NOTQIN Customer Engagement Playbook
The end-to-end process for taking a Moroccan industrial prospect from cold contact to signed pilot to paying annual contract. Combines stakeholder management, lean startup, PMBOK, change management, and pricing strategy into one operational document.
Overview: The 5-Stage Funnel
STAGE 1 — QUALIFY (Days 1–7)
Is this the right factory at the right moment?
STAGE 2 — DIAGNOSE (Days 8–21)
Show them their own problem in their own numbers.
STAGE 3 — PILOT PROPOSAL (Days 22–30)
A bounded, low-risk first engagement with clear success criteria.
STAGE 4 — PILOT DELIVERY (Months 1–3)
Deploy, catch the first real anomaly, generate the first CBAM report.
STAGE 5 — CONVERSION (Month 3)
Convert the pilot to an annual contract using pilot results as evidence.
Stage 1 — Qualify
The Ideal Customer Profile (ICP)
| Dimension | Qualifier | Disqualifier |
|---|---|---|
| Sector | Textile, cement, steel, agri-food, chemicals, mining | Pure services, retail, no production assets |
| Size | 50–2,000 employees | < 30 employees (too small) / > 5,000 (too slow, too political) |
| Energy exposure | Energy > 8% of COGS | Energy < 5% (low ROI urgency) |
| Export profile | Exports to EU or EU-bound supply chain | Domestic-only (no CBAM urgency) |
| Geography | Morocco (Casablanca, Settat corridor, Tanger, Safi, Beni Mellal) | Outside Morocco (out of scope for now) |
| Decision-maker access | You can get to the Director or Plant Manager | Gatekeeper blocks all access |
| Digital readiness | Has internet connectivity at factory floor | No connectivity at all (rare but exists) |
Qualifying Questions (for first call or LinkedIn message reply)
- “What percentage of your COGS is energy today?”
- “Do you export to EU markets or supply to EU-bound manufacturers?”
- “Are you currently tracking your carbon emissions per ton of production?”
- “Do you have any IoT or monitoring systems on your production floor today?”
- “Who in your organization is responsible for energy management?”
Signal to proceed: answers 1 (>8%), 2 (yes), 3 (no), 5 (specific person named) → book a site visit.
Target Account List (from vault research)
Tier 1 — CBAM urgency, already in pipeline:
- YNNA Steel (CBAM Urgent overlay in vault)
- Sonasid (CBAM Pilot overlay in vault)
- OCP Safi (Pilot overlay in vault)
Tier 2 — Good ICP, needs outreach:
- Lesieur Cristal (agri-food, Casablanca)
- LafargeHolcim Maroc (cement, high energy exposure)
- Managem Tizert (mining, remote deployment challenge)
- Tanger Med ecosystem manufacturers (automotive corridor)
Tier 3 — Strong ICP but longer cycle:
- Maroc Telecom data centers (energy + cooling)
- OCP Jorf Lasfar (large but long procurement)
- Renault Tanger suppliers (EU supply chain → CBAM pressure)
Stage 2 — Diagnose
Never pitch before you diagnose. The diagnosis IS the pitch.
The 90-Minute Discovery Visit
Goal: leave with enough information to write a 1-page ROI calculation and a draft pilot scope.
Preparation:
- Research the factory (CGEM directory, LinkedIn, news)
- Know their sector’s average energy cost benchmark (AMEE data)
- Know the CBAM declaration timeline for their product category
- Bring a physical notebook (shows you’re listening, not presenting)
- Prepare 3 reference stories (anomaly caught, energy saved, CBAM report generated)
Discovery questions — in order:
Operations:
- “Walk me through a typical production day — what runs, when, for how long?”
- “Which machines consume the most energy?”
- “How do you currently detect machine problems — before or after they fail?”
- “What was your last major unplanned downtime event? What did it cost?”
Energy:
- “What’s your monthly electricity bill with ONEE?”
