How attribution modelling can transform your understanding of B2B lead gen

If you want to improve your lead generation, it’s vital to be aware where your traffic is coming from. Understanding how people find your business and the route they take from initial discovery of you to becoming a paying customer is essential if you’re to optimise your organic content and make sure any paid ad spend is focused on the right areas.

But this is far from easy – and this is especially the case for B2B firms. However, there are tools available to help study your traffic and build a picture of how customers progress down the user journey. One of the most useful is attribution modelling, which is offered as part of the Google Analytics suite. 

In this article, we’ll explain how this works, why you need it and what it can tell you about how you should be targeting potential customers.

The challenges of B2B lead gen

One of the biggest challenges facing B2B firms when it comes to analysing and optimising their marketing is the length of the buying cycle. On average, buyers will visit a site around four times before making a conversion – and in some cases up to six or seven. When you think about it, this is a huge amount of research – in fact, it’s more times than you’d likely view a house before buying it.

This is understandable. Unlike in the B2C space, where a visitor may often end up going from discovery to purchase in a single visit, B2B buyers are typically looking at significant commitments. The products or services on offer are big-ticket items and could easily require six-figure capital investments or signing up for lengthy contracts, so it’s natural that purchasers will want to take their time and do their homework before making a decision.

However, the problem for marketers is that this lengthy buying cycle can make it hard to get a clear picture of the customer journey and what elements of your strategy you need to be focusing on to help customers through the process.

Looking beyond conversions

For instance, consider what you define as a ‘conversion’ for the purposes of your analytics. This will often be filling in a form, signing up for a free trial or using a contact us page. But by the time many B2B buyers complete this action, they’ve already interacted with you quite a bit.

At this stage, they’re familiar with the brand and may be visiting your website for a third, fourth or fifth time. This means they may well be coming directly to the page, perhaps via a bookmark, their browsing history or typing in the URL. Alternatively, they might take this action as the result of a targeted ad aimed specifically at people who’ve already shown interest in the brand. 

If it is the result of a retargeting ad, for instance, you might well conclude that Google Ads campaigns are responsible for the majority of conversions. But while this is technically true, it only tells half the story.

What you really need to be asking is: ‘How did this customer get to their final conversion point?’ What was their first interaction with your brand? What convinced them to come back and explore further? 

If you’re only focused on the final conversion, you won’t have this information, and in turn, you won’t know which earlier aspects of the customer journey you need to be looking at to optimise your campaigns. Fortunately, this is where attribution modelling comes in.

What is attribution modelling?

Attribution modelling is a way to understand how each marketing channel has contributed to your end goal, whether this is filling out a form, downloading an asset or making a purchase. It works by showing you a breakdown of where your traffic is coming from at each stage of the user journey.

This is particularly useful for B2B marketers, where it is typical for prospects to visit multiple times and interact with several different marketing channels before converting. While occasionally visitors will come to a website and convert on their first visit, in our experience, this is quite rare. Therefore, you need to know exactly what happened between the first contact and the last.

The improvements made in GA4

Google Analytics has had tools for attribution modelling for some time, but with the updates made to its user interface in GA4, it has become much easier to use, with Improvements including better visualisations to make it easier to understand and interpret the results.

In GA4, attribution modelling is divided into three categories – early, mid and late touchpoints. Early touchpoints will tell you which of your marketing channels was responsible for getting a user on the website for the first or second time. Mid touchpoints show how they’ve moved along the journey and what marketing channels convinced them to return. Finally, late touchpoints will show you which of your efforts resulted in the actual conversion.

How attribution modelling helps understand user behaviour

It’s equally important to optimise the marketing channels at the top of the funnel – the early touchpoints – as it is to focus on the mid and late touchpoints, but this can be difficult if you don’t know how your current efforts are performing.

Often, companies will look at their own data and see there is nothing recorded for early or mid touchpoints, so the only direct information they have about what led to a conversion is the final interaction. This gives firms an incomplete picture of the performance of their marketing funnel as a whole.

