Identifying Gaps Between CRM Updates and Customer Interactions

Dylan M. · 2025-12-12T04:57:30.552Z

Curious to get the group’s take on this: What’s the biggest gap you see between what’s written in CRM vs what’s actually happening in customer emails & meetings? Examples I’ve heard from CROs this week: • “Next step scheduled” but no reply for 8 days • Deal marked as Commit but zero multi-threading • AE says “champion is strong” but champion hasn’t replied since last week What’s the #1 “unexpected risk” pattern you see in your org? Would love to compare notes.❤️

Identifying Gaps Between CRM Updates and Customer Interactions | RevGenius

7 comments

· Sorted by Oldest

Manuel H.
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#1 unexpected risk pattern: Relying on AEs manually updating a CRM. First, nobody wants to do it, it’s time consuming, and relies on people remembering.
Manuel H.
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Second, it’s often very unreliable even if done due to rep recall, personal opinions, happy ears, etc.
Manuel H.
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I’ve found that if automate all the data capture and have ML evaluate your deals (and customers), you end up with much more accurate risk projections
Marylou Tyler
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CRM entries record intent. Buyer behavior reveals truth. And most clients still treat CRM entries vs. buyer behavior as the same signal. A diagnostic I like to run: :: Where does your CRM show progress while buyer signals show decline? :: Which behaviors (not fields) predict risk? :: What would change if every micro-signal triggered an action instead of relying on rep memory?
Dylan M.
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Manuel H. Spot on, Manuel. 'Happy ears' is exactly the pattern we're seeing too. The manual entry isn't just time-consuming; it's fundamentally biased. We're finding that when you automate the capture (looking at metadata stagnation directly), the 'risk projection' often contradicts the rep's forecast by 2-3 weeks. Curious - if you automate capture, is there a specific 'behavioral signal' (like multi-threading gaps) that you trust more than others?
Dylan M.
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Marylou Tyler Marylou, this distinction between 'Intent' (CRM) vs 'Truth' (Behavior) is brilliant. I might have to frame this on our office wall. We are actually building exactly that 'diagnostic' you mentioned — automating the detection of that specific divergence where CRM says 'Stage 4' but buyer signals (metadata) act like 'Closed Lost'. I'd love to learn more about how you currently run that diagnostic manually. Are you looking at specific 'micro-signals' (like calendar invites declining) or more broad patterns? Your framework is exactly what we are trying to productize.
😀
Kristina M.
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Biggest one I keep hearing: the data just doesn't get logged in the first place. Rep finishes call. Knows the budget, timeline, next steps. But 3 calls later it's fuzzy. They type something. Move on. CRM says one thing, reality is another. Not because reps are lazy. Just too many calls, not enough time to log properly. Curious if you see that too or mostly the "logged but wrong" problem?

Manuel H.
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·
#1 unexpected risk pattern: Relying on AEs manually updating a CRM. First, nobody wants to do it, it’s time consuming, and relies on people remembering.
Manuel H.
·
·
Second, it’s often very unreliable even if done due to rep recall, personal opinions, happy ears, etc.
Manuel H.
·
·
I’ve found that if automate all the data capture and have ML evaluate your deals (and customers), you end up with much more accurate risk projections
Marylou Tyler
·
·
CRM entries record intent. Buyer behavior reveals truth. And most clients still treat CRM entries vs. buyer behavior as the same signal. A diagnostic I like to run: :: Where does your CRM show progress while buyer signals show decline? :: Which behaviors (not fields) predict risk? :: What would change if every micro-signal triggered an action instead of relying on rep memory?
Dylan M.
·
·
Manuel H. Spot on, Manuel. 'Happy ears' is exactly the pattern we're seeing too. The manual entry isn't just time-consuming; it's fundamentally biased. We're finding that when you automate the capture (looking at metadata stagnation directly), the 'risk projection' often contradicts the rep's forecast by 2-3 weeks. Curious - if you automate capture, is there a specific 'behavioral signal' (like multi-threading gaps) that you trust more than others?
Dylan M.
·
·
Marylou Tyler Marylou, this distinction between 'Intent' (CRM) vs 'Truth' (Behavior) is brilliant. I might have to frame this on our office wall. We are actually building exactly that 'diagnostic' you mentioned — automating the detection of that specific divergence where CRM says 'Stage 4' but buyer signals (metadata) act like 'Closed Lost'. I'd love to learn more about how you currently run that diagnostic manually. Are you looking at specific 'micro-signals' (like calendar invites declining) or more broad patterns? Your framework is exactly what we are trying to productize.
😀
Kristina M.
·
·
Biggest one I keep hearing: the data just doesn't get logged in the first place. Rep finishes call. Knows the budget, timeline, next steps. But 3 calls later it's fuzzy. They type something. Move on. CRM says one thing, reality is another. Not because reps are lazy. Just too many calls, not enough time to log properly. Curious if you see that too or mostly the "logged but wrong" problem?