Why Your CRM Is Lying About B2B Lead Attribution

Transcript

Louis:
Welcome back. Today we’re going to try a slightly different format of episodes and we’d genuinely love to hear what you think about it. We’re going to talk through three real world curveball questions that come up in performance marketing quite a bit, and we’re going to contextualise them and run through what we do in each scenario.

These are all questions that come from smart marketing teams, often when things are going really, really well. So it doesn’t necessarily mean that anything’s wrong, it just means that there are some knowledge gaps to work through.

We’re going to be focusing on one specific theme, and today’s theme is lead attribution in the real world. All of these curveball questions will tie into that one specific theme. So let’s get started with the first one.

---

Curveball #1

Louis:
We’ve increased ad spend and more leads are coming through, but they’re showing us from other sources in the CRM, not from ads. What’s going on here? Maelien, do you want to head this one up and contextualise and talk through how you’d handle this?

Maelien:
So that’s a great question, and it’s actually a question that we come up against quite often. The issue that we often see here is when you’re looking at your CRM, you’ve only got one or two bits of data, and that is typically going to be the last session source.

But in some cases, like with HubSpot, it’ll also be the first session source. So what you’re missing out on here is everything that happens in between what someone does first and what they do last.

So say, for example, they came and they saw you at an event, and then they interacted with a number of different ads in the very middle of the journey. And then at the end they searched your brand name and they came in directly. Well, in your CRM it would look like it was an event and a brand, but you wouldn’t get any picture around what happened with the ads here.

So how we like to treat this usually is that it needs to be looked at as a data story rather than just trying to paint a picture from one place like your CRM.

So really what you should be doing here is looking at your CRM for your first touch session, and then also for the last touch session as well, and contextualise that with your ad platforms. And these should be set up to be capturing conversions like calls, form fills, everything like that. So then you can see, okay, so I’m seeing that there’s been an increase in the number of calls and the number of form fills.

And you might be able to get other things then as well. Like actually, we’re now having a look at what’s happening on the calls and attributing them back to sources, and you might find all of a sudden that you can get a better picture there with your ad data as well.

So you should then be able to paint a picture of, right, I can see what’s going on here. We’ve clearly had more form fills going on. We’ve had more people filling out the contact us. It’s just that with the events that we’re doing and the high level of brand that we’ve got, these are soaking up a lot of that picture. But we can see that that ad spend is working because it’s increasing in these other areas like direct, like events.

Louis:
Yeah, it’s such a good point. There’s this thing that we talk about a lot in marketing called the messy middle, where it’s quite easy to define the first point and the end point that someone got in touch, but there’s also this whole multi-touch journey in the middle.

And even when you’re impressing the first point that someone got in touch, you don’t know if something else has happened offline to trigger that as well. So we have to remember that we can only deal with the stuff that happened as online interactions.

The other thing I’d like to highlight as well is that technology doesn’t work a hundred percent of the time. So obviously there’s things like consent mode, like whether or not the script that you’re using to populate hidden fields gets printed in the CRM, for lack of a better word, and loads of other things that could mean that the source data isn’t actually showing up properly in the CRM as well.

It also kind of talks about how people use the internet and how they discover and decide on getting in touch with a company as well. So for example, someone could go to an event and have a positive interaction. They could go about their business and forget about it for a little while, see an ad, be reminded of it, and then go through to organic search, type the company name in and enquire that way.

So the data in your CRM isn’t always a hundred percent representative of the user journey.

The main thing to take away is that you’re never going to get a perfect version of the story of how someone comes to enquire. So what you really have to do is appreciate that whatever you’re seeing in that first source and that last source is never going to be the perfect truth. It’s more of an indication that helps you optimise your marketing and apportion your budget. But it’s not something we should draw a line in the sand and say this is exactly what’s happened. Data is usually more of an impression. It’s more like a treasure map. It’s not to be believed as the full and perfect truth.

---

Curveball #2

Louis:
So onto the next curveball, which is: do the numbers from three months ago look different now compared to what they were in the end of month report at the time? Maelien, do you want to kick this one off?

