Tracking Debt: The Hidden Cost of Building Conversion Tracking on the Wrong Tools
You've invested years building conversion tracking on a platform that was designed to send emails. That investment has a name — and a cost.
What Is Tracking Debt?
Tracking debt is what happens when marketing operations teams build conversion tracking on top of tools that were never designed for it — and then carry that system around for years.
It usually starts with the marketing automation platform. They all have some form of tracking built in. Form fills, page visits, email clicks. It works well enough for basic lead capture. So your team starts building on it. Custom fields to track conversions. Workflows to sync data to Salesforce. Logic to stitch together touchpoints across channels.
Before long, you've built an entire conversion tracking system inside a tool that was designed to send emails.
That's tracking debt. You've invested years of effort building and maintaining conversion tracking on a platform that was never purpose-built for it. And now you're stuck with it.
The Tools Are the Problem
Marketing automation platforms are good at what they were built for — nurture campaigns, email sequences, lead scoring, form management. They were not built to be your conversion tracking infrastructure.
But that's exactly what most B2B marketing teams have turned them into.
Even the most capable marketing automation platforms only capture shallow data natively — form fills, email engagement, landing page visits. That's helpful for basic lead capture, but it's nowhere near what you need for real conversion tracking. To get anything meaningful, your team ends up building complex automation workflows, custom field mappings, and manual reconciliation processes on top of a tool that was never designed for this.
Incomplete conversion visibility
Native tracking captures what happens inside the platform's own ecosystem. But the B2B buyer journey doesn't live in one tool. It spans paid media, organic search, social, events, direct traffic, sales interactions, and product usage. Your marketing automation platform sees a fraction of the picture and calls it the whole story.
Client-side tracking that doesn't work for B2B
Most native tracking relies on browser cookies, which were designed for consumer e-commerce — not six-month enterprise sales cycles with multiple stakeholders across different devices and sessions. Cookies expire. People switch browsers. Buying committees involve ten people, not one. Cookie-based conversion tracking systematically underreports what's actually happening.
No account-level intelligence
B2B sells to accounts, not individuals. But marketing automation tools track at the person level. Stitching together what an entire buying committee is doing across channels — and attributing that to a single account's journey — requires logic that these tools were never designed to handle. So your team builds workarounds. Custom objects, workflows, rollup fields. It works until it doesn't.
Fragile integrations with ad platforms
Connecting Google Ads, LinkedIn, Facebook, and other paid channels to your marketing automation tool typically means either native integrations that miss data, or custom-built syncs that break when APIs change. You end up with gaps in your conversion data — clicks that don't match leads, campaigns that can't be tied to pipeline, spend that can't be attributed to revenue.
Delayed and batch-based data
Most homegrown tracking systems rely on scheduled syncs — data that flows in batches, not real-time. By the time your conversion data is reconciled and available, it's hours or days old. Decisions get made on stale information. Campaigns run longer than they should. Budget gets wasted.
Then You Build on Top of the Limitations
Because the native tools can't do it all, your team does what MOPs teams always do: they build.
They manually create automations — dozens, sometimes hundreds of them — to capture conversion events, sync data between platforms, and push touchpoints into Salesforce. They manually create and manage SFDC campaigns to track program membership and tie marketing activity to pipeline. Every new program, every new channel, every new campaign requires someone to manually set up the tracking, build the automation, create the campaign, map the fields, and test the sync.
It's an enormous amount of manual effort just to get data flowing. And even after all that work, the insights are still shallow.
You can see that someone filled out a form or was added to a campaign. But you can't see the full buyer journey. You can't see what happened before the form fill or after the campaign touch. You can't connect the dots across channels, accounts, and time in a way that tells you what's actually driving pipeline.
So you build more. Spreadsheets to reconcile ad platform data with CRM data. Custom scripts to pull conversion events from multiple sources. Scheduled exports that someone has to run and validate. Lookup tables to map campaign names across platforms. Manual UTM management that breaks when someone forgets a parameter.
This manual layer becomes the real conversion tracking system. The marketing automation tool is just one input. The spreadsheets, scripts, automations, and SFDC campaigns your team maintains are what actually produces the numbers leadership sees.
And after all that effort — the manual automations, the campaign creation, the reconciliation, the maintenance — you're still left wanting. The insights are incomplete. The data is shallow. The picture is partial. You've done an enormous amount of work just to get to “not good enough.”
The Knowledge Debt Problem
The deepest cost of tracking debt isn't the tools or the time. It's the knowledge.
The system your team built over years — the custom workflows, the reconciliation logic, the field mappings, the transformation rules — that knowledge lives in the heads of one or two people. It's undocumented. It's built on assumptions that made sense three years ago. It's tied to a tech stack configuration that has since changed.
When one of those people leaves, the knowledge leaves with them.
You're left maintaining a system you don't fully understand, making changes you can't fully predict, and producing numbers you can't fully trust.
You hire someone new. They spend months learning the system. Then they want to rebuild it. Or they leave too.
The debt compounds.
The Symptoms
You probably have tracking debt if:
Your conversion data comes from a patchwork of tools, spreadsheets, and manual processes
You can't confidently answer "which channels are driving pipeline" without hours of reconciliation
Your marketing automation platform is doing things it was never designed to do
Adding a new ad platform or channel to your tracking takes weeks of custom work
One or two people on your team are the only ones who understand how conversion tracking works
Your numbers in Salesforce don't match your numbers in your BI tool
You spend more time maintaining your tracking system than analyzing the data it produces
You know your conversion data is incomplete but you don't know how incomplete
Tracking Is Not Attribution
It's important to be clear: solving your tracking problem doesn't solve your attribution problem. Tracking is the foundation. Attribution is what you build on top of it.
Most attribution systems are running analysis on incomplete, shallow data.
The attribution model might be sophisticated — multi-touch, weighted, time-decay — but if the conversion data feeding it is missing half the buyer journey, the output is meaningless. Garbage in, garbage out.
That's the dirty secret of most attribution platforms. The models look impressive. The dashboards are beautiful. But the underlying tracking data is shallow, cookie-dependent, and full of gaps. You're making budget decisions based on an incomplete picture dressed up in a pretty interface.
Fixing your tracking doesn't give you attribution. But without fixing your tracking first, no attribution system will give you answers you can trust.
Why This Matters Now
The tools to solve this exist today. Purpose-built conversion tracking that captures the full digital buyer journey — across channels, across devices, across accounts — without requiring your team to build and maintain it on top of tools that were never designed for it.
The question isn't whether your homegrown system works. It probably does, mostly. The question is whether it's worth the ongoing cost — the maintenance, the fragility, the knowledge risk, the incomplete data, the time your team spends on plumbing instead of strategy.
Every week you spend maintaining homegrown conversion tracking is a week you're not spending on the work that actually moves the business.
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