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• 10 Key Google Analytics Limitations You Should Be Aware Of

  9 mai 2022, par Erin

  Google Analytics (GA) is the biggest player in the web analytics space. But is it as “universal” as its brand name suggests ?
  

  Over the years users have pointed out a number of major Google Analytics limitations. Many of these are even more visible in Google Analytics 4. 

  Introduced in 2020, Google Analytics 4 (GA4) has been sceptically received. As the sunset date of 1st, July 2023 for the current version, Google Universal Analytics (UA), approaches, the dismay grows stronger.

  To the point where people are pleading with others to intervene : 

  

  Main limitations of Google Analytics

  Google Analytics 4 is advertised as a more privacy-centred, comprehensive and “intelligent” web analytics platform. 

  According to Google, the newest version touts : 

  • Machine learning at its core provides better segmentation and fast-track access to granular insights 
  • Privacy-by-design controls, addressing restrictions on cookies and new regulatory demands 
  • More complete understanding of customer journeys across channels and devices 

  Some of these claims hold true. Others crumble upon a deeper investigation. Newly advertised Google Analytics capabilities such as ‘custom events’, ‘predictive insights’ and ‘privacy consent mode’ only have marginal improvements. 

  Complex setup, poor UI and lack of support with migration also leave many other users frustrated with GA4. 

  

  Let’s unpack all the current (and legacy) limitations of Google Analytics you should account for. 

  1. No Historical Data Imports 

  Google rushed users to migrate from Universal Analytics to Google Analytics 4. But they overlooked one important precondition — backwards compatibility. 

  You have no way to import data from Google Universal Analytics to Google Analytics 4. 

  Historical records are essential for analysing growth trends and creating benchmarks for new marketing campaigns. Effectively, you are cut short from past insights — and forced to start strategising from scratch. 

  At present, Google offers two feeble solutions : 

  • Run data collection in parallel and have separate reporting for GA4 and UA until the latter is shut down. Then your UA records are gone. 
  • For Ecommerce data, manually duplicate events from UA at a new GA4 property while trying to figure out the new event names and parameters. 

  Google’s new data collection model is the reason for migration difficulties. 

  In Google Analytics 4, all analytics hits types — page hits, social hits, app/screen view, etc. — are recorded as events. Respectively, the “‘event’ parameter in GA4 is different from one in Google Universal Analytics as the company explains : 

  

  This change makes migration tedious — and Google offers little assistance with proper events and custom dimensions set up. 

  2. Data Collection Limits 

  If you’ve wrapped your head around new GA4 events, congrats ! You did a great job, but the hassle isn’t over. 

  You still need to pay attention to new Google Analytics limits on data collection for event parameters and user properties. 

  

  These apply to :

  • Automatically collected events
  • Enhanced measurement events
  • Recommended events 
  • Custom events 

  When it comes to custom events, GA4 also has a limit of 25 custom parameters per event. Even though it seems a lot, it may not be enough for bigger websites. 

  You can get higher limits by upgrading to Google Analytics 360, but the costs are steep. 

  3. Limited GDPR Compliance 

  Google Analytics has a complex history with European GDPR compliance. 

  A 2020 ruling by the Court of Justice of the European Union (CJEU) invalidated the Privacy Shield framework Google leaned upon. This framework allowed the company to regulate EU-US data transfers of sensitive user data. 

  But after this loophole was closed, Google faced a heavy series of privacy-related fines :

  • French data protection authority, CNIL, ruled that  “the transfers to the US of personal data collected through Google Analytics are illegal” — and proceeded to fine Google for a record-setting €150 million at the beginning of 2022. 
  • Austrian regulators also deemed Google in breach of GDPR requirements and also branded the analytics as illegal. 

  Other EU-member states might soon proceed with similar rulings. These, in turn, can directly affect Google Analytics users, whose businesses could face brand damage and regulatory fines for non-compliance. In fact, companies cannot select where the collected analytics data will be stored — on European servers or abroad — nor can they obtain this information from Google.

  Getting a web analytics platform that allows you to keep data on your own servers or select specific Cloud locations is a great alternative. 