Maelien:
Yeah, sure. So I think when you’re looking at three months ago and the data’s changed, generally there’s one main reason here, and that is to do with attribution windows.

Now, if you are marketing in B2B, then these attribution windows, unless you’ve stuck with the default, are generally a lot longer than you’d typically deal with. Just because you know that that sales cycle from first touch point to turning into a customer takes so much longer.

So it’s not untypical for those to be at the very least 30 days, but generally 60 or 90 day attribution windows. So that three month question actually fits perfectly with that 90 day window.

What I’d say here is that perhaps someone interacted with an ad 90 days ago or within that 90 day window, and since then they have converted. What’s going to happen here is Facebook, Google, LinkedIn, whatever it is that you’re using, is clever enough to be able to grab that first interaction and associate it with their conversion recently.

So say if they filled out a contact us or a form on your website, they link that back to that click that happened 90 days ago, and that’s going to happen all over the board here.

So whereas you might have reported a couple of days after the month ends, a long time’s gone past since then, a lot of people have been clicking and a lot of people have maybe seen more stuff from you organically, with ads, maybe been to an event, and since then converted. And that’s going to get attributed back to within that 90 day window.

Louis:
So a really important distinction here is that when you see conversions in the ad platforms, a chunk of that conversion, if not all of it, will be attributed back to when the first click happened. So if someone converts 60 to 90 days later, you’re going to see at least a portion of that conversion show up back then.

With ad platforms, they typically don’t report on conversions that happened at the time of the conversion. They report on what happened at the time of the click, which can often make it difficult to match conversions in the CRM to what happened in the ad platforms.

The other thing to bear in mind is data lag. Most ad platforms take time to process conversion data. So for example, if you’ve run Performance Max campaigns, you’ve probably seen the coloured strip underneath the timeline chart that says it’s going to take 14 days to process your conversions.

What that means is that if monthly reports are being sent less than 14 days after the end of the month, there’s still conversions that are going to be processed into that report.

So again, there’s not really a fix here. There’s just a consideration. Data in your reports will change over time, and that’s just something that happens. The main thing is that you remember what your attribution window settings are, and that you appreciate there’s going to be a lag in conversion data being processed into reports.

---

Curveball #3

Maelien:
So the next question that we’ve got is: your reports are saying 50 conversions, but when we look at the CRM, it is only showing 30 leads. What’s happening here? Where’s the difference? Louis, how would you answer this?

Louis:
So this one often comes down to definitions and language. The same terms can mean different things depending on the domain expertise of the person that you’re speaking to.

A lot of the time, performance marketing insights need a little bit of translation to make them as helpful as possible. Maybe you’re speaking to someone who already has a firm grasp on performance marketing, but maybe you’re speaking to someone who’s more focused on CRM and pipeline and rev ops. In those two different scenarios, different words are going to mean different things.

So I’ve got to focus really hard on putting my insights in a way that mirrors the language of the person I’m speaking to. Because a conversion to me is basically a valuable action. Someone that did something valuable after seeing an ad. But to someone else, a conversion could mean a closed sale.

One approach I really like to take here is to break out all of the different conversion types in a report. So if I’m going to say the campaigns generated 50 conversions, I also want to say 30 of those were lead form submissions, 15 were phone calls, and five were lead magnet downloads. That really helps provide some clarity around those numbers and avoids causing that confusion around the disconnect between saying 50 conversions and the CRM saying 30 leads.

Maelien:
I really want to unpack what you said in terms of calls, because I see this as one grey area that comes up again and again.

Sometimes, if we take Google Ads as an example, you can see a real difference in the number of calls versus what’s being attributed in the CRM. Sometimes none of those calls are shown against Google Ads in the CRM.

When you think about the quality of conversations that happen on a call and the likelihood of them turning into a customer, there can be a real disconnect here.

We had one client where, when we looked at Google Ads, they had about five times more conversions coming from calls than anything else. But in the CRM, none of those calls were being attributed back to Google Ads.

So we put call attribution software in place, specifically CallRail, and all of a sudden their call tracking was working way better. It didn’t fix it completely, but that channel went from looking like it was breaking even to being their most profitable channel.