- “Do you have peak/off-peak scheduling in place?”
- “Who reads the energy meters today — and what do they do with the data?”
- “Has AMEE ever audited your facility?”
CBAM / Compliance:
- “Are you aware of the EU CBAM regulation and how it affects your export prices?”
- “Has any EU buyer asked you for carbon footprint documentation?”
- “What’s your current process for tracking CO₂ emissions per ton?”
Organization:
- “Who would be the day-to-day contact if we deploy a monitoring system?”
- “Who needs to approve a technology investment of MAD 50,000–150,000/year?”
- “Has your company tried any IoT or smart monitoring before? What happened?”
What to listen for:
- 🟢 Specific numbers (energy bill amount, last downtime cost) → they track their pain
- 🟢 Named internal champion (“our energy engineer Khalid handles that”) → pilot operator identified
- 🟡 “We’ve tried something before and it didn’t work” → understand why, address directly
- 🔴 “The boss needs to decide” + no access to boss → disqualify or nurture slowly
HighByte-Inspired Use-Case Discovery Patterns
Source: HighByte website scrape 2026-05-27 use-case pages for predictive asset maintenance, first-pass yield, electronic batch reporting, and OEM cloud services. Use these as market-proven problem patterns, not as copied messaging.
| Pattern | Moroccan prospect translation | Discovery questions | Pilot evidence output |
|---|---|---|---|
| Predictive asset maintenance | Plants need to merge historian/process data with new vibration, temperature, lubrication, or power-quality signals before they can predict failures. | ”Which asset failure stops the line most often?” “Do you already collect vibration or motor-current data?” “Where does maintenance history live: CMMS, Excel, paper, or memory?” “Can you correlate a downtime event with process values from the hour before failure?” | Asset-health evidence object: asset, signal window, anomaly score, maintenance action, downtime avoided estimate, operator confirmation. |
| First-pass yield | Auto/aero/textile/food prospects need current quality results linked to machine and process context, not delayed manual reports. | ”How long after production do you know first-pass yield?” “Which test stand, CMM, lab, or inspection data is still manually combined?” “Can you trace scrap/rework back to machine, shift, material lot, or operator without rebuilding an Excel file?” | FPY evidence stream: product/order, test result, machine cycle window, quality status, scrap/rework reason, customer-facing trend. |
| Electronic batch reporting | Pharma, food, chemicals, and regulated batch producers need step-level batch evidence across PLCs, SCADA, MES, LIMS, historians, and manual checks. | ”What must be proven for one batch before release?” “Which batch fields are still hand-entered?” “How long does root-cause analysis take after a batch quality issue?” “Can you reconstruct equipment, lot, operator, and quality checks for one batch today?” | Batch evidence pack: batch ID, material lots, equipment/line used, process steps, timestamps, quality checks, exceptions, release-ready export. |
| OEM cloud services | Moroccan machine builders and integrators can turn machine data into service revenue, but only if data is normalized before cloud upload. | ”Do you support machines after installation?” “Could you offer uptime or maintenance reporting as a paid service?” “Are each customer’s machines sending different tag structures?” “How much cloud data are you paying to move that nobody uses?” | Machine-service payload: standardized asset model, minimal high-value telemetry, alert/event history, service ticket trigger, cloud-cost baseline. |
Use these patterns to choose the first pilot wedge:
- If the prospect has urgent downtime pain, lead with asset-health evidence before CBAM.
- If the prospect exports auto/aero parts, lead with first-pass-yield and scorecard evidence.
- If the prospect is food/pharma/chemical batch production, lead with batch traceability and release evidence.
- If the prospect is an integrator or machine builder, lead with OEM service payloads and recurring service revenue.
Do not turn the first meeting into an architecture discussion. The architecture only matters after the prospect names the evidence chain they cannot produce today.