  Google also has been lax with its cookie consent policy and doesn’t properly inform consumers about data collection, storage or subsequent usage. Google Analytics 4 addresses this issue to an extent. 

  By default, GA4 relies on first-party cookies, instead of third-party ones — which is a step forward. But the user privacy controls are hard to configure without losing most of the GA4 functionality. Implementing user consent mode to different types of data collection also requires a heavy setup. 

  4. Strong Reliance on Sampled Data 

  To compensate for ditching third-party cookies, GA4 more heavily leans on sampled data and machine learning to fill the gaps in reporting. 

  In GA4 sampling automatically applies when you :

  • Perform advanced analysis such as cohort analysis, exploration, segment overlap or funnel analysis with not enough data 
  • Have over 10,000,000 data rows and generate any type of non-default report 

  Google also notes that data sampling can occur at lower thresholds when you are trying to get granular insights. If there’s not enough data or because Google thinks it’s too complex to retrieve. 

  In their words :

  

  Data sampling adds “guesswork” to your reports, meaning you can’t be 100% sure of data accuracy. The divergence from actual data depends on the size and quality of sampled data. Again, this isn’t something you can control. 

  Unlike Google Analytics 4, Matomo applies no data sampling. Your reports are always accurate and fully representative of actual user behaviours. 

  5. No Proper Data Anonymization 

  Data anonymization allows you to collect basic analytics about users — visits, clicks, page views — but without personally identifiable information (or PII) such as geo-location, assigns tracking ID or other cookie-based data. 

  This reduced your ability to :

  • Remarket 
  • Identify repeating visitors
  • Do advanced conversion attribution 

  But you still get basic data from users who ignored or declined consent to data collection. 

  By default, Google Analytics 4 anonymizes all user IP addresses — an upgrade from UA. However, it still assigned a unique user ID to each user. These count as personal data under GDPR. 

  For comparison, Matomo provides more advanced privacy controls. You can anonymize :

  • Previously tracked raw data 
  • Visitor IP addresses
  • Geo-location information
  • User IDs 

  This can ensure compliance, especially if you operate in a sensitive industry — and delight privacy-mindful users ! 

  6. No Roll-Up Reporting

  Getting a bird’s-eye view of all your data is helpful when you need hotkey access to main sites — global traffic volume, user count or percentage of returning visitors.

  With Roll-Up Reporting, you can see global-performance metrics for multiple localised properties (.co.nz, .co.uk, .com, etc,) in one screen. Then zoom in on specific localised sites when you need to. 

  

  7. Report Processing Latency 

  The average data processing latency is 24-48 hours with Google Analytics. 

  Accounts with over 200,000 daily sessions get data refreshes only once a day. So you won’t be seeing the latest data on core metrics. This can be a bummer during one-day promo events like Black Friday or Cyber Monday when real-time information can prove to be game-changing ! 

  Matomo processes data with lower latency even for high-traffic websites. Currently, we have 6-24 hour latency for cloud deployments. On-premises web analytics can be refreshed even faster — within an hour or instantly, depending on the traffic volumes. 

  8. No Native Conversion Optimisation Features

  Google Analytics users have to use third-party tools to get deeper insights like how people are interacting with your webpage or call-to-action.

  You can use the free Google Optimize tool, but it comes with limits : 

  • No segmentation is available 
  • Only 10 simultaneous running experiments allowed 

  There isn’t a native integration between Google Optimize and Google Analytics 4. Instead, you have to manually link an Optimize Container to an analytics account. Also, you can’t select experiment dimensions in Google Analytics reports.

  What’s more, Google Optimize is a basic CRO tool, best suited for split testing (A/B testing) of copy, visuals, URLs and page layouts. If you want to get more advanced data, you need to pay for extra tools. 

  Matomo comes with a native set of built-in conversion optimization features : 

  • Heatmaps 
  • User session recording 
  • Sales funnel analysis 
  • A/B testing 
  • Form submission analytics 

  

  9. Deprecated Annotations

  Annotations come in handy when you need to provide extra context to other team members. For example, point out unusual traffic spikes or highlight a leak in the sales funnel. 

  This feature was available in Universal Analytics but is now gone in Google Analytics 4. But you can still quickly capture, comment and share knowledge with your team in Matomo. 

