It's common to see data differences between CRM, ad management platforms, and GA4. Below are the most common reasons.
Different Attribution Models
Each platform attributes conversions differently. For example:
Ads Managment (Google Ads, Meta Ads, Programmatic, etc): Typically rely on both click and view-through conversions.
Google Analytics (GA4): Uses data-driven or last-click attribution by default.
CRM: Usually attributes conversions based on the last recorded interaction in its system.
Different Attribution Windows
Aside from actual attribution model differences, the attribution windows can also differ. For example:
Ads Management: Use attribution windows like 7-day or 30-day click / 1-day view by default.
Google Analytics: Can track over longer or customizable periods.
CRMs: Often rely on when a lead is entered rather than when an ad interaction happened.
This means a platform may credit a conversion to an ad interaction that happened days or weeks earlier, while the CRM records it when the lead is manually entered or tracked.
Example: Let's look at an example of how these attribution model and window discrepancies could play out for a customer's journey. Say a user is browsing Instagram and clicks on an ad. Now, they're in the funnel and interested, but not ready to buy. 3 days later they receive a remarketing ad from a Display campaign. Instead of clicking it, they decide to wait another day and search the company on Google. They click the Paid Search ad and make the purchase.
These 3 total touch points would all result in conversions for their respective platforms. But why?
Meta will count the conversion in the platform because it was within the 7-day click window.
Programmatic will count the conversion because it was within the view-through conversion window.
Google will count the conversion because of the last click.
Now, you have 3 conversions (1 on each platform), but technically, only 1 actual customer/purchase in your CRM.
Missing or Untracked Data
CRMs don’t always capture every lead or interaction accurately, especially from platform-native lead forms or call tracking tools are not properly integrated:
Ads Management: Leads generated directly on these platforms may not sync automatically with your CRM.
Call Extensions & Click-to-Call Ads: Calls tracked in Google Ads might not be recorded in your CRM unless integrated with a call tracking system.
Misattributed Data
Attribution is rarely perfect, and many conversions may appear as direct traffic in your CRM or analytics when they were actually influenced by ads. In the same example from above, let's say instead of Googling the business as the last touchpoint, the user enters their business directly in their browser's search bar. Because they've already been to the site via an IG ad, the URL autopopulates and the user clicks enter, then eventually makes the purchase. Since the CRM records only the final interaction, it may attribute the conversion to direct traffic because of the last click, even though the initial touchpoint was the ad. This makes it important to look at assisted conversions, view through conversions, and multi-touch attribution to fully understand the impact of your marketing efforts.
Data Processing & Reporting Delays
Platforms often use estimated or delayed data, while CRMs rely on real-time entries. This can lead to temporary mismatches, especially if conversions are still being attributed or processed on the platform side. To be as accurate as possible, make sure you're doing the following:
Align Attribution Models Where Possible: Ensure your CRM’s attribution logic is as close as possible to the platforms you’re using.
Check Platform-Specific Lead Syncing: If you rely on on-platform lead forms, make sure they are properly integrated with your CRM.
Use UTM Parameters & Tracking Integrations: This can help better align CRM data with ad platforms and analytics tools.
Understand That No Data Source is 100% Perfect: Expect some level of discrepancy and focus on trends over exact one-to-one matching.