Post-Visit: The 1-Page ROI Brief (send within 48 hours)
SMARTEX ENERGY INTELLIGENCE — PILOT VALUE ESTIMATE
[Factory Name] | [Date] | Confidential
CURRENT SITUATION
Monthly energy spend: MAD [X] /month
Estimated energy waste (7%): MAD [0.07 × X] /month
Last unplanned downtime cost: MAD [Y] (annualised: MAD [Y/3] /month)
CBAM exposure (estimated): MAD [Z] /year → MAD [Z/12] /month
TOTAL MONTHLY PAIN: MAD [X×0.07 + Y/3 + Z/12] /month
SMARTEX PILOT PROPOSAL
Pilot duration: 3 months
Scope: [N] machines, IEIA + Core deployment
Expected energy savings (5%): MAD [0.05 × X] /month
CBAM data readiness: Full traceability by Month 3
Anomaly detection: ≥ 80% precision target
PILOT INVESTMENT
One-time setup + hardware: MAD [setup cost]
Monthly pilot fee: MAD 5,000 /month
Total 3-month pilot: MAD [setup + 15,000]
EXPECTED ROI
Monthly value generated: MAD [savings + fine avoidance + downtime reduction]
Monthly pilot cost: MAD 5,000
Net monthly gain: MAD [value − 5,000]
Full-year projection (if continued): MAD [annual net gain]
Payback period: [N] months
NEXT STEP
30-minute call to review these numbers and agree pilot scope.
Stage 3 — Pilot Proposal
The Pilot Charter Document
Send this as a formal PDF after the ROI brief is accepted in principle. It replaces a vague “let’s try it” handshake with a document a CFO can approve.
SMARTEX PILOT CHARTER Project: NOTQIN IEIA Pilot — [Factory Name] Date: [Date] | PM: Ahmed Ben Ahmed | Sponsor: [Factory Director Name]
PURPOSE Deploy NOTQIN IEIA to monitor [N] machines at [Factory Name], validate energy anomaly detection at ≥ 80% precision, and produce CBAM-ready carbon traceability data for [product category] production. 3-month bounded engagement.
OBJECTIVES (SMART)
- Install sensors on [N] machines and establish live data feed by Week 2
- Achieve ≥ 80% anomaly detection precision by end of Month 2
- Reduce monitored line energy consumption by ≥ 3% by end of Month 3
- Deliver CBAM-compliant carbon data report by end of Month 3
SCOPE In scope:
- Physical sensor installation: [N] machines (looms / compressors / motors — specify)
- Cloud deployment: NOTQIN Core + IEIA (InfluxDB + Grafana + Claude API agent)
- Monthly energy report (3 reports)
- CBAM carbon data export (tCO₂ per ton, Scope 2)
- Weekly anomaly alert digest (WhatsApp + email)
- Final pilot review presentation
Out of scope:
- PLC reprogramming or DCS integration
- Factory network infrastructure changes
- Legal CBAM filing (client responsibility)
- Training beyond 2 onboarding sessions
MILESTONES
| Milestone | Target Date |
|---|---|
| M1: Contract signed, hardware ordered | Week 0 |
| M2: Sensors installed, data flowing to InfluxDB | Week 2 |
| M3: IEIA deployed, first anomaly detected | Week 4 |
| M4: Model tuned, 80% precision validated | Week 8 |
| M5: CBAM report generated, Month 3 report delivered | Week 12 |
| M6: Pilot review, conversion decision | Week 13 |
SUCCESS CRITERIA The pilot is considered successful if ALL of the following are met:
- Anomaly detection precision ≥ 80% on validation set
- ≥ 1 real energy anomaly identified and confirmed by plant operator
- CBAM carbon data report generated and reviewed by client
- Energy consumption on monitored line decreased by ≥ 3%
INVESTMENT
| Item | Cost |
|---|---|
| Hardware (sensors + edge gateway) | MAD [X] — one-time |
| Pilot monthly fee (3 months) | MAD 5,000 × 3 = MAD 15,000 |
| Total pilot investment | MAD [X + 15,000] |
Hardware cost is credited toward Year 1 annual contract if client converts.