  You can add annotations to any graph that shows statistics over time including visitor reports, funnel analysis charts or running A/B tests. 

  10. No White Label Option 

  This might be a minor limitation of Google Analytics, but a tangible one for agency owners. 

  Offering an on-brand, embedded web analytics platform can elevate your customer experience. But white label analytics were never a thing with Google Analytics, unlike Matomo. 

  Wrap Up 

  Google set a high bar for web analytics. But Google Analytics inherent limitations around privacy, reporting and deployment options prompt more users to consider Google Analytics alternatives, like Matomo. 

  With Matomo, you can easily migrate your historical data records and store customer data locally or in a designated cloud location. We operate by a 100% unsampled data principle and provide an array of privacy controls for advanced compliance. 

  Start your 21-day free trial (no credit card required) to see how Matomo compares to Google Analytics ! 

  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 hereby accept the terms and conditions and the data processing agreeement (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

  

• Google Analytics Privacy Issues : Is It Really That Bad ?

  2 juin 2022, par Erin

  If you find yourself asking : “What’s the deal with Google Analytics privacy ?”, you probably have some second thoughts. 

  Your hunch is right. Google Analytics (GA) is a popular web analytics tool, but it’s far from being perfect when it comes to respecting users’ privacy. 

  This post helps you understand tremendous Google Analytics privacy concerns users, consumers and regulators expressed over the years.

  In this blog, we’ll cover :

  What Does Google Analytics Collect About Users ? 

  To understand Google Analytics privacy issues, you need to know how Google treats web users’ data. 

  By default, Google Analytics collects the following information : 

  • Session statistics — duration, page(s) viewed, etc. 
  • Referring website details — a link you came through or keyword used. 
  • Approximate geolocation — country, city. 
  • Browser and device information — mobile vs desktop, OS usage, etc. 

  Google obtains web analytics data about users via two means : an on-site Google Analytics tracking code and cookies.

  A cookie is a unique identifier (ID) assigned to each user visiting a web property. Each cookie stores two data items : unique user ID and website name. 

  With the help of cookies, web analytics solutions can recognise returning visitors and track their actions across the website(s).

  

  • First party cookies are generated by one website and collect user behaviour data from said website only. 
  • Third-party cookies are generated by a third-party website object (for example, an ad) and can track user behaviour data across multiple websites. 

  As it’s easy to imagine, third-party cookies are a goldmine for companies selling online ads. Essentially, they allow ad platforms to continue watching how the user navigates the web after clicking a certain link. 

  Yet, people have little clue as to which data they are sharing and how it is being used. Also, user consent to tracking across websites is only marginally guaranteed by existing Google Analytics controls. 

  Why Third-Party Cookie Data Collection By GA Is Problematic 

  Cookies can transmit personally identifiable information (PII) such as name, log in details, IP address, saved payment method and so on. Some of these details can end up with advertisers without consumers’ direct knowledge or consent.

  Regulatory frameworks such as General Data Protection Regulation (GDPR) in Europe and California Consumer Privacy Act (CCPA) emerged as a response to uncontrolled user behaviour tracking.

  Under regulatory pressure, Big Tech companies had to adapt their data collection process.

  Apple was the first to implement by-default third-party blocking in the Safari browser. Then added a tracking consent mechanism for iPhone users starting from iOS 15.2 and later. 

  Google, too, said it would drop third-party cookie usage after The European Commission and UK’s Competition and Markets Authority (CMA) launched antitrust investigations into its activity. 

  To shake off the data watchdogs, Google released a Privacy Sandbox — a set of progressive tech, operational and compliance changes for ensuring greater consumer privacy. 

  Google’s biggest promise : deprecate third-party cookies usage for all web and mobile products. 

  Originally, Google promised to drop third-party cookies by 2022, but that didn’t happen. Instead, Google delayed cookie tracking depreciation for Chrome until the second half of 2023. 

  Why did they push back on this despite hefty fines from regulators ?

  Because online ads make Google a lot of money.

  In 2021, Alphabet Inc (parent company of Google), made $256.7 billion in revenue, of which $209.49 billion came from selling advertising. 

