SALES OPERATIONS // FREE LIVE DEMO
Deal Health Predictor
THE PROBLEM
Deals that are quietly dying — stalled replies, shrinking meeting attendance, a champion who's gone quiet — don't get flagged until the close date slips and it's too late to save them.
9h → 2h
Weekly optimisation time (production)
PROVEN IN PRODUCTION
Part of the Deal Closing Squad →
No pitch — just a plan.
Describe your deals' recent behaviour — I'll board them by stage, glow the ones that are quietly dying, and tell you which are worth saving.
Execution trace — recorded run (this agent's real pipeline)
Reading the recent activity timeline
ok
Identifying specific warning signs
ok
Scoring deal health against risk patterns
ok
Recommending a save or let-go action
ok
Time to assess deal risk
~15 min → ~15 sec
projected
Weekly optimisation time (production)
9h → 2h
real · anonymized
Discovery
Gulf Modular Interiors
AED 180K
Replied yesterday, second stakeholder joined
⚠ Falcon Logistics
AED 95K
No reply in 11 days, single-threaded
Proposal
Al Reem Clinics
AED 240K
Proposal opened 3×, follow-up call booked
⚠ Marina FitOut Co
AED 310K
Proposal unanswered 9 days, champion quiet
Desert Rose Retail
AED 150K
Scope negotiation active, healthy cadence
Negotiation
⚠ Oryx Facilities
AED 420K
Champion missed last 2 calls, attendance shrinking
Pearl Hospitality Group
AED 275K
Legal review in progress, on track
Pipeline health
62%
Confidence below 0.80 — in production this result routes to a human for review before any action.
Why these deals are flagged
Falcon Logistics: 11 days of silence on a single-threaded deal — no secondary stakeholder to fall back on if the contact has gone cold. Marina FitOut Co: the proposal has sat unanswered for 9 days and the champion has stopped initiating contact — stalled replies at this stage usually mean lost internal support, not a busy calendar. Oryx Facilities: meeting attendance is shrinking and the champion has missed 2 consecutive calls — the biggest deal on the board is quietly dying while its stage label still says Negotiation. None of these show up in stage-and-close-date CRM views; all three show up in behaviour.
WHAT IS DEAL HEALTH PREDICTOR?
An AI deal health predictor reads a deal's recent activity pattern — response lag, missed meetings, champion silence, a stalled proposal — and scores how at-risk the deal actually is, names the specific warning signs behind that score, and recommends either a concrete save action or a graceful let-go, instead of a deal quietly dying until the close date slips.
HOW IT WORKS
Deal risk almost never shows up as one dramatic event — it shows up as a pattern of small signals accumulating: replies getting slower, a champion skipping calls, a proposal sitting unanswered. Individually each signal is explainable (people get busy); together they form a recognisable risk pattern that most CRMs don't score because they track stage and close date, not behaviour trend. This agent is prompted to read the pattern as a whole and to resist the temptation to soften the score for a deal that still looks fine on paper (right stage, right close date) but is behaviourally dying underneath.
The recommendation deliberately isn't always 'try harder' — for a genuinely cold pattern (champion gone silent, no secondary stakeholder), the agent recommends a graceful let-go over the pipeline, because chasing a dead deal costs more than it saves and inflates a forecast that then has to be walked back later.
You are a deal-health risk analyst for B2B sales. Given recent deal activity patterns and stage context, produce EXACTLY these blocks in this order: (1) a 'table' with columns Stage, Deal, Value, Signal — the FIRST column must be the pipeline stage (e.g. 'Discovery', 'Proposal', 'Negotiation') so rows group into kanban columns; 6-8 rows spread across 3-4 stages; prefix the Deal cell of every at-risk deal with '⚠ ' (flag 2-3 deals, and only for real behavioural signals: response lag, meeting no-shows, champion gone silent, stalled proposal). (2) a 'scoreGauge' labeled exactly 'Pipeline health' scoring overall pipeline health 0-100 — do not soften a genuinely at-risk score to be optimistic. (3) a 'metricCards' block with labels exactly 'Deals tracked', 'Deals at risk', 'Value at risk'. (4) a short 'copyBlock' titled 'Why these deals are flagged' naming the concrete signal behind each ⚠ deal. Output ONLY a JSON array of typed blocks matching the OutputBlock union — no prose outside the JSON. The wider pipeline board is an illustrative synthetic sample used to demonstrate the pattern — never present the other, non-input deal names or AED values as real; only the flagged-deal reasoning should draw on the activity pattern actually described.USE CASES
Weekly pipeline risk sweep
Run every open deal past a certain stage through the agent weekly to catch quiet decay before it shows up as a slipped close date.
Forecast-call red-flag prep
Before a forecast review, flag which 'commit' deals actually show at-risk behavioural signals underneath the stage label.
Handoff between reps
When a deal changes owners, the new rep gets an honest health read instead of inheriting an optimistic status update.
Renewal / expansion risk
The same activity-pattern logic applies to at-risk renewals — a quiet champion pre-renewal is the same signal as one pre-close.
RESULTS & BENCHMARKS
Time to assess deal risk
projected (modeled)
Weekly optimisation time (production)
real, anonymized
GET THIS RUNNING ON YOUR BUSINESS
Want Deal Health Predictor solving this for you?
This runs in production today, not a mockup. Tell me your case on a free 30-minute call, or hire the whole system for $999/mo.
No pitch — just a plan.
FAQ
Common questions
What signals does the agent look for?
Response lag, missed or declined meetings, champion silence, and stalled proposals — individually explainable events that together form a recognisable at-risk pattern.
Does it always recommend pushing harder to save the deal?
No — for a genuinely cold pattern it recommends a graceful let-go instead, since chasing a dead deal costs more than it saves and inflates a forecast that later has to be corrected.
Can it connect to my real CRM activity data?
The live demo works from a described activity pattern you paste in; a production integration would pull the same signals directly from CRM activity logs.
RELATED AGENTS
Built by Hammad Yousuf — AI Marketing Automation Engineer, 540K+ YouTube subscribers.
See the production missions these agent patterns run in, or hire the whole system.