If you rely on Demandbase reporting to make decisions, you know the pain when the numbers don’t add up. Maybe your leads in Salesforce don’t match what Demandbase shows, or website visits are way off from Google Analytics. This guide is for marketers, ops folks, and anyone tired of chasing phantom data issues. Let’s break down how to actually spot and fix these discrepancies, without the runaround.
Step 1: Get Clear on What "Discrepancy" Means
Before you start poking around, decide what you’re actually trying to match. Are you talking about:
- Web traffic (sessions, pageviews, unique users)?
- Account identification (which companies showed up)?
- Engagement metrics (clicks, time on site, conversions)?
- Pipeline or revenue attribution?
A lot of headaches come from comparing apples to oranges. For example, Demandbase ([demandbase.html]) uses its own IP-based identification, which won’t match up to your CRM’s contact-based records. Write down exactly what numbers you expect to match—and why.
Pro tip: Don’t try to reconcile everything at once. Pick one metric and one time frame to start. Otherwise, you’ll drown in details.
Step 2: Identify Where Differences Actually Show Up
There are three main spots where things get weird:
- Between Demandbase and your CRM (like Salesforce/HubSpot)
- Between Demandbase and your web analytics (Google Analytics, Adobe, etc.)
- Between different Demandbase reports or dashboards
Start by pulling the same report from each system for the same date range. Screenshot or export the numbers. Highlight what doesn’t match—don’t just eyeball it.
What to Ignore
- Small gaps (under 5–10%) between platforms are normal. Different platforms count things differently and update at different times.
- Don’t waste time trying to get “perfect” alignment. It won’t happen.
Step 3: Check Your Demandbase Setup
A ton of issues come down to setup problems. Run through this checklist:
-
Is the Demandbase tag firing on all pages?
Use browser tools or Tag Assistant to check. If the tag isn’t firing, you’ll miss visits. -
Is your CRM integration working?
Check for recent sync errors in Demandbase’s integration logs. If you see a backlog, fix it before comparing numbers. -
Are you filtering out internal traffic?
Sometimes Demandbase tracks your own employees. Make sure you’re excluding your company’s IP ranges. -
Are data sources mapped correctly?
If you’re pulling in custom fields or using custom dimensions, make sure they’re mapped the same way in both systems.
What matters:
If you spot a setup issue, fix it and re-run your reports. No point troubleshooting old data if your pipeline is broken.
Step 4: Dig Into Data Definitions
This is where most people trip up. Demandbase defines things differently than your other tools.
- “Account” in Demandbase means a company identified by IP or cookies. In your CRM, it might be a record with a domain name. Not always the same.
- “Visitor” in Demandbase is not the same as a “user” or “session” in Google Analytics.
- Attribution windows and lookback periods are often different. A 30-day window in one tool might be 7 days in another.
How to fix:
Find the documentation for each metric in both Demandbase and your other tools. Make a table showing how each platform defines the key terms. If the definitions don’t match, don’t expect the numbers to match.
Step 5: Run a Controlled Test
Still stuck? Set up a simple test to trace data through the systems. Here’s how:
- Pick a very short time window (e.g., one day).
- Generate a handful of test visits or conversions—ideally from a known company/IP.
- Watch how those visits appear (or don’t) in Demandbase, your CRM, and your web analytics.
Document every step. If you can’t trace a specific visit across the systems, you’ve found a disconnect.
Pro tip:
Use incognito browsers and clear cookies to avoid getting lumped into internal or returning visitor segments.
Step 6: Check for Data Processing Delays
Demandbase doesn’t always update in real time. Some data can lag by hours or even a day, especially with integrations. So:
- Double-check data refresh schedules for all your tools.
- Wait at least 24 hours before comparing the latest numbers.
- Don’t panic if today’s data looks off; check again tomorrow.
Step 7: Look for Known Platform Limitations
Here’s some honest truth: Demandbase has some quirks that can’t be fixed with user effort. For example:
- IP-based identification isn’t perfect. Companies with remote workers, VPNs, or shared office buildings might get misattributed.
- Ad blockers and privacy tools can prevent Demandbase from tracking visits.
- Account list size limits and API rate limits can cause partial data loads.
Check Demandbase’s support docs or community forums for known issues. Sometimes the problem isn’t on your end.
Step 8: Fix What You Can—And Document the Rest
- If you found a real setup or mapping problem, fix it, then rerun your numbers.
- If the issue is a known platform quirk, make a note of it and adjust how you report.
- For gaps you can’t close, document the difference and your best guess at the cause. This helps avoid endless debates later.
What not to do:
Don’t fudge the numbers to make them match. If there’s a gap, be upfront about it.
Step 9: Communicate Clearly With Stakeholders
Don’t leave your team in the dark. Share:
- What you found (and what you didn’t)
- What you fixed
- What will probably never match (and why)
- How you’ll monitor discrepancies going forward
If you’re not sure, say so. People appreciate honesty over made-up certainty.
Step 10: Set Up Ongoing Monitoring
Discrepancies will come back. Build a habit of regular checks:
- Create a simple dashboard comparing key metrics across systems.
- Set up alerts for major swings (not minor blips).
- Review integrations and data mapping at least once a quarter—especially after platform updates.
Real Talk: What Actually Works (and What Doesn’t)
Worth your time:
- Regularly checking integrations and tag firing
- Mapping definitions across platforms
- Controlled tests with known data
Often a waste:
- Chasing minor percentage differences
- Expecting Demandbase, your CRM, and web analytics to ever fully agree
- Blaming “bad data” without checking your own setup first
Keep It Simple (And Don’t Chase Your Tail)
Data discrepancies are a fact of life when you’re dealing with complex tools like Demandbase. The trick isn’t to make everything match perfectly—it’s to know why things are different, fix what you can, and move on. Don’t let perfect be the enemy of good. Document what you find, keep your team in the loop, and revisit your setup every so often. That’s usually enough to keep reporting headaches from turning into migraines.