  Lax Google Analytics privacy enforcement — and its wide usage by website owners — help Google make those billions from collecting and selling user data. 

  How Google Uses Collected Google Analytics Data for Advertising 

  Over 28 million websites (or roughly 85% of the Internet) have Google Analytics tracking codes installed. 

  Even if one day we get a Google Analytics version without cookies, it still won’t address all the privacy concerns regulators and consumers have. 

  Over the years, Google has accumulated an extensive collection of user data. The company’s engineers used it to build state-of-the-art deep learning models, now employed to build advanced user profiles. 

  Deep learning is the process of training a machine to recognise data patterns. Then this “knowledge” is used to produce highly-accurate predictive insights. The more data you have for model training — the better its future accuracy will be. 

  Google has amassed huge deposits of data from its collection of products — GA, YouTube, Gmail, Google Docs and Google Maps among others. Now they are using this data to build a third-party cookies-less alternative mechanism for modelling people’s preferences, habits, lifestyles, etc. 

  Their latest model is called Google Topics. 

  This comes only after Google’s failed attempt to replace cookie-based training with Federated Learning of Cohorts (FLoC) model. But the solution wasn’t offering enough user transparency and user controls among other issues.

  

  Google Topics promises to limit the granularity of data advertisers get about users. 

  But it’s still a web user surveillance method. With Google Topics, the company will continue collecting user data via Chrome (and likely other Google products) — and share it with advertisers. 

  Because as we said before : Google is in the business of profiting off consumers’ data. 

  Two Major Ways Google Takes Advantage of Customer Data

  Every bit of data Google collects across its ecosystem of products can be used in two ways :

  • For ad targeting and personalisation 
  • To improve Google’s products 

  The latter also helps the former. 

  Advanced Ad Personalisation and Targeting

  GA provides the company with ample data on users’ 

  • Recent and frequent searches 
  • Location history
  • Visited websites
  • Used apps 
  • Videos and ads viewed 
  • Personal data like age or gender 

  The company’s privacy policy explicitly states that :
  

  

  Google also admits to using collected data to “measure the effectiveness of advertising” and “personalise content and ads you see on Google.” 

  But there are no further elaborations on how exactly customers’ data is used — and what you can do to prevent it from being shared with third parties. 

  In some cases, Google also “forgets” to inform users about its in-product tracking.

  Journalists from CNBC and The New York Times independently concluded that Google monitors users’ Gmail activity. In particular, the company scans your inbox for recent purchases, trips, flights and bills notifications. 

  While Google says that this information isn’t sold to advertisers (directly), they still may use the “saved information about your orders in other Google services”. 

  Once again, this means you have little control or knowledge of subsequent data usage. 

  Improving Product Usability 

  Google has many “arms” to collect different data points — from user’s search history to frequently-travelled physical routes. 

  They also reserve the right to use these insights for improving existing products. 

  Here’s what it means : by combining different types of data points obtained from various products, Google can pierce a detailed picture of a person’s life. Even if such user profile data is anonymised, it is still alarmingly accurate. 

  Douglas Schmidt, a computer science researcher at Vanderbilt University, well summarised the matter : 

  “[Google’s] business model is to collect as much data about you as possible and cross-correlate it so they can try to link your online persona with your offline persona. This tracking is just absolutely essential to their business. ‘Surveillance capitalism’ is a perfect phrase for it.”

  Google Data Collection Obsession Is Backed Into Its Business Model 

  OK, but Google offers some privacy controls to users ? Yes. Google only sees and uses the information you voluntarily enter or permit them to access. 

  But as the Washington Post correspondent points out :

  “[Big Tech] companies get to set all the rules, as long as they run those rules by consumers in convoluted terms of service that even those capable of decoding the legalistic language rarely bother to read. Other mechanisms for notice and consent, such as opt-outs and opt-ins, create similar problems. Control for the consumer is mostly an illusion.”

  Google openly claims to be “one of many ad networks that personalise ads based on your activity online”. 

  The wrinkle is that they have more data than all other advertising networks (arguably combined). This helps Google sell high-precision targeting and contextually personalised ads for billions of dollars annually.

