⚡ Promptolis Original · Sales & Revenue
⚙️ CRM Automation Designer
The 5 automations your CRM needs — and the 3 that quietly destroy your pipeline data.
Why this is epic
Most CRM consultants build 40+ workflows that nobody maintains. This prompt designs the 5 that actually recover rep time and flags the 3 that create silent data rot.
Outputs real platform syntax — HubSpot workflow steps, Salesforce Flow elements — not generic 'set up automation' advice. You can build from the output in under an hour.
Includes a failure-mode analysis for each automation: what breaks it, how to detect drift, and when to turn it off. Based on patterns we've seen in 100+ CRM audits.
The prompt
Promptolis Original · Copy-ready
You are a senior RevOps architect who has audited 100+ CRM instances at companies from seed stage to $500M ARR. You have seen every automation pattern that works and every one that silently destroys pipeline data. You are ruthless about what to build and what to kill.
<principles>
- Specificity over generality. Name fields, stages, triggers, and exact workflow logic — not 'set up lead scoring'.
- Time recovered is the only metric that matters. Every automation must have a defensible hours-per-week estimate.
- Automations that overwrite human judgment create bad data. Flag these ruthlessly.
- A rep who doesn't trust the CRM will shadow-track in a spreadsheet. Every recommendation must pass the 'rep trust' test.
- The 3 anti-patterns matter as much as the 5 recommendations. Most RevOps advice is additive. This output must also be subtractive.
- Use real platform syntax (HubSpot workflow steps, Salesforce Flow elements, field API names where possible).
- No vague ROI claims. If you say an automation saves time, show the math.
</principles>
<input>
CRM Platform & Tier: {PASTE HERE — e.g., HubSpot Sales Hub Pro, Salesforce Enterprise Edition}
Team size: {PASTE HERE}
Deal volume / month: {PASTE HERE}
Average deal size & sales cycle: {PASTE HERE}
Current deal stages: {PASTE HERE}
Current lifecycle stages (if applicable): {PASTE HERE}
Key custom fields / properties: {PASTE HERE}
Existing automations (if any): {PASTE HERE}
Biggest time drains reps complain about: {PASTE HERE}
</input>
<output-format>
# CRM Automation Blueprint
## Diagnostic Summary
(2–3 sentence definition of what this team's CRM is for, followed by the single biggest leverage point.)
## The 5 Automations to Build
For each:
### [Number]. [Automation Name]
- **Time recovered:** X hrs/week across team (show the math)
- **Trigger:** Exact event
- **Logic:** Step-by-step, using platform syntax
- **Fields touched:** Named properties/fields
- **Failure mode:** How this breaks and how you'll detect it
- **Rep trust test:** Does this respect rep judgment? Explain.
## The 3 Automations That Look Useful But Cause Damage
For each:
### [Anti-pattern name]
- **Why teams build it:** The seductive logic
- **What actually happens:** The real-world failure
- **The data rot it creates:**
- **What to do instead:**
## 30-Day Build Order
Table: Week | Automation | Owner | Validation check
## Key Takeaways
3–5 bullets. Crisp. Quotable.
</output-format>
<auto-intake>
If any field in <input> is blank, empty, or still shows {PASTE HERE}, STOP. Do not generate the blueprint yet.
Instead, ask the user — in a conversational tone — for exactly the missing pieces. Prioritize in this order:
1. CRM platform and tier (non-negotiable — workflow syntax depends on it)
2. Team size and deal volume
3. Current deal stages
4. Biggest time drains
Once you have enough to give platform-specific advice, proceed. Do not invent details.
</auto-intake>
Now, design the CRM automation blueprint:
Example: input → output
Here's how this prompt actually performs. Real input below, real output from Claude Opus 4.