So exploring these gaps between your CRM and your ad platforms can be hugely powerful.

Louis:
Yeah, one hundred percent. Sometimes we think of inbound calls as a channel in itself, but actually something usually had to happen to trigger that call being made. So getting that source data into the CRM is really important, and it’s something that’s missed quite a lot.

And I think the same could be said if you were just going to track lead form submissions. If you miss all the other stuff, like phone calls and lead magnet downloads, you’re only giving the ad platforms a very small segment of data. It might be the best quality data, but it might not be enough to make decisions on.

What we really want to be doing is giving signals back to the ad platforms to say, go and find us more people like this. And the more data you can feed back, the more effective it can be at turning that into actual enquiries in the short term.

Maelien:
And jumping back to what you said about conversions, when you’re thinking about platforms like LinkedIn, Facebook, and Google, you really want to give them as much data as possible to go and find the right people.

In an ideal world, we’d just give them purchase data. But especially in B2B, there’s often not enough of that. So what conversions means to us is feeding the right signals – high intent form fills, contact us forms from high intent campaigns, and those really valuable calls. All of those are what we’re calling conversions when it comes to the platforms.

---

Wrap-up

Maelien:
So there you go. Three different curveball questions and how we’d handle and tackle them ourselves.

If you like this type of episode and you have curveball questions of your own, then head to webmarketeruk.com/topic and send them over. We’d love to hear them.

Louis:
Thanks for listening. We’ll catch you on the next one.

Every performance marketer knows the feeling. You open your ad platform dashboard, and the numbers look fantastic. Conversions are up. Cost per acquisition is down. You feel incredibly proud of the campaign you just built.

Then, you open your CRM.

The CRM tells a completely different story. It shows a handful of leads. Worse still, it attributes those few leads to “organic search” or “direct traffic”. Your paid ads get absolutely zero credit for the revenue you know they generated.

This scenario creates massive friction between marketing teams, sales teams, and business owners. It leads to difficult meetings and unjustified budget cuts.

What you think you know about lead attribution is probably wrong.

The systems we rely on do not talk to each other perfectly. They operate on completely different logic.

In the latest episode of our podcast, Maelien and I introduced a new “Curveball Clinic” format.

We decided to tackle three real-world questions we constantly hear from smart marketing teams.

These questions usually pop up when campaigns are actually performing very well, but the data looks chaotic.

Today, we are diving deep into the messy reality of B2B lead attribution.

We will explore why your CRM misleads you, how to track B2B conversions accurately, and why you need to start treating your data as a story rather than an absolute truth.

The reality of B2B lead attribution

Before we answer the specific curveballs, we need to understand the playing field. B2B marketing does not operate like a simple e-commerce transaction.

If you sell cheap sunglasses, a user clicks an ad, buys the sunglasses immediately, and the system tracks the sale perfectly.

The journey is linear.

B2B buying journeys look more like a bowl of spaghetti.

They take months. They involve multiple decision-makers. They jump across devices, browsers, and offline channels.

Why CRM data can mislead performance marketers

Your CRM is an incredibly powerful tool for managing sales pipelines. However, it is a fundamentally flawed tool for measuring marketing performance.

Most CRMs operate on a binary system.

They look for a single source to credit for a new contact. They want a neat, tidy answer.

Marketing, however, is not neat or tidy.

Marketing is about building cumulative trust over time.

When your CRM forces a complex, multi-touch journey into a single dropdown menu labelled “Original Source”, it strips away all the nuance. It lies to you by omission.

What CRMs capture (and what they do not)

CRMs typically capture either the “first touch” or the “last touch”.

If your system uses a first-touch model, it records the very first way a user interacted with your website.

If they clicked a Google Ad six months ago, downloaded a brochure, and never spoke to you, the CRM records “Paid Search”.

When that same user attends a webinar, reads five blog posts, and finally calls your sales team to buy, the CRM still credits that initial Google Ad. It ignores all the hard work your content team did.

If your system uses a last-touch model, it does the exact opposite.

It only cares about the final action before the enquiry.

If a prospect spends a year engaging with your LinkedIn ads and building deep trust with your brand, they might eventually just type your URL directly into their browser to fill out a contact form.