If companies are able to fill in these gaps with real data about their early and mid touchpoints, they can start better nurturing those leads, which will ultimately result in higher conversion rates later on in the user journey.

We often come across clients who can be overly-focused on one aspect of their marketing. For instance, we’ll hear from them that they only want to prioritise Google Ads and are not interested in metrics such as traffic or time on page. Often this is because their metrics show that one channel – such as Google search ads – offers the best conversion rates.

However, they often don’t understand that before this conversion happens, they need to build trust. This is especially true in the B2B space, where a sale could represent hundreds of thousands of pounds of investment. This trust building doesn’t happen in a single visit. 

The importance of marketing at every stage of the user journey

For instance, a common journey may start with a user clicking on a blog recommended to them via social media, which shows that the company has expertise and experience in their sector. This may then lead an individual to a product page where they learn more about what the company has to offer. Later, the user might then be shown a retargeting ad, at which point they return to the site and fill in a form. 

With traditional data analytics techniques, only the fact that the retargeting ad led directly to the conversion is recorded, so it’s not surprising that some clients make this their focus.

The attribution model, on the other hand, will show the full journey for every conversion. For example, it might reveal that 15 per cent of a final conversation can be credited to the early touchpoint stage, 30 per cent can be attributed to mid touchpoints and the remainder to the late touchpoint.

This will show you that even though you might think the later touchpoints are the most important, between them, the early and mid part of the journey might make up around half of the credit. This helps illustrate how much users rely on other channels to research a brand, and how they will come back multiple times and view different pages before they convert.

The differences between early, mid and late touchpoints

Understanding what the different sources of traffic are for each touchpoint at the different stages is also important in planning out campaigns.

While no two companies are the same as there’s no fixed standard, we typically see that early touchpoints are likely to include organic traffic from social media or search engines. Mid touchpoints tend to be a mix of organic channels and paid, targeted ads. Later touchpoints usually consist of both advertising and direct traffic.

The importance of accurate data tracking

One thing to bear in mind is that in order for attribution modelling to be effective, you need to have accurate tracking set up for your marketing activities. If this is missing, it can also end up giving an inaccurate impression of your customers’ user journeys.

For example, one issue we sometimes see is higher than expected levels of direct traffic. Some clients may take this as a positive sign that their brand awareness efforts are bearing fruit, but there could be another reason for this – a lack of proper tracking for other campaigns.

When is direct traffic not direct traffic?

It’s important to note that what appears on analytics as direct traffic – that is to say, traffic that does not come from a referring website such as a search engine, backlink or social media site – can in fact originate from a variety of sources. It’s often taken to mean traffic that arrives via a user typing your URL into their browser, or an autocomplete suggestion that takes users back to a site they’ve already visited, but this is not always the case.

Other common sources of ‘direct traffic’ include links from email campaigns or other marketing channels that do not have tracking set up correctly. This can skew your analytics, so it’s important to remember when building campaigns such as email newsletters to implement these tools properly in order to ensure full visibility.

How can attribution modelling boost your B2B business?

Attribution modelling is very easy to set up in GA4, so it’s an activity every B2B brand should do as part of its analytics. It’s something we always look to set up for our clients, but if you want to conduct your own analytics, it should be straightforward to get started. 

All you need to do is let Google Analytics know what actions you consider to be a conversion point and it will automatically generate an attribution model for you. From there it is a matter of understanding what this model is showing you – which is something an expert analytics partner can help with.

Ultimately, the main goal of using attribution modelling is to understand the full user journey, from initial awareness to conversion, and how firms can optimise their marketing to help guide prospects through this process. Using this helps ensure efforts are focused in the right places, not just the end of the funnel.

While attribution modelling doesn’t directly show where prospective clients may be dropping out of the sales funnel, it does tell you what channels you should be focusing your budget on. With the help of a full service digital marketing partner like Axonn, you can then turn these insights into action with the right mix of expert content to guide your target audience down the user journey and turn curious visitors into buyers.