  Given that Google has stakes in so many products — it’s really hard to de-Google your business and minimise tracking and data collection from the company.
  

  They are also creating a monopoly on data collection and ownership. This fact makes regulators concerned. The 2021 antitrust lawsuit from the European Commission says : 

  “The formal investigation will notably examine whether Google is distorting competition by restricting access by third parties to user data for advertising purposes on websites and apps while reserving such data for its own use.”

  In other words : By using consumer data to its unfair advantage, Google allegedly shuts off competition.

  But that’s not the only matter worrying regulators and consumers alike. Over the years, Google also received numerous other lawsuits for breaching people’s privacy, over and over again. 

  Here’s a timeline : 

  • 2019 : UK citizens issued a class action suit against Google for imposing cookies to override users’ privacy settings in the Safari browser. 
  • 2020 : US citizens pushed for a $5 billion class-action suit for tracking their activity through browsers set in “private” mode.
  • 2022 : Another class-action lawsuit in the US for deceptive privacy controls and unconsented location data tracking by Google mobile apps. 
  • 2022 : Google reached a $100 million class-action settlement for breaching Illinois biometrics privacy laws in Google Photos. 

  Separately, Google has a very complex history with GDPR compliance. 

  How Google Analytics Contributes to the Web Privacy Problem 

  Google Analytics is the key puzzle piece that supports Google’s data-driven business model. 

  If Google was to release a privacy-focused Google Analytics alternative, it’d lose access to valuable web users’ data and a big portion of digital ad revenues. 

  Remember : Google collects more data than it shares with web analytics users and advertisers. But they keep a lot of it for personal usage — and keep looking for ways to share this intel with advertisers (in a way that keeps regulators off their tail).

  For Google Analytics to become truly ethical and privacy-focused, Google would need to change their entire revenue model — which is something they are unlikely to do.

  Where does this leave Google Analytics users ? 

  In a slippery territory. By proxy, companies using GA are complicit with Google’s shady data collection and usage practice. They become part of the problem.

  In fact, Google Analytics usage opens a business to two types of risks : 

  • Reputational. 77% of global consumers say that transparency around how data is collected and used is important to them when interacting with different brands. That’s why data breaches and data misuse by brands lead to major public outrages on social media and boycotts in some cases. 
  • Legal. EU regulators are on a continuous crusade against Google Analytics 4 (GA4) as it is in breach of GDPR. French and Austrian watchdogs ruled the “service” illegal. Since Google Analytics is not GDPR compliant, it opens any business using it to lawsuits (which is already happening).

  But there’s a way out.

  Choose a Privacy-Friendly Google Analytics Alternative 

  Google Analytics is a popular web analytics service, but not the only one available. You have alternatives such as Matomo. 

  Our guiding principle is : respecting privacy.

  Unlike Google Analytics, we leave data ownership 100% in users’ hands. Matomo lets you implement privacy-centred controls for user data collection.

  Plus, you can self-host Matomo On-Premise or choose Matomo Cloud with data securely stored in the EU and in compliance with GDPR.

  The best part ? You can try our ethical alternative to Google Analytics for free. No credit card required ! Start your free 21-day trial now. 

  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 hereby accept the terms and conditions and the data processing agreeement (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

  

• B2B Customer Journey Map : A Quickfire Guide for Growth

  20 mai 2024, par Erin

  What is a company’s biggest asset ?

  Its product ? Its employees ? Its unique selling proposition ?

  More and more people are recognising it’s something else entirely : your customers.

  Without your customers, your business can’t exist.

  Nearly 77% of B2B buyers found the buying process too complicated.

  With more competition than ever, it’s crucial you provide the best possible experience for them.

  That’s where your customer journey comes in.

  If you’re in the B2B space, you need to know how to map out the journey.

  By building a B2B customer journey map, you’ll be able to analyse the weak spots in the customer journey so you can improve the experience (and generate more revenue).

  In this article, we break down the B2B customer journey stages, how to build a customer journey map and how Matomo can help you track your customer journey automatically.

  What is a B2B customer journey ?

  Every customer goes through a specific path within your business.

  At some point in time, they found out about you and eventually bought your products.