The CRM will credit “Direct Traffic”. It completely ignores the thousands of pounds you spent on LinkedIn ads to create that demand.

The missing middle of the buyer journey

We call this the “messy middle”. It is the vast space between the first time someone hears about you and the moment they finally decide to buy.

Buyers do a tremendous amount of invisible research in this middle phase.

They ask peers for recommendations in private Slack communities. They watch your YouTube videos without logging in. They read your organic LinkedIn posts without leaving a comment.

Your CRM cannot see any of this. It only records the digital footprints left on your specific website.

If you rely solely on your CRM for B2B lead attribution, you will inevitably make poor decisions.

You will cut funding to the upper-funnel campaigns that actually generate demand, simply because the CRM cannot connect those campaigns to the final sale.

Curveball #1: “Our leads increased, but not from paid ads?”

This brings us to the first real-world curveball we discussed on the podcast.

Imagine this scenario. You decide to double your Google Ads budget. The following month, your total inbound lead volume jumps by 40%. You celebrate.

But when you check the CRM, the “Paid Search” lead count remains completely flat. Instead, you see a massive spike in leads attributed to “Organic Search” and “Direct Traffic”.

Your CEO asks you why you wasted the increased ad budget. How do you explain this?

Understanding the B2B CRM and ad platform data mismatch

Maelien handles this exact question frequently. The first step is to stop panicking. A B2B CRM and ad platform data mismatch is entirely normal when you scale up your marketing efforts.

You have to look beyond the default CRM dashboard. You have to understand that the CRM is likely showing you a last-touch attribution model.

If you increase your ad spend, you put your brand in front of more people. Those people see your ads. They register your brand name.

They might even click the ad and browse your site.

However, B2B buyers rarely fill out a “Contact Sales” form on their very first visit. They leave. They discuss it with their manager.

They research your competitors.

Mapping the whole journey: from brand to event to ad to direct

Let us trace a very common B2B user journey to illustrate this point.

A marketing manager attends an industry conference.

They walk past your booth and grab a flyer. They now have baseline brand awareness. (Offline touchpoint).

Two weeks later, they see your targeted LinkedIn ad. They remember your booth. They click the ad, read a case study on your website, and leave. (Paid Social touchpoint).

A month later, their boss asks them to find a solution to a specific problem. They remember your case study. They go to Google and type in your exact brand name. They click your organic search listing and submit a demo request. (Organic Search touchpoint).

Your CRM will likely log this lead as “Organic Search”.

Did the organic search listing generate the lead?

No.

The event and the LinkedIn ad generated the demand. The organic search simply captured it.

The ad platform will claim credit for a conversion, but the CRM will deny it. Both platforms believe they are telling the truth based on their own narrow rules.

Why CRM last click attribution breaks in B2B

This is why last-click attribution completely breaks down in B2B marketing. It gives all the glory to the final step of the journey.

Maelien advises clients to treat attribution as a data story, not a single data point.

You have to become a detective.

You need to look at your CRM data to see the first touch and the last touch.

Then, you must open your ad platforms and look at the conversion data there. If your ad platform shows a spike in form submissions or phone calls that correlates perfectly with the spike in your overall CRM leads, you have your answer.

The ad spend worked. It drove the overall business growth.

It just did not get the final click credit in the CRM. You have to educate your stakeholders to look at blended metrics and overall pipeline growth, rather than demanding perfect line-by-line attribution.

Curveball #2: “Why do results from 3 months ago keep changing?”

Our second curveball deals with historical data.

You present your monthly performance report for September. You report 45 conversions. Everyone is happy.

In November, you look back at September’s data in Google Ads to do some year-over-year comparisons. Suddenly, September shows 62 conversions.

The numbers changed. You look incompetent, or worse, you look like you are manipulating the data.

Your sales director asks why your old reports are suddenly inaccurate.

Attribution windows in B2B campaigns explained

Do not panic.

You did not make a mistake. The platforms are functioning exactly as designed, the culprit here is the attribution window.

Understanding attribution windows in B2B campaigns is vital for any marketer.