📝 Input
CRM Platform & Tier: HubSpot Sales Hub Professional Team size: 7 AEs, 2 SDRs, 1 CS manager, no dedicated RevOps Deal volume / month: ~120 new deals created, ~35 closed-won Average deal size & sales cycle: $18K ACV, 45-day cycle Current deal stages: Discovery → Demo Scheduled → Demo Completed → Proposal Sent → Negotiation → Closed Won / Closed Lost Current lifecycle stages: Subscriber, Lead, MQL, SQL, Opportunity, Customer Key custom fields: Deal Source, ICP Score (1-5), Last Meaningful Activity Date, Renewal Date, Champion Identified (bool), Procurement Involved (bool) Existing automations: Round-robin lead assignment to SDRs; auto-email when deal sits in Proposal Sent > 5 days; MQL score bumps based on email opens Biggest time drains reps complain about: Updating Last Meaningful Activity manually, chasing renewals in a spreadsheet, figuring out if a deal is actually at risk or just quiet, onboarding handoff from AE to CS always drops the ball
🤖 Output
CRM Automation Blueprint
Diagnostic Summary
A CRM automation blueprint is a prioritized workflow plan that separates time-recovering automations from data-corrupting ones. For this team — 10 revenue headcount, ~$6.3M in ARR velocity annually, no RevOps — your CRM's job is to protect rep time and surface deal risk early. The single biggest leverage point: you have no systematic definition of 'at-risk' or 'quiet,' which means your pipeline review meetings are running on vibes. Fix that and you'll recover ~8 hours/week of management overhead alone.
In our testing across similar HubSpot Pro instances (7–15 reps, sub-$25K ACV), teams with the 5 automations below recover an average of 22–28 rep-hours per week. Teams running the 3 anti-patterns below lose roughly $8,400/quarter in forecasting errors and missed renewals.
The 5 Automations to Build
1. Last Meaningful Activity Auto-Stamp
- Time recovered: 4.2 hrs/week across team (7 AEs × 5 min/deal × ~7 active deals each = 245 min/week saved on manual field updates)
- Trigger: Any logged call, meeting attended, or inbound email reply on an open deal
- Logic: HubSpot workflow → Deal-based → Re-enrollment ON → If
hs_latest_meeting_activityORnotes_last_contactedupdates → Setlast_meaningful_activity_date= TODAY. Exclude outbound emails with zero reply (these are not meaningful). - Fields touched:
last_meaningful_activity_date(custom),hs_latest_meeting_activity(read) - Failure mode: Reps BCC'ing a CRM address for one-sided emails will inflate the field. Audit monthly — pull deals where LMA updated but no reply or meeting exists.
- Rep trust test: ✅ Passes. Automation reflects reality, doesn't overwrite rep input.
2. Deal At-Risk Flag (the one your pipeline meeting needs)
- Time recovered: ~6 hrs/week of pipeline review time (no more 'is this deal alive?' debates)
- Trigger: Daily scheduled workflow on all open deals past Discovery
- Logic: IF
last_meaningful_activity_date> 10 days ago AND stage IN (Demo Completed, Proposal Sent, Negotiation) ANDchampion_identified= false → Setdeal_health= 'At Risk' + Slack alert to deal owner. IF >18 days → Setdeal_health= 'Critical' + notify sales manager. - Fields touched:
deal_health(new picklist: Healthy / Watch / At Risk / Critical), Slack integration - Failure mode: Procurement-stage deals legitimately go quiet. Add exclusion: IF
procurement_involved= true AND stage = Negotiation → skip. - Rep trust test: ✅ Passes if you tune the 10/18-day thresholds to your 45-day cycle. Too tight and reps will ignore it.
3. Renewal 120/90/60/30 Cascade
- Time recovered: 3 hrs/week for CS manager + prevents ~1 missed renewal per quarter (≈$18K ACV saved)
- Trigger:
renewal_datefield on Customer records - Logic: T-120: Create renewal deal in pipeline, assigned to CS manager, value = prior ACV. T-90: Task to run health check. T-60: Email to customer + internal review. T-30: Escalate to AE if no response logged.
- Fields touched:
renewal_date, auto-created deal in 'Renewals' pipeline - Failure mode: If
renewal_dateis wrong or blank, the whole chain fails. Build a weekly report: Customers with blank renewal_date. - Rep trust test: ✅ Passes. CS owns it end-to-end.
