Deployment Brief
Start with a weekly stale-deal report showing last touch, stage age, missing next step, owner, recommended action, and approval status.
Difficulty
High
Revenue impact
Medium
Operational impact
High
Risk level
Medium
When it runs
Evidence in
What AI prepares
- stale opportunity report
- recommended action
- owner task or manager review item
- close-date, stage, or loss-reason exception
- measurement event for stale count, revived deals, closed-lost cleanup, and forecast correction
Decision rules
- Flag an opportunity when stage age, last activity, or close date violates the team standard.
- Recommend revive, update, reassign, close-lost review, or manager review based on evidence.
- Route stage, amount, forecast, owner, close date, and loss reason changes to review.
- Do not trigger customer outreach from stale data without owner approval.
- Block cleanup when there is recent activity not reflected in the CRM.
Human approval point
What stays human
- Do not close opportunities automatically.
- Do not move stage or forecast without owner review.
- Do not send revive outreach without review.
- Do not invent loss reasons or next steps.
Quality and stop gates
- Staleness rules differ by stage.
- Every stale deal shows last touch and next step.
- Forecast-impacting changes require review.
- Owner tasks are specific.
- Loss reasons are not guessed.
- Manager review is logged.
How it is measured
- Stale opportunity count.
- Missing next-step rate.
- Close-date correction rate.
- Revived opportunity count.
- Closed-lost cleanup count.
- Forecast correction count.
Systems involved
Worked example
consulting firm · sales manager
a pipeline review shows several proposal-stage deals with no next step and close dates that passed last month
What the owner reviews
- stage, stage age, last activity, close date, next step, owner, amount, forecast, and revive or loss reason
- stale-deal report, recommended action, owner task, manager review item, and a flag for any forecast-impacting change
Workflow Dataset Record
Deployment evidence and duplicate boundary
This section is generated from the enriched workflow dataset. It is designed for pilot planning, not as validated outcome evidence.
Buyer Problem
Open opportunities remain in pipeline after buyer activity stops, next steps expire, or close dates become unrealistic.
Economic Logic
Cleanup improves forecast and pipeline trust by forcing owner review on deals with stale evidence.
Baseline Metric
stale_opportunity_disposition_rate
Share of stale opportunities reviewed and dispositioned as next action, revise, pause, or close.
Source system: CRM opportunities, activity history, stage history, forecast categories
Minimum Viable Pilot
- Duration
- 30 days
- Sample
- All opportunities stale by stage age or no-activity rule in one pipeline
- Owner
- Sales manager
- Threshold
- 90% of stale opportunities receive a next action, forecast update, or close/pause reason.
Unique Workflow Test
Compare stage age, activity age, close date pushes, next-step status, owner disposition, and forecast update.
Duplicate Guard
Keep separate from stage progression monitoring. Stale cleanup acts on stale deals; stage monitoring continuously watches stage movement and rule exceptions.
Not Ready If
- Activity logging is unreliable.
- Stage-age thresholds are undefined.
- Managers do not review stale-deal dispositions.
Claim level: Pilot-shaped. Sources support workflow mechanics and pilot design unless field evidence is attached.
HubSpot Knowledge Base: Stage Calculated Properties
Stage entry, exit, current-stage time, and cumulative-stage time can be used to measure pipeline progression.
Salesforce Help: Managing Pipelines with Pipeline Inspection
Pipeline inspection can combine opportunity changes, deal health insights, activity counts, scores, and configurable summary metrics.
Salesforce Help: Forecasting Concepts
Forecasts use opportunity pipeline categories such as Pipeline, Best Case, Commit, Closed, and Most Likely.
Keep moving
Where this workflow connects next
A useful AI build rarely lives on one page. Check the surrounding workflow, the decision rule, and the deployment path before you commit budget.
Workflow group
CRM Operations
Compare the nearby workflows that usually break before or after this one.
OpenSales pillar
AI Sales Workflow Deployment
See how sales teams can use AI for pipeline briefs, meeting prep, follow-up, account plans, and stalled deals.
OpenDecision tool
Automate vs. keep manual
Check which parts should stay human before this workflow touches customers or records.
OpenIndustry fit
Browse industries
See how this workflow changes by revenue model, buyer urgency, delivery risk, and customer handoff.
OpenService path
Business Process Automation
Turn repeated internal work into a reviewed process people can actually run.
OpenSales review
Pressure-test this sales workflow
Bring the sales motion, the source evidence, and the number this workflow should move.
OpenTL;DR
Stale deals make the pipeline look healthier than it is. The workflow should flag old deals and recommend action, while managers approve stage, forecast, amount, and close-date changes.
What is stale opportunity cleanup?
Stale opportunity cleanup is the operating process for finding open deals that no longer reflect real pipeline status.
Who is this workflow for?
- Companies where sales, marketing, service, and reporting all depend on the CRM.
- Teams preparing to use more AI automation but still fighting duplicate, stale, incomplete, or inconsistent records.
