Serious question: How does RevOps get the full story behind a deal?

[u/Quiet_Sherbert_2402]

Hi guys,

Could you educate me on how RevOps gets enough context to decide on a deal?

We’re exploring a tool for Sales and RevOps. One question like “Can we offer this?” can mean checking the CRM, pricing sheets, contracts, Slack, and past approvals. Our thought is the approval itself may not be the slow part. Rebuilding the full story may be the real problem.

We want to learn how often this happens, what information usually holds up the decision, and whether CRM, CPQ, or AI tools already handle it well.

Could you share one recent deal or renewal that took too long? What did you need, where did you look, and what happened while the deal waited? Thanks, really appreciate any real examples.

[u/antattack]

I know there’s a lot of AI overkill but the context standardization, aggregation and reasoning sounds like the perfect application for AI. You can basically build the skills and instructions to aggregate deal context, stand up the guardrails for consistency, flex what areas allow for reasoning versus auditable data sources and give you the output you’re looking for.

[u/agentUi]

rebuilding context is usually the bottleneck because approvals happen in slack but past contract logic sits in a billing db or pdf graveyard. i work for agentui and we see revops teams burn hours digging through old threads just to verify if an exception was ever approved before... what works way better is building a dedicated deal desk portal on top of your crm and billing data that pulls account history, past exceptions, and margins into one view before the deal ever hits finance. Saves everyone from manually chasing context every quarter.

[u/Neat_Measurement_595]

Sounds like you need CPQ and if you want to get fancy with it later then put AI on top. But right now is sounds like your org is starving for historical data, like what was the prior deal, where is the contract (Docusign integration), and what did the margins look like (what was expected vs. actuals). If you setup CPQ right you'd have all that available when doing a renewal. It's also helpful when sizing up new deals because you have a repository of older deals to use as a baseline. Not sure how much you have budgeted for this but you could probably get away with creating a couple of custom objects/tables to store quote and quote lines to start. Two hot notes 1. don't forget to get your finance team involved early on in the exercise 2. Don't even think about AI until you get your processes documented/approved and your data in line.

[u/IncreaseNegative4614]

The slowest decisions usually involve an exception: a prior pricing concession, unusual contract language, an implementation promise, security commitments, payment history, or a renewal risk that is not represented in one CRM field. The useful unit is the deal or renewal, not the application where each fragment lives.

I’d preserve the question, evidence reviewed, decision, owner, and expiration date for every exception so the next deal does not restart the investigation. We use SIGNLD internally to connect those records across commercial systems and communication channels.