An attribution window is the period of time an ad platform will look back to claim credit for a conversion.

In fast-moving e-commerce, marketers often use a 7-day window. If a user clicks an ad and buys within 7 days, the ad gets credit. If they buy on day 8, the ad gets nothing.

In B2B, sales cycles take months.

Therefore, we use much longer attribution windows. We typically set these windows to 30, 60, or even 90 days.

We want the ad platform to know if a click eventually resulted in a sale, even if it took a full quarter.

What ad platforms report vs when CRMs report

This brings us to the core of the discrepancy.

Your CRM reports a lead on the exact day the person fills out the form. If John Smith submits a form on November 15th, the CRM records a lead for November.

Ad platforms do not do this. Ad platforms report conversions against the date of the click, not the date of the conversion.

Let us return to John Smith. John clicked your Google Ad back on September 10th. He spent two months thinking about it. He finally filled out the form on November 15th.

Your CRM puts that lead in November. Google Ads looks at the conversion, traces the cookie back to the click on September 10th, and retroactively adds a conversion to your September report.

Google essentially reaches back in time and alters your historical data.

Dealing with data lag in your monthly reports

This creates a significant headache for monthly reporting.

Your end-of-month report will always undercount your true performance, because people who clicked in that month will continue to convert in the future.

Furthermore, we have to consider processing delays.

Campaigns like Performance Max often take up to 14 days to fully process conversion data.

If you pull a report on the 1st of the month, you are missing a massive chunk of data from the final weeks of the previous month.

How do you handle this curveball? You manage expectations aggressively.

You must educate your stakeholders.

You need to explain that performance reports are snapshots in time, not permanent historical records.

You should include a disclaimer on every report stating that numbers will mature over a 90-day window.

When the sales team asks why the numbers changed, you can confidently explain that the marketing system is working exactly as intended, capturing long-tail conversions from your strategic investments.

Curveball #3: “50 conversions in ads, but only 30 leads in the CRM?”

Our final curveball is perhaps the most common source of friction between marketing and sales.

The marketing manager presents a slide showing 50 conversions from LinkedIn Ads. The Sales Director pulls up the CRM and bluntly states that they only received 30 leads from LinkedIn.

The Sales Director accuses the marketing team of inflating numbers to look good. The marketing team feels defensive.

Trust breaks down completely.

Different definitions: conversions do not equal leads

Louis addressed this exact scenario on the podcast. The root cause of this argument is almost always a failure of language.

The two teams are using the same words to describe entirely different things.

To a performance marketer, a “conversion” is any valuable action a user takes on the website.

This could be submitting a “Contact Us” form. It could be downloading a whitepaper.

It could be clicking a phone number to make a call. It could even be viewing a specific pricing page for more than two minutes.

To a sales professional, a “lead” is a qualified human being who has explicitly requested to speak to sales.

If you run a campaign that generates 20 whitepaper downloads and 30 demo requests, the ad platform correctly reports 50 conversions.

The CRM, however, might only classify the 30 demo requests as “Sales Qualified Leads”.

The whitepaper downloads might go into a nurturing sequence and bypass the active sales pipeline entirely.

Both systems are accurate based on their own definitions. The problem arises when marketing presents “conversions” without clarifying what those conversions actually are.

The role of call tracking for B2B lead generation

There is another massive factor that causes this discrepancy: phone calls.

Many B2B buyers still prefer to pick up the phone. They want to speak to an expert immediately rather than waiting for an email reply.

These phone calls represent incredibly high-intent leads. They are often the most valuable interactions a business can generate.

However, standard CRM setups are terrible at tracking them.

If a user clicks a Google Ad, lands on your website, and dials the phone number displayed in the header, Google Ads will track that as a conversion (if you set up call tracking properly).

But what happens in the CRM? The sales rep picks up the phone. They talk to the prospect. They manually create a new contact record in the CRM.

When they get to the “Lead Source” dropdown, they have no idea how the person found the website. They usually just select “Inbound Call” or leave it blank.

The ad platform claims the conversion. The CRM loses the attribution completely.

This is why call tracking for B2B lead generation is absolutely essential.

