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• How to Conduct a Customer Journey Analysis (Step-by-Step)

  9 mai 2024, par Erin

  Your customers are everything.

  Treat them right, and you can generate recurring revenue for years. Treat them wrong ; you’ll be spinning your wheels and dealing with churn.

  How do you give your customers the best experience possible so they want to stick around ?

  Improve their customer experience.

  How ?

  By conducting a customer journey analysis.

  When you know how your customers experience your business, you can improve it to meet and exceed customer expectations.

  In this guide, we’ll break down how the customer journey works and give you a step-by-step guide to conduct a thorough customer journey analysis so you can grow your brand.

  What is a customer journey analysis ?

  Every customer you’ve ever served went on a journey to find you.

  From the moment they first heard of you, to the point that they became a customer. 

  Everything in between is the customer journey.

  A customer journey analysis is how you track and analyse how your customers use different channels to interact with your brand.

  

  Analysing your customer journey involves identifying the customer’s different touchpoints with your business so you can understand how it impacts their experience. 

  This means looking at every moment they interacted with your brand before, during and after a sale to help you gain actionable insights into their experience and improve it to reach your business objectives.

  Your customers go through specific customer touchpoints you can track. By analysing this customer journey from a bird’s eye view, you can get a clear picture of the entire customer experience.

  4 benefits of customer journey analysis

  Before we dive into the different steps involved in a customer journey analysis, let’s talk about why it’s vital to analyse the customer journey.

  By regularly analysing your customer journey, you’ll be able to improve the entire customer experience with practical insights, allowing you to :

  Understand your customers better

  What’s one key trait all successful businesses have ?

  They understand their customers.

  By analysing your customer journey regularly, you’ll gain new insights into their wants, needs, desires and behaviours, allowing you to serve them better. These insights will show you what led them to buy a product (or not).

  For example, through conducting a customer journey analysis, a company might find out that customers who come from LinkedIn are more likely to buy than those coming from Facebook.

  Find flaws in your customer journey

  Nobody wants to hear they have flaws. But the reality is your customer journey likely has a few flaws you could improve.

  By conducting customer journey analysis consistently, you’ll be able to pinpoint precisely where you’re losing prospects along the way. 

  For example, you may discover you’re losing customers through Facebook Ads. Or you may find your email strategy isn’t as good as it used to be.

  But it’s not just about the channel. It could be a transition between two channels. For example, you may have great engagement on Instagram but are not converting them into email subscribers. The issue may be that your transition between the two channels has a leak.

  Or you may find that prospects using certain devices (i.e., mobile, tablet, desktop) have lower conversions. This might be due to design and formatting issues across different devices.

  By looking closely at your customer journey and the different customer touchpoints, you’ll see issues preventing prospects from turning into leads or customers from returning to buy again as loyal customers.

  Gain insights into how you can improve your brand

  Your customer journey analysis won’t leave you with a list of problems. Instead, you’ll have a list of opportunities.

  Since you’ll be able to better understand your customers and where they’re falling off the sales funnel, you’ll have new insights into how you can improve the experience and grow your brand.

  For example, maybe you notice that your visitors are getting stuck at one stage of the customer journey and you’re trying to find out why.

  So, you leverage Matomo’s heatmaps, sessions recordings and scroll depth to find out more.

  In the case below, we can see that Matomo’s scroll map is showing that only 65% of the visitors are reaching the main call to action (to write a review). 

  

  To try to push for higher conversions and get more reviews, we could consider moving that button higher up on the page, ideally above the fold.

  Rather than guessing what’s preventing conversions, you can use user behaviour analytics to “step in our user’s shoes” so you can optimise faster and with confidence.

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  Grow your revenue

  By taking charge of your customer journey, you can implement different strategies that will help you increase your reach, gain more prospects, convert more prospects into customers and turn regulars into loyal customers.

  Using customer journey analysis will help you optimise those different touchpoints to maximise the ROI of your channels and get the most out of each marketing activity you implement.

  7 steps to conduct a customer journey analysis

  Now that you know the importance of conducting a customer journey analysis regularly, let’s dive into how to implement an analysis.

  Here are the seven steps you can take to analyse the customer journey to improve your customer experience :

  

  1. Map out your customer journey

  Your first step to conducting an effective customer journey analysis is to map your entire customer journey.

  Customer journey mapping means looking at several factors :

  • Buying process
  • Customer actions
  • Buying emotions
  • Buying pain points
  • Solutions

  Once you have an overview of your customer journey maps, you’ll gain insights into your customers, their interests and how they interact with your brand. 

  After this, it’s time to dive into the touchpoints.

  2. Identify all the customer touchpoints 

  To improve your customer journey, you need to know every touchpoint a customer can (and does) make with your brand.

