The GTM Engineer bridge.
Ivo opened a Director, GTM Tech and Automation role with a 90-day target that includes GTM trusts the data. That is a forecast problem before it is an ops problem. I run the GTME function while you hire so your AEs stop reconciling SFDC by hand and your number stops moving between Monday and Friday.
Forecast confidence is a CRM workflow problem, not a rep skill problem.
When product usage events do not reach the account record and stage definitions drift across reps, the forecast you take to the board is a weighted average of inconsistent inputs. AEs feel it, they hedge, and the number you commit is the number you can defend, not the number that is actually there. The FTE you are hiring fixes this in quarter two. I fix it in quarter one so your next board update is clean.
Three things only an internal builder can fix.
AEs reconcile renewal data by hand
Consumption signals live in product analytics. AEs copy them into SFDC notes the week before a renewal call, if at all. That is not a forecast input, that is a guess.
Stage taxonomy drifts rep to rep
Without enforced definitions, what a rep calls Stage 3 and what your dashboard calls Stage 3 are different things. The pipeline coverage ratio you report is fiction.
Order form friction kills late-stage velocity
Manual order form assembly adds days to closed-won. Those days show up as slippage in your forecast, and the rep gets blamed for a process tax.
A forecast layer your AEs can defend and your board can trust.
- Weeks 1 to 2
Audit forecast inputs end to end
Walk the path from product event to SFDC field to dashboard. Output the reconciliation tax your AEs pay weekly and where the forecast leaks.
- Weeks 3 to 4
Wire consumption and threshold alerts to AEs
Agent writes usage metrics onto the account record and pings the AE before a renewal turns red. Stage definitions written down and enforced by required-field logic.
Salesforce in plain English, shipped in 4 weeks.
AssetWatch leadership wanted natural-language access to pipeline, accounts, demo outcomes, and work orders without filing a RevOps ticket for every question. I shipped a custom GPT in ChatGPT Enterprise that translates English to SOQL and queries production Salesforce live. Two Knowledge files made it work: an auto-generated schema catalog covering 26 objects and 3,800+ fields, plus a hand-curated semantic layer encoding AssetWatch tribal knowledge, so "who owns this deal" returns the Solution Architect and "deal size" returns ARR, not the raw admin fields. Read-only, leadership-facing, 4 weeks. Tyler's team owns the maintenance now.
Same play I would run for Ivo. Different stack, same fixed-fee discipline.
$15,000, fixed. 6 weeks. One invoice.
- Signal architecture
- Account list and buying-committee map
- Sequence build, live send, and deliverability infrastructure
Documentation and handoff included, not billed. If volume justifies it after the bridge, $25,000 / 90-day retainer extends the system. Your call, not mine.
Reply if your forecast moves more than you want it to.
Send me a sentence on how confident your AEs are in their pipeline today. I will reply within a day with a 1-page scope and an honest read on whether this fits.