  

  A B2B customer journey is the collection of touchpoints your customer has with your business from start to finish.

  From discovery to purchase (and more), your customers go through a specific set of touches you can track. By analysing this journey, you can get a snapshot of your user experience.

  One way to track the customer journey is with a B2B customer journey map.

  It helps you to quickly see the different steps your customers take in their path with your business.

  With it, you can quickly identify weak spots and successes to improve the customer journey.

  5 stages of the B2B customer journey

  Every one of your customers is unique. Their specific needs and their journey.

  It’s all different.

  But, there are crucial steps they take through their journey as your customer.

  It’s the same path your entire customer base takes.

  Here are the five stages of the B2B customer journey (and why you should track them) :

  

  1. Awareness

  Awareness is the first stage that every B2B buyer goes through when they start their journey in B2B companies as a customer.

  At this stage, your target buyer understands they have a problem they need solving. They’re out, actively trying to solve this problem. 

  This is where you can stand out from the competition and give them a good first impression.

  Some helpful content you could create to do this is :

  • Blog posts
  • Social media posts
  • Ebooks
  • Whitepapers

  2. Consideration

  Next up, your buyer persona has an awareness of your company. But, now they’ve started narrowing down their options for potential businesses they’re interested in.

  They’ve selected yours as a potential business to hand their hard-earned cash over to, but they’re still making up their mind.

  At this point, you need to do what you can to clear up any objections and doubts in their mind and make them trust you.

  Some helpful content you could create here include :

  • Product demos by your sales team
  • Webinars
  • Case studies

  3. Conversion

  Next up, your target buyer has compared all their options and decided on you as the chosen product/company.

  This is where the purchase decision is made — when the B2B buyer actually signs or clicks “buy.”

  Here, you’ll want to provide more :

  • Case studies
  • Live demos
  • Customer service
  • Customer reviews/testimonials

  4. Loyalty

  Your B2B buyer is now a customer. But, not all customers return. The majority will slip away after the first purchase. If you want them to return, you need to fuel the relationship and nurture them even more.

  You’ll want to shift your efforts to nurturing the relationship with a post-purchase strategy where you build on that trust, seek customer feedback to prove high customer satisfaction and reward their loyalty.

  Some content you may want to create here includes :

  • Thank you emails
  • Follow-up emails
  • Follow-up calls
  • Product how-tos
  • Reward program
  • Surveys

  5. Advocacy

  The final stage of the B2B customer journey map is advocacy.

  This is the stage beyond loyalty where your customers aren’t just coming back for more ; they’re actively telling others about you.

  This is the cream of the crop when it comes to the B2B buyer stages, and it happens when you exceed customer expectations repeatedly.

  Your goal should be to eventually get all of your customers to this stage. Because then, they’re doing free marketing for you.

  This is only possible when a customer receives enough positive B2B customer experiences with your company where the value they’ve received far exceeds what they perceived they have given.

  Here are a few pieces of content you can create to fuel advocacy :

  • Surveys
  • Testimonial requests
  • Referral program

  Difference between B2C and B2B customer journeys

  Every person on earth who buys something enters the customer journey.

  But, not all customer journeys are created equal.

  This is especially true when you compare the B2C and B2B customer journeys.

  While there are similarities, the business-to-consumer (B2C) journey has clear differences compared to the business-to-business (B2B) journey.

  

  The most obvious difference between the two journeys is that B2B customer journeys are far more complex. 

  Not only are these two companies selling to different audiences, but they also have to deploy a completely different set of strategies to lead their customers down the path as far as they can go.

  While the journey structures are similar (from awareness to advocacy), there are differing motivating behaviours.

  Here’s a table showing the difference between B2C and B2B in the customer journey :

  Different Factors	B2B	B2C
  Target audience	Smaller, industry more important	Larger, general consumer
  Buyer	Multiple decision-makers	One decision-maker
  Buying decision	Based on needs of the organisation with multiple stakeholders	Based on an individual’s pain points
  Buying process	Multiple steps	Single step
  Customer retention	Organisational needs and ROI-based	Individual emotional factors
  Repeat sales driver	Deep relationship	Repetition, attention-based

  Step-by-step guide to building a B2B customer journey map

  Now that you’ve got a basic understanding of the typical B2B customer journey, it’s time to build out your map so you can create a visual representation of the journey.

