  When properly configured, Google Analytics (Universal Analytics and Google Analytics 4) is moderately accurate for global traffic collection. That said : Google Analytics doesn’t accurately report European traffic. 

  According to GDPR provisions, sites using GA products must display a cookie consent banner. This consent is required to collect third-party cookies — a tracking mechanism for identifying users across web properties.

  Google Analytics (GA) cannot process data about the user’s visit if they rejected cookies. In such cases, your analytics reports will be incomplete.

  Cookie rejection refers to visitors declining or blocking cookies from ever being collected by a specific website (or within their browser). It immediately affects the accuracy of all metrics in Google Analytics.

  Google Analytics is not accurate in locations where cookie consent to tracking is legally required. Most consumers don’t like disruptive cookie banners or harbour concerns about their privacy — and chose to reject tracking. 

  This leaves businesses with incomplete data, which, in turn, results in : 

  • Lower traffic counts as you’re not collecting 100% of the visitor data. 
  • Loss of website optimisation capabilities. You can’t make data-backed decisions due to inconsistent reporting

  For the above reasons, many companies now consider cookieless website tracking apps that don’t require consent screen displays. 

  Why is Google Analytics Not Accurate ? 6 Causes and Solutions 

  A high rejection rate of cookie banners is the main reason for inaccurate Google Analytics reporting. In addition, your account settings can also hinder Google Analytics’ accuracy.

  If your analytics data looks wonky, check for these six Google Analytics accuracy problems. 

  You Need to Secure Consent to Cookies Collection 

  To be GDPR-compliant, you must display a cookie consent screen to all European users. Likewise, other jurisdictions and industries require similar measures for user data collection. 

  This is a nuisance for many businesses since cookie rejection undermines their remarketing capabilities. Hence, some try to maximise cookie acceptance rates with dark patterns. For example : hide the option to decline tracking or make the texts too small. 

  

  Sadly, not everyone’s treating users with respect. A joint study by German and American researchers found that only 11% of US websites (from a sample of 5,000+) use GDPR-compliant cookie banners.

  As a result, many users aren’t aware of the background data collection to which they have (or have not) given consent. Another analysis of 200,000 cookies discovered that 70% of third-party marketing cookies transfer user data outside of the EU — a practice in breach of GDPR.

  Naturally, data regulators and activities are after this issue. In April 2022, Google was pressured to introduce a ‘reject all’ cookies button to all of its products (a €150 million compliance fine likely helped with that). Whereas, noyb has lodged over 220 complaints against individual websites with deceptive cookie consent banners.

  The takeaway ? Messing up with the cookie consent mechanism can get you in legal trouble. Don’t use sneaky banners as there are better ways to collect website traffic statistics. 

  Solution : Try Matomo GDPR-Friendly Analytics 

  Fill in the gaps in your traffic analytics with Matomo – a fully GDPR-compliant product that doesn’t rely on third-party cookies for tracking web visitors. Because of how it is designed, the French data protection authority (CNIL) confirmed that Matomo can be used to collect data without tracking consent.

  With Matomo, you can track website users without asking for cookie consent. And when you do, we supply you with a compact, compliant, non-disruptive cookie banner design. 

  Your Google Tag Isn’t Embedded Correctly 

  Google Tag (gtag.js) is a web tracking script that sends data to your Google Analytics, Google Ads and Google Marketing Platform.

  A corrupted gtag.js installation can create two accuracy issues : 

  • Duplicate page tracking 
  • Missing script installation 

  Is there a way to tell if you’re affected ?

  Yes. You may have duplicate scripts installed if you have a very low bounce rate on most website pages (below 15% – 20%). The above can happen if you’re using a WordPress GA plugin and additionally embed gtag.js straight in your website code. 

  A tell-tale sign of a missing script on some pages is low/no traffic stats. Google alerts you about this with a banner : 

  

  Solution : Use Available Troubleshooting Tools 

  Use Google Analytics Debugger extension to analyse pages with low bounce rates. Use the search bar to locate duplicate code-tracking elements. 

  Alternatively, you can use Google Tag Assistant for diagnosing snippet install and troubleshooting issues on individual pages. 

  If the above didn’t work, re-install your analytics script. 

  Machine Learning and Blended Data Are Applied

  Google Analytics 4 (GA4) relies a lot on machine learning and algorithmic predictions.