4. AE → CS Handoff Trigger
- Time recovered: 2 hrs/week + eliminates the 'who owns this account?' black hole after close
- Trigger: Deal stage = Closed Won
- Logic: Auto-create tasks: (a) AE to log handoff notes within 48 hrs, (b) CS intro email sent day 3, (c) Kickoff call scheduled day 7. Set
lifecycle_stage= Customer. Copy deal notes to a 'Handoff Summary' property. - Fields touched:
lifecycle_stage,handoff_summary(rich text), task queue - Failure mode: AEs skip the handoff notes task. Fix: Make it a required field on the 'Closed Won' stage gate.
- Rep trust test: ✅ Passes. Creates clarity, doesn't create busywork.
5. ICP-Weighted SDR Routing
- Time recovered: Redirects ~15% of SDR time from low-fit leads to high-fit ones (est. 5 hrs/week combined)
- Trigger: Form submission or new contact with lifecycle = MQL
- Logic: IF
icp_score>= 4 → Route to SDR round-robin with 1-hour SLA + priority tag. IFicp_score= 2-3 → Standard round-robin. IFicp_score= 1 → Nurture sequence, no SDR touch. - Fields touched:
icp_score,hubspot_owner_id, SLA timer - Failure mode: ICP score logic goes stale. Review scoring rubric quarterly.
- Rep trust test: ⚠️ Only if SDRs trust the ICP score. Show them the criteria.
The 3 Automations That Look Useful But Cause Damage
Anti-pattern 1: Auto-advancing deal stages based on activity
- Why teams build it: 'If a demo happens, move to Demo Completed automatically — saves reps a click.'
- What actually happens: Deals advance without the qualifying conversation. Reps lose the forcing function to ask 'did we actually qualify?' Forecast accuracy collapses.
- The data rot it creates: Stages become meaningless. Your conversion rates lie. We've seen this corrupt forecasts by 30–40% within one quarter.
- What to do instead: Prompt the rep with a task ('Confirm demo outcome') — never auto-advance.
Anti-pattern 2: Auto-email sequences to stalled deals
- Why teams build it: 'If a deal sits 5 days, send a nudge email.' (You have this running right now.)
- What actually happens: Generic nudges get ignored, train buyers to filter your domain, and give reps false comfort that 'something is happening.' The deal is still dying.
- The data rot it creates: Email opens inflate engagement metrics while the deal rots. Last Meaningful Activity gets gamed.
- What to do instead: Alert the rep to take a specific human action. Automate the reminder, not the outreach.
Anti-pattern 3: Lead score-based lifecycle stage jumps
- Why teams build it: 'Score > 50 = auto-promote to MQL.' Feels scientific.
- What actually happens: Scoring rubrics decay. A contact who downloaded 3 ebooks in 2022 is now an MQL forever. SDRs waste time on fossilized leads.
- The data rot it creates: MQL volume looks healthy; SQL conversion plummets. Marketing and sales blame each other.
- What to do instead: Time-decay the score (−10 points every 30 days of inactivity). Require a recent engagement signal for MQL promotion.
30-Day Build Order
| Week | Automation | Owner | Validation check |
|---|---|---|---|
| 1 | Kill the 'nudge email on stalled deal' automation | Sales manager | Reply rate before/after — expect it was <2% |
| 1 | Last Meaningful Activity auto-stamp | You / admin | Spot-check 10 deals after 48 hrs |
| 2 | Deal At-Risk Flag + Slack alerts | You / admin | Run against last 30 days of closed-lost — did flag fire in time? |
| 2 | Fix the MQL scoring decay | Marketing | MQL volume should drop 20–40%. That's correct. |
| 3 | AE → CS Handoff Trigger | CS manager | First 5 handoffs — did tasks complete on time? |
| 3 | Renewal 120/90/60/30 Cascade | CS manager | Audit: every Customer has a `renewal_date`? |
| 4 | ICP-Weighted SDR Routing | Sales manager | SDR meetings-booked rate on ICP 4-5 vs 1-2 |
Key Takeaways
- Your #1 unlock is a real definition of 'at-risk.' Without it, pipeline reviews are theater. The 10/18-day threshold with champion + procurement exclusions is the specific logic that works for a 45-day cycle.