  

  Here are six steps you need to take to craft an effective B2B customer journey map in your business :

  1. Identify your target audience (and different segments)

  The first step in customer journey mapping is to look at your target audience.

  You need to understand who they are and what different segments make up your audience.

  You need to look at the different roles each person plays within the journey.

  Unlike B2C, you’re not usually dealing with a single person. You likely have a few decision-makers you need to interact with to close a deal.

  The average B2B deal involves 6 to 10 people.

  Analyse the different roles and responsibilities of your audience.

  Figure out what requirements they need to onboard you. Understand each person’s level of influence in the buying decision.

  2. Determine your customers’ goals

  Now that you have a clear understanding of each person involved in the buying process, it’s time to analyse their unique needs and goals.

  Unlike B2C, which will include a single person with a single set of needs and goals, you have to look at several people through the decision-making process.

  What is every decision-maker’s goal ?

  An entry-level admin will have much different goals than a CEO.

  Understand each of their needs as it will be key to selling them and taking you to the next person in the chain of command.

  3. Lean on data and analytics

  Now it’s time to analyse your data.

  You don’t want to guess what will work on your B2B buyers. Instead, leverage data that proves what’s working (and what’s not).

  Analytics software like Matomo are crucial tools in your B2B customer journey toolkit.

  Matomo can help you make data-driven decisions to fuel customer acquisition and loyalty to help get more customers all the way to the advocacy stage.

  Using Matomo (which analyses and interprets different data sources) can give you a holistic view of what’s going on at each stage of the journey so you can reach your goals.

  Try Matomo for Free

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

  Start for free

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  4. Draw out customer journey stages

  Now that you have your data-backed plan, it’s time for some customer journey mapping.

  You can do this on paper or use a diagram tool to create a visual B2B customer journey map.

  Here, you’ll draw out every single stage in your customer journey, including every single touchpoint from different decision-makers.

  5. Determine each customer touchpoint

  Once you’ve drawn up the customer journey stages, you’ll have a key list of B2B customer journey touchpoints to implement.

  Write down every single customer interaction possible on the journey through.

  This could be reading an email, a blog post or watching a video on your home page.

  It could be an advertisement, a phone call or a follow-up email.

  It could even be a live demo or video sales call (meeting).

  6. Identify your own goals

  Now that you’ve got your visual B2B customer journey mapping done, it’s time to go back to you and your company.

  What are your goals ?

  What are the end results you’re looking for here ?

  You’ve got your current map in place. Now, how would you like customers to go through this journey ?

  Where would you like them to end up ?

  Look back at your company’s primary objectives if you’re stuck here.

  If your company is looking to increase profit margins, then maybe you want to focus more on retention, so you’re spending less on acquisition (and leaning more on recurring revenue from existing customers).

  How to create a Matomo funnel to track your B2B customer journey

  If you want to start tracking and optimising your B2B customer journey, you need to have a good grasp on your funnel.

  The reality is that your customer journey is your funnel.

  They’re one and the same.

  Your customer journeys through your sales funnel.

  So, if you want to optimise it, then you need to see what’s going on at each stage of your funnel.

  

  With Matomo, you can map out your entire funnel and track key events like conversions.

  This allows you to identify where your site visitors are having problems, where they’re exiting and other obstacles they’re facing on their journey through.

  To start, you first define what events or touchpoints you want included. This could mean :

  • Landing on your website
  • Visiting a product page
  • Adding something to cart
  • Going to checkout
  • Clicking “buy”

  Then, at each stage, you’ll see conversion rates.

  For example, if only 3% of your visitors go from landing on your website to the product page, you likely have an issue between your homepage (and other pages) and your product pages.

  Or, if you can get people to add to cart, but you rarely get people going to checkout, there’s likely a problem to fix on your add-to-cart page.

  By leveraging Matomo’s funnels feature, you get to see your entire customer journey (and where people are falling off) so you understand what you need to optimise to grow your business.

  If you’re ready to start building and optimising your customer journey today, then try Matomo for free for 21 days.

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