  By applying Google’s advanced machine learning models, the new Analytics can automatically alert you to significant trends in your data. [...] For example, it calculates churn probability so you can more efficiently invest in retaining customers.

  Vidhya Srinivasan, VP of Measurement, Analytics and Buying Platforms at Google

  On the surface, the above sounds exciting. In practice, Google’s application of predictive algorithms means you’re not seeing actual data. 

  To offer a variation of cookieless tracking, Google algorithms close the gaps in reporting by creating models (i.e., data-backed predictions) instead of reporting on actual user behaviours. Therefore, your GA4 numbers may not be accurate.

  For bigger web properties (think websites with 1+ million users), Google also relies on data sampling — a practice of extrapolating data analytics, based on a data subset, rather than the entire dataset. Once again, this can lead to inconsistencies in reporting with some numbers (e.g., average conversion rates) being inflated or downplayed. 

  Solution : Try an Alternative Website Analytics App 

  Unlike GA4, Matomo reports consist of 100% unsampled data. All the aggregated reporting you see is based on real user data (not guesstimation). 

  Moreover, you can migrate from Universal Analytics (UA) to Matomo without losing access to your historical records. GA4 doesn’t yet have any backward compatibility.

  Spam and Bot Traffic Isn’t Filtered Out 

  Surprise ! 42% of all Internet traffic is generated by bots, of which 27.7% are bad ones.

  Good bots (aka crawlers) do essential web “housekeeping” tasks like indexing web pages. Bad bots distribute malware, spam contact forms, hack user accounts and do other nasty stuff. 

  A lot of such spam bots are designed specifically for web analytics apps. The goal ? Flood your dashboard with bogus data in hopes of getting some return action from your side. 

  Types of Google Analytics Spam :

  • Referral spam. Spambots hijack the referrer, displayed in your GA referral traffic report to indicate a page visit from some random website (which didn’t actually occur). 
  • Event spam. Bots generate fake events with free language entries enticing you to visit their website. 
  • Ghost traffic spam. Malicious parties can also inject fake pageviews, containing URLs that they want you to click. 

  Obviously, such spammy entities distort the real website analytics numbers. 

  Solution : Set Up Bot/Spam Filters 

  Google Analytics 4 has automatic filtering of bot traffic enabled for all tracked Web and App properties. 

  But if you’re using Universal Analytics, you’ll have to manually configure spam filtering. First, create a new view and then set up a custom filter. Program it to exclude :

  • Filter Field : Request URI
  • Filter Pattern : Bot traffic URL

  Once you’ve configured everything, validate the results using Verify this filter feature. Then repeat the process for other fishy URLs, hostnames and IP addresses. 

  You Don’t Filter Internal Traffic 

  Your team(s) spend a lot of time on your website — and their sporadic behaviours can impair your traffic counts and other website metrics.

  To keep your data “employee-free”, exclude traffic from : 

  • Your corporate IPs addresses 
  • Known personal IPs of employees (for remote workers) 

  If you also have a separate stage version of your website, you should also filter out all traffic coming from it. Your developers, contractors and marketing people spend a lot of time fiddling with your website. This can cause a big discrepancy in average time on page and engagement rates. 

  Solution : Set Internal Traffic Filters 

  Google provides instructions for excluding internal traffic from your reports using IPv4/IPv6 address filters. 

  

  Session Timeouts After 30 Minutes 

  After 30 minutes of inactivity, Google Analytics tracking sessions start over. Inactivity means no recorded interaction hits during this time. 

  Session timeouts can be a problem for some websites as users often pin a tab to check it back later. Because of this, you can count the same user twice or more — and this leads to skewed reporting. 

  Solution : Programme Custom Timeout Sessions

  You can codify custom cookie timeout sessions with the following code snippets : 

  • _setSessionCookieTimeout. Set a custom new session cookie timeout in milliseconds.
  • _setVisitorCookieTimeout. Sets a custom Google Analytics visitor cookie expiration time frame in milliseconds.

  Final Thoughts 

  Thanks to its scale and longevity, Google Analytics has some strong sides, but its data accuracy isn’t 100% perfect.

  The inability to capture analytics data from users who don’t consent to cookie tracking and data sampling applied to bigger web properties may be a deal-breaker for your business. 

  If that’s the case, try Matomo — a GDPR-compliant, accurate web analytics solution. Start your 21-day free trial now. No credit card required.

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