  This means taking note of every single channel and medium they use to communicate with your brand :

  • Website
  • Social media
  • Search engines (SEO)
  • Email marketing
  • Paid advertising
  • And more

  Essentially, anywhere you communicate and interact with your customers is fair game to analyse.

  If you want to analyse your entire sales funnel, you can try Matomo, a privacy-friendly web analytics tool. 

  You should make sure to split up your touchpoints into different customer journey stages :

  • Awareness
  • Consideration
  • Conversion
  • Advocacy

  Then, it’s time to move on to how customers interact on these channels.

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  3. Measure how customers interact on each channel

  To understand the customer journey, you can’t just know where your customers interact with you. You end up learning how they’re interacting.

  This is only possible by measuring customer interactions.

  How ?

  By using a web analytics tool like Matomo.

  With Matomo, you can track every customer action on your website.

  This means anytime they :

  • Visit your website
  • View a web page
  • Click a link
  • Fill out a form
  • Purchase a product
  • View different media
  • And more

  You should analyse your engagement on your website, apps and other channels, like email and social media.

  4. Implement marketing attribution

  Now that you know where your customers are and how they interact, it’s time to analyse the effectiveness of each channel based on your conversion rates.

  Implementing marketing attribution (or multi-touch attribution) is a great way to do this.

  Attribution is how you determine which channels led to a conversion.

  While single-touch attribution models credit one channel for a conversion, marketing attribution gives credit to a few channels.

  For example, let’s say Bob is looking for a new bank. He sees an Instagram post and finds himself on HSBC’s website. After looking at a few web pages, he attends a webinar hosted by HSBC on financial planning and investment strategies. One week later, he gets an email from HSBC following up on the webinar. Then, he decides to sign up for HSBC’s online banking.

  Single touch attribution would attribute 100% of the conversion to email, which doesn’t show the whole picture. Marketing attribution would credit all channels : social media, website content, webinars and email.

  Matomo offers multiple attribution models. These models leverage different weighting factors, like time decay or linear, so that you can allocate credit to each touchpoint based on its impact.

  Matomo’s multi-touch attribution reports give you in-depth insights into how revenue is distributed across different channels. These detailed reports help you analyse each channel’s contribution to revenue generation so you can optimise the customer journey and improve business outcomes.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  5. Use a funnels report to find where visitors are leaving

  Once you set up your marketing attribution, it’s time to analyse where visitors are falling off.

  You can leverage Matomo funnels to find out the conversion rate at each step of the journey on your website. Funnel reports can help you see exactly where visitors are falling through the cracks so you can increase conversions.

  6. Analyse why visitors aren’t converting

  Once you can see where visitors are leaving, you can start to understand why.

  For example, let’s say you analyse your funnels report in Matomo and see your landing page is experiencing the highest level of drop-offs.

  

  You can also use form analytics to find out why users aren’t converting on your landing pages – a crucial part of the customer journey.

  7. A/B test to improve the customer journey

  The final step to improve your customer journey is to conduct A/B tests. These are tests where you test one version of a landing page to see which one converts better, drives more traffic, or generates more revenue.

  For example, you could create two versions of a header on your website and drive 50% of your traffic to each version. Then, once you’ve got your winner, you can keep that as your new landing page.

  

  Using the data from your A/B tests, you can optimise your customer journey to help convert more prospects into customers.

  Use Matomo to improve your customer journey analysis

  Now that you understand why it’s important to conduct customer journey analysis regularly and how it works, it’s time to put this into practice.

  To improve the customer journey, you need to understand what’s happening at each stage of your funnel. 

  Matomo gives you insights into your customer journey so you can improve website performance and convert more visitors into customers.

  Used by over 1 million websites, Matomo is the leading privacy-friendly web analytics solution in the world. 

  Matomo provides you with accurate, unsampled data so you understand exactly what’s going on with your website performance.

  The best part ?

  It’s easy to use and is compliant with the strictest privacy regulations.

  Try Matomo free for 21-days and start Improving your customer journey. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

  Start improving your websites now

  

• 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.

  21 day free trial. No credit card required.

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

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  I hereby accept the terms and conditions and the data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  

  » Start improving your websites now

  

• Lean Analytics in a Privacy-First Environment – Bootcamp with Timo Dechau

  29 novembre 2024, par Daniel Crough — Banking and Financial Services, GDPR, Marketing, Privacy, Videos, Featured Banking Content

  In a recent bootcamp, Timo Dechau walked attendees through his approach to data and measurement in privacy-focused analytics environments. He demonstrates how to shift from a chaotic, ‘track-it-all’ mentality to a focused method that prioritizes quality over quantity. This post will summarize some of his key privacy-first analytics ideas, but be sure to check out the on-demand video for more detail.

