Why B2B Marketers & Publishers Should Stop Using Google Analytics

Google Analytics (GA) is the go-to web analytics platform in the marketing world, with its extensive use spanning the B2C and B2B worlds. Today we explore where GA has limitations for B2B marketers and where there can be alternative solutions that can provide a better fit the unique challenges that B2B presents.

In our opinion there are a number of core challenges which GA leaves B2B marketers struggling to overcome;

  • GA continues to have legality concerns, and B2B publishers and marketers typically have access to sensitive data beyond the individual, meaning a B2B site may have personally sensitive data as well as business sensitive data – which compounds the PII concerns. We have spoken about the potential legal ramifications for GA and B2B publishing here 
  • GA is at its core an individual [person] tracking solution, which really boils down even further to being a devices tracking platform – where B2B needs the ability to track accounts. In the World of B2B, what we really need is the ability to track accounts and the decision making universe that lives within that named account. Where multiple users from the same organisation might access a website, it becomes challenging to identify and track individual users accurately. This limitation makes it difficult to get a comprehensive understanding of user journeys and behaviour within an organisation
  • GA doesn’t measure every page view – it measures samples of page views – which is designed for modelling data in very large scale environments like B2C news websites. In B2B we need precision monitoring, and not scaled modelling.
  • GA has no capability to handle named account tracking and multiple stakeholders – and we have talked on this blog before about how the average B2B organisation has 5.4 individual stakeholders in their decision making cycle – and with that, no way to track long sales cycles. This is because GA relies on web cookies, which firstly are being phased out and secondly, they have an average lifespan of just 30 days.
  • GA lacks the demographic data that really matters or B2B publishers and advertisers – where it carries some basic demographic data like gender and age, it lacks data around job roles, seniority and firmographic data like company size, industry and specialism.
  • GA is siloed, without integrating into other key B2B platforms like SalesForce, Marketo, and Hubspot, meaning that metrics like revenue and attribution are limited to the onsite behaviour
  • You are essentially swapping your extremely valuable first party data with Google in return for Analytics. This may or may not be a problem, but if you believe you have high value audience segments, then you may want to build more robust moats around your data pools
  • GA lacks monitoring tools which are really relevant to B2B marketers, with data lacking or non-existent in areas like
    • Which accounts have been on site, what have they read, how long were they there, did they show intent?
    • How our key web forms perform
    • Onsite conversion reporting (without Google bias) and integration with audience API’s of media buying platforms where B2B marketers invest significantly – such as LinkedIn
    • Roll-up reporting to see all stats across micro-sites in one view
    • Richer media analytics; videos, audio etc

So far we have only presented problems, and at this stage, its important that I point out that I cannot provide ALL of the solutions. However here at FunnelFuel, we have been busy building an insights and analytics solution which we hope over time will continue to grow to satisfy more and more of these concerns. Here’s an overview of how it all works and what it does

Introducing The FunnelFuel B2B Analytics Platform

Taking these limitations into account, we set about designing a B2B analytics platform which was built from the ground up to meet the needs in this space. Here are some of our core features;

A GDPR compliant, Cookieless alternative to GA

It’s no secret that web cookies are an endangered species harking back to the early days of the web. If you missed the memo, they are on their way out, and platforms like Google are in the process of deprecating them. In a more privacy aware world spearheaded by initiatives like GDPR, cookies are much less tolerated by users, many of whom are blocking them. Step forward the FunnelFuel analytics

What are the benefits of going ‘cookieless’?

  1. Cookieless solutions are more accurate and frankly those solutions still using cookies are increasingly becoming more and more unreliable. These solutions do not need cookie banners and thus you don’t need to second guess decisions in order to get the full picture.
  2. Privacy friendly – as personal data is not collected, you get assurance that you’re respecting users whilst meeting all the privacy law compliance requirements, globally.
  3. No absolute need for annoying web cookie consent banners – which eliminates hassle for your users. We still recommend that sites using FunnelFuel follow the disclosure guidance that we offer, as we believe a front foot, transparent and respectful relationships with your web users necessitates this – but we also use a core tracker which has ben signed of within the EU as not requiring disclosure.
  4. GDPR compliance – as cookieless analytics solutions use alternative tracking methods to protect a users privacy, they’re easily configured to comply with strict privacy laws like GDPR.
  5. Data is stored on our server not your users device – giving you true first party data ownership

Cookieless solutions like FunnelFuel use alternative [to cookies] tracking like IP addresses, which can’t get deleted by users or turned off. IP addresses have an average lifespan of over 1 year versus 30 days for cookies, so they represent better alignment with B2B sales cycles too. Company level IP addresses remain static on average for much longer, so organisation level tracking is even more robust again.

