Chapter 03 · Bottom Funnel · 10 Workflows
Close more. Retain always.
The most expensive resource in your stack is rep time. These workflows tell you exactly where to spend it.
The uncomfortable truth
When the model disagrees with the rep on deal health, the model is right 93% of the time. Reps are systematically optimistic.
The deal is in motion. What happens in the next 48 hours determines whether it closes — or slips a quarter. Most reps are systematically optimistic: they see what they want to see in the pipeline, and the CRM reflects what they log, not what actually happened in the call. These ten workflows exist to close that gap: deal intelligence first (because you can't sequence correctly on wrong information), then execution, then the post-sale motion that determines whether a closed deal becomes a 130%+ NRR account or a churn risk.
Sales Sequences / Outreach Cadences
The workhorse of the bottom funnel. A sequence is a timed series of steps — auto-send emails, create call tasks, schedule follow-ups — that standardizes the sales process and removes rep discretion from outreach cadence. PPF priorities feed directly into sequence enrollment.
Sequences generate the engagement data — meeting acceptance, email response cadence, call durations — that Deal Health uses to predict which deals are quietly dying before it's too late to intervene.
Sales Deal Health (Close Date Prediction)
Industry-average sales forecast accuracy sits at 60–75% (Gartner). In top-performing deal-intelligence deployments, ML models disagree with rep-submitted forecasts on ~43% of deal-days and are correct 93% of the time vs. rep 3.6% (Clari). Reps systematically inflate close date optimism — the disagreement signal exposes it.
Deal Health tells you when deals are likely to close. Predictive Deal Scoring tells you which ones are actually real — together they separate genuine pipeline from optimistic pipe-padding.
Predictive Deal Scoring (PDS)
ML model predicting the probability each deal closes won. Scores deals on ~50 features including stage progression, close date push history, email engagement intervals, meeting counts, overdue tasks. In top-performing deployments, 71% precision at the 10% threshold surfaces which deals are real and which are pipe-padding (Clari, 2024).
Scoring models see CRM fields. Conversation Intelligence sees what actually happened in calls — the competitor objections, the sentiment shifts, the uncaptured next steps that make the difference between a model and reality.
Conversation Intelligence
Deals are won and lost in actual conversations — not CRM fields. Across 326,000 analyzed sales calls, the average rep talks 60% of the time; closed-won deals converge on a 43% talk / 57% listen ratio (Gong Labs). Call and meeting recording analysis extracts deal signals: competitor mentions, objection patterns, stakeholder sentiment shifts, next-step commitments. These signals feed back into deal scoring, coaching, and pipeline risk.
Deal Pipeline Stage Automation
Auto-trigger workflows when deals enter or leave specific stages. When a deal moves to "Negotiation," auto-create a proposal task. When it moves to "Closed Won," trigger onboarding. Every stage transition triggers the next step, ensuring momentum.
Quote Automation & Approval Chains
Auto-create quotes from deals and route through approval workflows. Standard Approvals use ruleset-driven logic per quote type. Advanced Approvals use multi-step, multi-tier logic for complex deals. Approval chains also protect margin: no rogue discounts without oversight.
Deal Forecasting
AI-based revenue projections for month/quarter end. Models daily sales trends with seasonality and holiday effects. Retrained per portal as more data accumulates. The model outperforms manual rep submissions — and the gap widens as the quarter progresses.
Multi-Agent Deal Orchestration
The frontier: AI that reasons about deals rather than executes fixed rules. The emerging architecture has a Campaign Agent orchestrator dispatching specialized task agents — each owning a specific execution domain (research, outreach writing, risk assessment, forecast updates). Agents inspect deal state, reason across CRM data, email threads, call transcripts, and stakeholder maps, then decide the right next action.
Close Won → Post-Sale Automation
When a deal closes won, trigger the full post-sale chain: create onboarding task → assign CSM → trigger welcome email → sync to ERP. Automated 30/60/90-day check-ins surface upsell signals while the relationship is warm. Top-quartile public B2B SaaS companies sustain 120–130%+ Net Revenue Retention (Bessemer State of the Cloud 2024) — in the Loop era, post-sale is the growth engine.
Contract & Renewal Automation
Auto-create renewal quotes when contracts approach renewal dates. Automation detects upcoming renewals, generates quotes from current contract terms, applies applicable legal terms automatically, and routes through approval. Teams targeting top-quartile NRR (130%+, per Bessemer 2024) cannot afford manual renewal processes at any volume.
What it means
120%+ NRR means existing customers expand faster than others churn. The deal isn't done at close — it's done when the customer is growing and referring. Post-sale automation is the NRR defense mechanism.