How to fix high Direct Traffic in your CRM with Revenue Attribution
This article was last updated May 2023
Most B2B users of leading CRM systems (or indeed Google Analytics) have been stumped by high levels of Direct Traffic. Seeing Direct Traffic far outstriping all other channels.
Unsurprisingly, these numbers are not reflecting the true sources of leads and traffic. Instead, as we’ll show in this post, they’re the victim of inadequate tracking and single-touch attribution.
Without tackling this problem B2Bs and their go-to-market teams remain none the wiser about how they’re actually generating leads. They simply cannot trust the data, making any attempt to scale more a case of hope than of targeted action.
In this post, we’re going to examine what’s behind the high direct traffic phenomenon and how B2Bs can solve it. Basically, we want to show you how you can make your acquisition numbers look something like this👇
Acquisition data from a Dreamdata customer.
Dotted vertical line marks date of customer’s Dreamdata purchase.
Contents:
The CRM high Direct Traffic problem
Why is this a bigger-than-expected business problem?
What’s causing the CRM high Direct Traffic?
How can you solve it?
Multi-touch attribution
High Direct Traffic in CRM and Google Analytics
HubSpot defines Direct Traffic as:
“[those] people who typed the URL directly in their browser, or removed all query parameters before entering a site.”
Google similarly classifies Direct Traffic as traffic where:
“no referral information is available, such as when a user arrives on your site or app directly. These include users who enter a URL in their web browser or click a link from a bookmark, mobile app, or offline document.”
This begs the question, can there really be that many people typing or bookmarking my URL as the first touch?
Of course not.
Acquisition is much more diverse. Naturally, the more channels you’re marketing on the more diverse it is.
Which means that many of the touches which are being dumped into Direct are anything but. Leaving you with a situation where ‘non-direct traffic’ is ending up as Direct.
This misplaced traffic has been aptly coined ‘Dark Traffic’. The problem with high levels of Dark Traffic is that it muddies the waters of what is actually taking place in the buyer journey. Blindfolding B2B’s when it comes to optimising or scaling their go-to-market efforts.
These business repercussions are hard to dismiss.
Why are high levels of CRM Direct Traffic a business problem?
Not being able to see the impact of channels on acquisition is a much bigger business problem than just hurting marketing’s ability to prove their efforts are profitable.
Above all, not being able to dissect your traffic into the source channels (and even more narrowly campaign) means not having clarity over your customer journey.
Without this clarity, it’s impossible to optimise and scale.
Let’s say c-suite issues a quarterly target for x2 growth.
You take a look at your CRM and 70% of your leads were apparently acquired through Direct.
Knowing that this is highly unlikely, the assumption quickly becomes that these must be originating from Social activities.
BDRs are hired, Social Selling is ramped up. No impact. Quarterly target missed.
Next quarter, money is pumped into paid campaigns to bring traffic and hope this converts. Leads are poor and targets are now further than ever, not to mention the money that’s gone out the window.
Turns out it was your email campaign and a couple of referring sites that were bringing in real quality leads. Unfortunately, poor tracking wasn’t picking this up.
Now, before we jump into how you can start looking to overcome the issue, we need to take a look at why this happens in the first place.
What’s causing all this Direct Traffic?
As you’ve probably guessed already, there are a number of reasons for Direct Traffic being disproportionately shown as the main source of traffic/acquisition. Here are some of the most common:
1) Tracking. Tracking is likely the biggest contributor to unrealistically high direct traffic. This can happen either because on-site tracking or form submissions are missing a tracking script, and/or because the tools on your go-to-market tech stack aren’t connected. Here are a few examples:
A user submitted a Form on a page without a tracking script. Your CRM will only recognise that the form submission came from a site visit, but will not be able to accurately allocate a source without the tracking script on the page. So the visit gets dumped into Direct Traffic.
A user lands on a page without the tracking script and then proceeds to another page with the script. Direct Traffic.
You’ve sent emails from a product outside the CRM that’s not tracking links in the email. Making tracking impossible and so, you guessed it, Direct Traffic.
2) Cookies disabled. If you haven’t enabled cookies on your site, or the visitor is rejecting marketing/advertising cookies it might not be possible to track the source of the visit. Similarly at form level, where cookie tracking has been disabled on the form. All of which will make the visit be counted as Direct Traffic.