  Watch the bootcamp on demand

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  Unrestrained data collection leads to data bloat

  Marketing and the business world are experiencing a data problem. Analysts and business intelligence teams grapple with large amounts of data that aren’t always useful and are often incomplete. The idea that “more data is better” became a guiding principle in the early 2000s, encouraging companies to gather everything possible using all available data collection methods. This unrestrained pursuit often led to an unexpected problem : data bloat. Too much data, too little clarity. Digital marketers, analysts, and business leaders now try to navigate vast amounts of information that create more confusion than insight, especially when the data is incomplete due to privacy regulations.

  

  Cutting through the noise, focusing on what matters

  The “more data is better” mindset emerged when digital marketers were beginning to understand data’s potential. It seemed logical : more data should mean more opportunities to optimise, personalise, and drive results. But in practice, gathering every possible piece of data often leads to a cluttered, confusing pile of metrics that can mislead more than guide.

  This approach carries hidden costs. Excessive data collection burns resources, increases privacy concerns, and leaves teams unfocused. It’s easy to get lost trying to make sense of endless dashboards, metrics, and reports. More data doesn’t necessarily lead to better decisions ; it often just leads to more noise, hindering effective data management.

  Rethinking data management : From data overload to data mindfulness

  Data management has often prioritised comprehensive data gathering without considering the specific value of each data point. This approach has created more information, but not necessarily better insights.

  Data mindfulness is about taking a deliberate, focused approach to data collection and analysis. Instead of trying to collect everything, it emphasises gathering only what truly adds value. It’s about ensuring the data you collect serves a purpose and directly contributes to better insights and data-driven decision-making.

  Think of it like applying a “lean” methodology to data—trimming away the unnecessary and keeping only what is essential. Or consider embracing data minimalism to declutter your data warehouse, keeping only what truly sparks insight.

  

  Mindful data is ethical data

  Adopting a mindful approach to data can pay off in several ways :

  • Reduces overwhelm : When you reduce the clutter, you’re left with fewer, clearer metrics that lead to stronger decisions and actionable data insights.

  • Mitigates compliance risks : By collecting less, companies align better with privacy regulations and build trust with their customers. Privacy-first analytics and privacy-compliant analytics practices mean there’s no need for invasive tracking if it doesn’t add value—and customers will appreciate that.

  • Enhances data ethics : Focusing on the quality rather than the quantity of data collected ensures ethical data collection and management. Companies use data responsibly, respect user privacy, and minimise unnecessary data handling, strengthening customer relationships and brand integrity.

  • Improves data efficiency : Focused analytics means better use of resources. You’re spending less time managing meaningless metrics and more time working on meaningful insights. Many companies have found success by switching to a leaner, quality-first data approach, reporting sharper, more impactful results.

  Shifting towards simplicity and lean analytics

  If data mindfulness sounds appealing, here’s how you can get started :

  1. Ask the right questions. Before collecting any data, ask yourself : Why are we collecting this ? How will it drive value ? If you can’t answer these questions clearly, that data probably isn’t worth collecting. This is a key step in smart data management.

  2. Simplify metrics. Focus on the KPIs that truly matter for your business. Choose a handful of key metrics that reflect your goals rather than a sprawling list of nice-to-haves. Embracing data simplicity helps in targeting data collection effectively.

  3. Audit your current data. Review your existing data collection processes. Which metrics are you actively using to make decisions ? Eliminate any redundant or low-value metrics that create noise. Use ethical data management practices to ensure data efficiency and compliance. Understanding what is data management in this context is crucial.

  4. Implement lean analytics practices. Shift towards lean analytics by cutting down on unnecessary tracking. This can involve reducing reliance on multiple tracking scripts, simplifying your reporting, and setting up a streamlined dashboard focused on key outcomes. Embrace data reduction strategies to eliminate waste and boost effectiveness.

  Who should watch this bootcamp

  This bootcamp is perfect for data analysts, product managers, digital marketers and business leaders who are seeking a more streamlined approach to data measurement. If you’re interested in moving away from a chaotic “track-it-all” mentality and towards a focused, lean, and privacy-first analytics strategy, this workshop is for you.

  What you’ll discover

  • Practical steps : Learn actionable strategies to reduce data bloat and implement lean, privacy-first analytics in your organisation.

  • Real-life examples : Explore case studies of companies that have successfully adopted focused and privacy-first analytics.

  • Deep insights : Gain a deeper understanding of how to prioritise quality over quantity without sacrificing valuable insights.

  Watch the bootcamp on-demand

  For a comprehensive dive into these topics, watch the full workshop video or download the detailed transcript. Equip yourself with the knowledge and tools to transform your data management approach today.

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