Named accounts and company level tracking comes front and centre

We use robust and best in class databases to identify companies visiting your website/s based on their IP address (we link IP ranges back to organisations, we don’t store IP addresses, we instead link them to organisations and then save the organisation, and only then when the company is >50 employees in the office we’re tracking), giving us a much clearer view as to which named accounts have been on your web site in with country, globally.

We then apply the company data against all of your usual web analytics data points; like city, time on page, pages visited, funnels, forms, entry pages, referrer, exit pages and many more

We also uniquely crawl your site to categorise your pages into FunnelFuel’s B2B content taxonomy. This helps you to quickly understand exactly what topics have been read about by which company. Additionally, we crawl B2B publisher pages using the same technology, making it easy for B2B advertisers to buy super-relevant pages around the internet on the worlds leading niche B2B websites.

5 cookieless attribution models

We could talk all day about attribution modelling, and how it is evolving. I believe the below captures a pretty thorough overview of how it can work. Here at FunnelFuel we deploy a number of these potential tactics, and continue to enhance our offering – but the long and the short of it becomes – a cookieless approach is best suited to monitoring longer sales cycles more accurately and the 5 different models help build a really deep picture of the marketing landscape and how it interacts between channels.

Cookieless attribution modelling refers to the practice of attributing conversions or actions to marketing channels or touchpoints without relying on traditional tracking cookies. This approach has gained importance due to privacy concerns and increasing restrictions on third-party cookies. Instead of cookies, cookieless attribution modelling utilises alternative methods and technologies to track and attribute conversions accurately. Here’s how it works:

  1. User-level identifiers: Cookieless attribution relies on user-level identifiers, such as hashed email addresses or device IDs, to track and connect user interactions across different touchpoints. These identifiers serve as a privacy-friendly alternative to cookies and enable the attribution model to link user actions without relying on individual tracking cookies.
  2. Deterministic matching: Deterministic matching is one of the key techniques used in cookieless attribution modelling. It involves matching the user-level identifiers across different marketing channels or platforms to create a unified view of the customer journey. This matching can be done through common identifiers shared by the user, such as an email address provided during a website registration or login process.
  3. Probabilistic matching: In cases where deterministic matching is not possible or practical, probabilistic matching is employed. This method uses statistical algorithms and machine learning techniques to analyse patterns and behaviours to make probabilistic associations between user actions and touchpoints. It relies on various data points, such as IP addresses, browser characteristics, device information, and contextual data, to identify and connect user interactions.
  4. Cross-device tracking: With the prevalence of multiple devices used by individuals, cross-device tracking becomes crucial for accurate attribution. Cookieless attribution modelling incorporates techniques to track and link user interactions across different devices, allowing marketers to understand the impact of various touchpoints within the customer journey.
  5. First-party data integration: Cookieless attribution modelling emphasises the use of first-party data, which is data collected directly from users with their consent. By integrating first-party data from different sources, such as websites, apps, and customer relationship management (CRM) systems, marketers can gain a more comprehensive view of the customer journey and attribute conversions accurately.
  6. Machine learning and algorithms: Advanced machine learning algorithms are employed in cookieless attribution modelling to analyse user behaviour, identify patterns, and determine the most significant touchpoints in the conversion process. These algorithms consider various factors, including the timing, sequence, and impact of touchpoints, to assign appropriate credit to each channel or interaction.
  7. Contextual and campaign-level data: Cookieless attribution modelling takes into account contextual information, such as the content of the ad or the landing page, to better understand the influence of specific campaigns or creative elements. By analysing campaign-level data, marketers can identify the effectiveness of different marketing initiatives and optimise their strategies accordingly.

Cookieless attribution modelling represents an evolving landscape as marketers adapt to changing privacy regulations and technological advancements. It requires leveraging alternative user identifiers, advanced matching techniques, cross-device tracking, and robust data analysis to attribute conversions accurately and gain insights into the impact of marketing efforts across different touchpoints.