3) Referral URLs. Sites may be referring to yours using URL links. Without UTM parameters this traffic might also be improperly syphoned off to Direct Traffic.
Sometimes a referrer is dropped because of technical reasons. And whenever a referrer is dropped, it’s impossible to determine the origin of the traffic source, leading to it being defaulted to direct traffic.
Documents and PDFs can also send direct traffic through embedded links - think ebooks. These are also susceptible to the same fallacy and thus generate more Direct Traffic.
4) UTM mapping. Incorrect or missing UTMs on your campaigns (or referral links) is a common cause of Direct Traffic.
5) Single-source attribution. When the models processing the data draw only on a single source, it’s unable to adequately handle the multiplicity of touches that take place across the B2B buyer journey. Including those touched that are only associated with the account at a later point.
For instance, say a customer has a direct click from an untracked email. Yet, the customer was actually acquired through an ad clicked by another user within the same account. But this user isn’t linked to the account in the CRM. The value of the paid campaign is ignored.
You can read more into the problems behind single source data in this post.
How to solve the Direct Traffic problem?
The first 4 causes can largely be kept in order through advice that is readily available in the net, such as:
Troubleshooting your CRM’s tracking script and introducing proactive tracking audits and testing will limit the extent to which tracking issues flare up.
And, adding UTM parameters on all referral links as well as introducing UTM mapping and regular testing will minimise the risk of incorrect or missing UTMs.
However, while these certainly set you on the right path, they only go part of the way in overcoming the problem, as this 👇 HubSpot customer pointed out.
The attribution question however, is a little harder to overcome.
CRMs are not designed for making sense of the multi-touch, multi-stakeholder, multi-device B2B customer journey.
Ignoring all these touches by focusing on a single ‘original source’ touch makes it particularly problematic to analyse your go-to-market activities.
B2B Revenue Attribution
It’s not just about making sure the ‘original source’ of the lead is not incorrectly dumped into direct traffic. It’s about getting a holistic picture of all the channels and touches, from all the stakeholders, that influence the sale.
To answer this question, with as much accuracy possible, we need to look at:
Better tracking and mapping.
Connecting all the tools in the go-to-market tech stack (from Marketing, Sales, and CS)
Modelling this data with multi-stakeholder (account-based) multi-touch attribution
Let’s check out how a B2B Revenue Attribution tool brings all of these together to bring you to this stage 👇
Acquisition data from a Dreamdata customer.
Dotted vertical line marks date of customer’s Dreamdata purchase.
The central element of multi-touch attribution is taking into account every one of the touches that happen across the customer journey. This allows marketers to see the impact of all the events that took place on their channels, especially when the leads were acquired.
Tracking
A revenue attribution platform will offer a leading tracking and identification javascript.
The script will sit in your site and track all anonymous user visits before identifying them - say when the user makes a form submission, or via reverse IP lookup. Gathering all event data for mapping and modelling.
The script will continue feeding data to enrich your customer (account) profiles throughout the buyer journey.
Alternatively, the attribution platform will offer integrations with leading CDP providers, whose scripts perform the same functions.
You can read more on Dreamdata’s tracking script here.
Connecting all tools in the go-to-market ecosystem
In order to bring all the channels under one roof and measure them against revenue and pipeline generation, it’s necessary to link data from across the revenue ecosystem.
Problem is, almost without exception, these tools are siloed. Meaning that the customer journey data is disjointed. So any attempt to bring it under one roof is pretty much impossible.
A revenue attribution platform will consolidate all the revenue-related data into one place. That means data from on-site tracking as well as from across your ecosystem - CRM, ad platforms, automation tools, etc.
Once this is all merged and cleaned - to make sure there’s no duplication or empty values - the data is run through multi-touch attribution modelling.
Read more about the behind-the-scenes data processing here.
Multi-touch attribution modelling
The multi-touch attribution modelling will then map every touch of the customer journey and attribute these to pipeline and revenue generated.
This means that the actual first touch will be identified and given credit, no matter when the data is gathered (as the example above).
Ultimately, what this means, is that the revenue attribution platform will enable you to properly identify which channel actually acquired the lead. Find out more about multi-channel attribution in this post.
Coupled with UTM and cookie best-practice, a Revenue Attribution platform will finally enable you to get insight into your acquisition!
Why not give Dreamdata’s Revenue Attribution tool a try and see for yourself?