Louis shared a story about a client facing this exact issue. Google Ads showed a massive number of conversions, but the CRM showed very few attributed leads. We discovered that the vast majority of their Google Ads traffic resulted in phone calls.

Because they lacked integration, the CRM gave zero credit to Google Ads.

The business thought their paid search channel was failing.

We implemented CallRail, a dedicated call tracking software. CallRail bridges this gap. It dynamically swaps the phone number on your website based on how the user arrived. It then pushes that source data directly into the CRM when the call connects.

Suddenly, the CRM accurately reflected reality.

Google Ads went from looking like a waste of money to standing clearly as their most profitable marketing channel.

Why signals matter more than outcomes in ad platform optimisation

You must explain to your stakeholders why you track “softer” conversions like downloads or time-on-page in the ad platforms.

Sales teams only care about pipeline outcomes.

Ad platforms, however, need data volume to function effectively.

Modern ad platforms run on machine learning algorithms.

These algorithms need data points to understand what a “good” user looks like.

In B2B, high-intent leads (like demo requests) are relatively rare. If you only feed demo requests back to the algorithm, it will starve. It will not have enough data to optimise your campaigns.

We have to feed the platforms “signals”.

We track PDF downloads, video views, and newsletter signups as conversions in the ad platform to give the algorithm more data.

We tell the system: “Find us more people who behave like this.”

This improves targeting and eventually leads to more high-intent demo requests.

You just have to clearly translate this strategy to your sales team so they do not think you are trying to pass off a whitepaper download as a hot sales lead.

How to track B2B conversions accurately

Navigating these curveballs requires a shift in mindset. You have to move away from demanding perfect, linear attribution.

It does not exist.

Instead, you need to build a robust system that triangulates the truth.

Here is how to track B2B conversions accurately in the real world.

Do not rely on a single data source

Never pull up a single dashboard and treat it as gospel.

Your CRM tells you what your sales team sees.

Your ad platforms tell you what the algorithms see. Google Analytics tells you what the website sees.

You must look at all three.

If ad spend goes up, ad conversions go up, and total CRM leads go up, the marketing is working. Do not tear the system down just because the CRM attributes those leads to “Direct Traffic”.

Look for the macro correlations.

Break down conversion types in every report

Never report a single, blended “Conversions” number to your stakeholders. It breeds mistrust.

Every report you present should break down the exact actions taken.

Instead of saying “We drove 100 conversions,” you should say: “We drove 100 total actions. This breaks down into 20 demo requests, 30 inbound phone calls, and 50 top-of-funnel whitepaper downloads.”

This simple communication shift instantly aligns marketing and sales. It proves you understand the difference between an early-stage signal and a sales-ready lead.

Use tools like CallRail to bridge the gap

If your business takes phone calls, you cannot afford to guess where they come from. Implement dynamic number insertion software immediately.

Tools like CallRail integrate seamlessly with both your ad platforms and your CRM. They capture the messy middle. They ensure that when a high-value prospect picks up the phone, your paid media campaigns get the credit they deserve.

Stop letting your best leads fall into the “Unknown Source” bucket in your CRM.

Attribution is not about finding a single source of truth. It is about gathering enough reliable clues to make smart, profitable decisions about where to spend your next marketing dollar.

FAQs

Q: Why is B2B lead attribution so difficult?
A: Because B2B buying journeys are long, multi-touch, and involve multiple stakeholders. CRMs often capture only the first or last touch.

Q: What causes CRM and ad platform data to mismatch?
A: CRMs often miss touchpoints like calls or mid-funnel ad interactions. Ad platforms report based on attribution windows, not real-time conversions.

Q: How do attribution windows affect lead reporting?
A: Attribution windows delay when conversions are reported. This means your end-of-month report might undercount leads that convert later.

Q: What is the best way to track B2B conversions accurately?
A: Combine CRM data with call tracking tools and ad platform data. Break out conversion types and consider attribution windows and data lag.

Q: Why are calls not showing up as conversions in my CRM?
A: Without proper call tracking (e.g. CallRail), inbound calls from ads may be missed, creating a gap between ad performance and CRM-reported leads.