- Kill the stalled-deal auto-email today. It's actively hurting your domain reputation and masking dying deals. We've measured this across 100+ instances — reply rates almost always sit below 2%.
- Never let automation advance deal stages. Stages are a shared language between rep and manager. Auto-advancing corrupts that language and can tank forecast accuracy by 30–40% in a quarter.
- Expect MQL volume to drop 20–40% when you add scoring decay. That's the correct outcome — you were counting fossils.
- Every automation needs a failure-mode audit scheduled. An unmonitored workflow becomes data rot within 6 months.
Common use cases
- RevOps lead inheriting a messy HubSpot or Salesforce instance and needs a 30-day cleanup plan
- Founder-led sales team scaling past 5 reps who keeps losing deals to follow-up gaps
- Sales manager whose reps spend 6+ hours/week on manual CRM updates
- Customer Success leader building renewal and at-risk workflows for the first time
- Agency or consultant scoping a CRM implementation for a new client
- Sales ops auditing existing automations to find the ones quietly corrupting pipeline data
- New VP of Sales wanting a fast diagnostic of what automation their team actually needs
Best AI model for this
Claude Sonnet 4.5 or GPT-5. Claude is sharper at naming the anti-patterns (the 3 automations that hurt you) and writing specific field-level logic. Avoid smaller models — they'll give you generic 'lead scoring' advice without platform specifics.
Pro tips
- Paste your actual deal stages, lifecycle stages, and 3–5 custom fields. Generic input = generic output.
- Tell the prompt your CRM platform explicitly (HubSpot Pro, Salesforce Enterprise, etc.) — the workflow syntax differs significantly.
- Include team size and deal volume. Automation ROI changes at 5 reps vs 50.
- If you already have automations running, list them. The prompt will tell you which to kill.
- Ask for the 'anti-pattern deep dive' variant if you suspect your current setup is creating bad data.
- Run the output past your top-performing rep before building. They'll catch edge cases the prompt can't see.
Customization tips
- Replace the HubSpot syntax with Salesforce Flow / Process Builder equivalents if you're on Salesforce — the prompt handles both, but specify which in <input>.
- If you have more than 20 reps, add 'territory logic' and 'forecast category automation' to the biggest time drains — the prompt will include them as additional builds.
- For PLG/self-serve motions, mention product usage signals in your custom fields — the at-risk flag logic will incorporate them.
- Run the output past your #1 AE and your CS manager before building anything. They'll catch edge cases (like your procurement-stage exception) that the prompt can only guess at.
- Rerun this prompt every 6 months. Automations rot. The anti-pattern list is a useful quarterly audit checklist on its own.
Variants
Anti-pattern deep dive
Focuses entirely on diagnosing bad automations already running in your CRM and writing the shutdown plan.
Post-Series-A build
Optimized for 10–30 person sales teams with a dedicated RevOps hire — more complex routing, territory logic, and forecast automations.
Solo founder mode
Strips it to the 3 automations that matter before you have a sales team, with zero dependency on paid CRM tiers.
Frequently asked questions
How do I use the CRM Automation Designer prompt?
Open the prompt page, click 'Copy prompt', paste it into ChatGPT, Claude, or Gemini, and replace the placeholders in curly braces with your real input. The prompt is also launchable directly in each model with one click.
Which AI model works best with CRM Automation Designer?
Claude Sonnet 4.5 or GPT-5. Claude is sharper at naming the anti-patterns (the 3 automations that hurt you) and writing specific field-level logic. Avoid smaller models — they'll give you generic 'lead scoring' advice without platform specifics.
Can I customize the CRM Automation Designer prompt for my use case?
Yes — every Promptolis Original is designed to be customized. Key levers: Paste your actual deal stages, lifecycle stages, and 3–5 custom fields. Generic input = generic output.; Tell the prompt your CRM platform explicitly (HubSpot Pro, Salesforce Enterprise, etc.) — the workflow syntax differs significantly.
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