Conversion Rate Optimisation (CRO)

Conversion rate optimisation first really came to the fore in the Worlds of B2C, more specifically in the fast paced, entirely ad funded world of D2C brands. Direct to Consumer brands popped up around the growth in the power of the ad engines behinds sites like Facebook, Instagram and Pinterest, where the proliferation of somewhat cheap clicks married with robust demographic data created a D2C boom. D2C brands use high volumes of consumer data to optimise, but B2B presents a different set of challenges.

We don’t get the benefit of high volumes of data pools, but we do benefit from precision around data. The average B2B website isn’t counting its daily visits in the millions, we’re instead wanting to carve up smaller pools of data even more granularly. This opens up some tools which are incredibly useful for B2B which are harder to use in B2C, like;

  1. Session recordings; we enable B2B marketers and publishers to identify named accounts that enter their website and to watch recordings of their exact activity on site. Sometimes sheer numbers (time on site, page views etc) don’t tell the full story, and watching exactly what a named account did opens a new world of precision data
  2. Dynamic A/B testing is baked in – meaning you can test subtle changes in landing pages in order to drive stronger responses, then automatically direct your traffic to the winning page. This one comes straight out of the D2C playbook and is now available for B2B marketers who want to get the maximum impact when named accounts come onto their website/s
  3. Form analytics – B2B sites are full with forms, and these come in thousands of variations. Slight tweaks can have huge conversion impacts. We measure all forms, and provide insights that can radically improve form fill rates. Small tweaks to the language [to make forms less complicated], reduction in fields, or optimising better to mobile are just 3 ways that your form can be letting you down. We show data like
    1. What percentage of users start the form
    2. The forms conversion rate
    3. How many people re-submit the form
    4. What the hesitation time is (how long to people hover over before starting the form)
    5. How long it takes to fill in the form on average
    6. Time to conversion
    7. Hoe the same form performs on different pages (linked to our A/B testing tools)
  4. Funnels; these help measure the journey from first interaction to completion. This helps identify how your website/s flow, where drop-offs happen, which actions are taken and how each funnel compares. Build comprehensive sets of funnels which match user journeys, including refer insights on entry and exit points, including a segmented user log of all visitors who entered funnels. Small tweaks in each stages performance can make huge overall impacts

Visitor and company profiles

One of our most standout features is our user and company profiles, which enable you to identify exactly what each individual visitor has done on your web properties. We create a persistent user profile which is updated like a doctors record every time that user returns to the website. The same applies for companies and named accounts, meaning you have an organisation level profile card and a profile card for all employees of that organisation who visited your sites.

Unbiassed search engine metrics to aid SEO

In a world as competitive as B2B, where winning attention from ITDM’s is ever harder and more fraught, your brand needs to be omnipresent in all areas online where ITDM’s are spending time, from owning contextual placements next to research media to owning high ranking positions across the key search engines – including Google, Yahoo and Bing. We have built full integrations with each of these search engines search consoles, to seamlessly pull a much fuller suite of SEO based ranking data into our analytics platform

What does this mean in reality? well anybody who has looked at these sorts of reports in Google will be familiar with the phrase ‘keyword not defined’ in referrer reports. We have entirely removed this problem

We then provide unbiassed search engine ranking reports, keyword ranking positions, crawling statistics, campaign tracking and full web vitals.

Whether you need specialist B2B SEO help and work with FunnelFuel, or otherwise handle your SEO directly or with an agency, this data is invaluable in delivering transparency and the data required to make real improvements in your brands online visibility

Tag manager

B2B marketers are typically running advertising campaigns across a wide range of media buying platforms, whether that’s Google, LinkedIn, FunnelFuel, Twitter etc. These platforms all want to place tracking pixels on site, which often causes a huge compliance issue as well as concerns around data security and integrity. Pixels are a source of weakness and can cause page rendering issues, slower websites etc.

That’s why we built a full tag manager which gives you easy control over all third party tracking codes. This centralised management makes it easy for you to deploy tracking without needing a developer or otherwise having to go into the backend of your site. Dropping pixels this way is lighter touch and more controlled then a direct integration.


Do you want to learn more about how FunnelFuel can help your business with better B2B analytics and media buying? Reach out using the form below to schedule your free demo and solutions discussion with one of our B2B specialists today  


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