- Owners who need cleaner data without giving automation permission to damage customer history.
- Service businesses, agencies, SaaS companies, consultants, and professional firms where every missed follow-up or bad handoff has revenue impact.
What breaks in the manual process?
The manual process breaks when the CRM is cleaned as a one-time project instead of an operating routine:
- deals sit open with no next step;
- close dates roll forward without evidence;
- forecast includes deals the owner has not touched;
- lost deals stay open because no one wants to close them;
- revive outreach happens without checking whether the deal is real.
The goal is not a prettier database. The goal is a CRM that can support routing, follow-up, reporting, forecasting, and safe automation.
How does the AI-enabled process work?
The workflow checks CRM records against approved standards, prepares a correction or review queue, shows the evidence, and separates safe suggestions from changes that need approval.
AI can identify patterns faster than a person reviewing records one by one. It should still stop before changing ownership, consent, activity history, deal stage, amount, forecast, customer commitments, or any field that affects routing and reporting.
What does this look like in practice?
Example scenario: A pipeline review shows several proposal-stage deals with no next step and close dates that passed last month. The workflow checks stage, stage age, last activity, close date, next step, owner, amount, forecast, and revive or loss reason. It prepares stale-deal report, recommended action, owner task, manager review item, and a flag for any forecast-impacting change.
What decision rules should govern this workflow?
- Flag an opportunity when stage age, last activity, or close date violates the team standard.
- Recommend revive, update, reassign, close-lost review, or manager review based on evidence.
- Route stage, amount, forecast, owner, close date, and loss reason changes to review.
- Do not trigger customer outreach from stale data without owner approval.
- Block cleanup when there is recent activity not reflected in the CRM.
What are the implementation steps?
- Trigger: A scheduled pipeline hygiene review finds open opportunities with old activity, outdated close dates, missing next steps, or stage age beyond the team standard.
- Inputs collected: opportunity stage, stage age and last activity, close date, next step and due date, owner, amount and forecast category, revive reason or loss reason, manager approval rule.
- AI/system action: The system checks the record against the data standard, prepares the suggested output, and flags conflicts or protected fields.
- Human review point: The opportunity owner or sales manager reviews closing deals, changing stage, changing forecast, changing amount, moving close dates, reassigning owner, and triggering customer outreach.
- Output generated: stale opportunity report, recommended action, owner task or manager review item, close-date, stage, or loss-reason exception, measurement event for stale count, revived deals, closed-lost cleanup, and forecast correction.
- Follow-up or next action: The owner approves, rejects, revises, merges, assigns, updates, blocks, or logs the record based on the evidence.
Required inputs
- opportunity stage.
- stage age and last activity.
- close date.
- next step and due date.
- owner.
- amount and forecast category.
- revive reason or loss reason.
- manager approval rule.
Expected outputs
- stale opportunity report.
- recommended action.
- owner task or manager review item.
- close-date, stage, or loss-reason exception.
- measurement event for stale count, revived deals, closed-lost cleanup, and forecast correction.
Human review point
The opportunity owner or sales manager reviews closing deals, changing stage, changing forecast, changing amount, moving close dates, reassigning owner, and triggering customer outreach.
Risks and stop rules
Stop when the source of truth is unclear, the match evidence is weak, a protected field would change, the update affects revenue or routing, activity history could be lost, consent could be overwritten, or the record is tied to an active customer or opportunity.
Best first version
Start with a weekly stale-deal report showing last touch, stage age, missing next step, owner, recommended action, and approval status.
Advanced version
Add source-priority rules, confidence bands, protected-field policy, recurring exception review, import prevention, sync monitoring, and manager dashboards after the first version has been reviewed on real CRM records.
Related workflows
Measurement plan
- Stale opportunity count.
- Missing next-step rate.
- Close-date correction rate.
- Revived opportunity count.
- Closed-lost cleanup count.
- Forecast correction count.
FAQ
What is stale opportunity cleanup?
Stale opportunity cleanup identifies open deals with old activity, outdated close dates, missing next steps, or stage age beyond the team standard.
What should AI recommend for stale opportunities?
AI can recommend update, revive, reassign, close-lost review, manager review, or owner follow-up based on CRM evidence.
What should stay under human review?
Closing deals, changing stage, changing forecast, changing amount, moving close dates, reassigning owners, and outreach should stay under review.
What is the simplest first version?
Start with a weekly stale-deal report showing last touch, stage age, missing next step, owner, recommended action, and approval status.
How should stale opportunity cleanup be measured?
Track stale count, missing next steps, close-date corrections, revived deals, closed-lost cleanup, and forecast corrections.
Related Workflow Group
AI Workflows for CRM Operations
Compare this workflow against nearby operating problems before choosing the first build. The group shows what usually breaks together, what evidence is needed, and where review still matters.
View Workflow GroupRelated Workflows
Further Reading
AI workflow readiness checklist
A field report on checking workflow clarity, evidence, ownership, and measurement before implementation.