RISKS
| Risk | Probability | Impact | Mitigation |
|---|---|---|---|
| Factory network incompatibility | Medium | High | Network assessment in Week 1 before sensor install |
| Sensor procurement delay | Low | Medium | Order hardware at contract signing |
| Client data access delays | Medium | High | Sign data access authorization at contract signing |
| IT Manager blocks deployment | Medium | High | Include IT Manager in Week 1 kickoff meeting |
CONVERSION PATH If pilot succeeds: standard annual contract at MAD [12,000–20,000]/month depending on scope expansion. If pilot fails on defined criteria: no obligation to continue, hardware remains with client.
APPROVALS Client Sponsor: _________________ Date: _______ Ahmed Ben Ahmed (NOTQIN): _________________ Date: _______
Handling Objections at This Stage
| Objection | Root cause | Response |
|---|---|---|
| ”Too expensive for a trial” | No urgency or no ROI clarity | Recalculate ROI with their exact numbers. Offer to reduce to 1 production line first. |
| ”We need procurement committee approval” | Large organization, long cycle | Provide full charter + ROI doc formatted for internal presentation. Offer to present to the committee. |
| ”Our IT department needs to approve” | IT Manager is a gatekeeper | Request a 30-min call with IT Manager. Send architecture + security doc (Morocco UNS Standard, TLS MQTT, no data leaves without consent). |
| ”We tried IoT before and it failed” | Bad prior experience | Ask what failed specifically. Address the exact failure mode. Offer a 4-week proof of concept before the full pilot. |
| ”Not the right time, maybe next quarter” | No urgency | ”CBAM reporting starts [date]. To have 3 months of validated data before that, we’d need to start by [date].” |
Stage 4 — Pilot Delivery
Week-by-Week Playbook
Week 1 — Foundation
- Kick-off meeting: Director + Plant Manager + IT Manager + Energy Engineer + Ahmed
- Sign data access authorization (legal)
- Network assessment: connectivity at machine floor, MQTT port open, TLS configured
- Hardware inventory check: all sensors received and tested in lab before site visit
- RACI matrix agreed and signed off
Week 2 — Physical Installation
- On-site installation day (plan for 1 full day per 4 machines)
- Each sensor tested live: MQTT message visible in Mosquitto logs
- InfluxDB ingestion verified: data flowing at 1Hz per machine
- Grafana dashboard provisioned and shared with Energy Engineer
- First WhatsApp message to champion: “Sensors live — you can see [Machine 1] real-time here: [Grafana link]”
Week 3 — First Anomaly Hunt
- IEIA BearingAnomalyJob running, EWMA window configured for this factory’s baseline
- Review first 7 days of data with Energy Engineer — identify any obvious patterns
- CRITICAL: Find the first real anomaly. Even if small. Document it. Share it.
- Format: “Machine 4 (Loom 7) showed abnormal vibration pattern Tuesday 14:00–16:00 correlating with 12% energy spike. Likely belt tension issue. Recommend inspection.”
- Send as WhatsApp + PDF to Director and Plant Manager
- Follow up: did they inspect? what did they find? → This is your proof of concept moment.
Week 4 — IEIA Live
- IEIA FastAPI deployed in production
- Claude API analyst tool configured with factory-specific context (ONEE tariff, machine specs, shift schedule)
- Energy Engineer onboarding session (60 min): how to query IEIA, how to read scenarios, what alerts mean
- Baseline energy consumption documented per machine
Month 2 — Model Tuning
- Review anomaly alerts with Plant Manager: false positives? missed events?
- Retrain/tune anomaly thresholds based on 4 weeks of real data
- Run first monthly energy report: baseline vs. monitored period
- CBAM data mapping: establish CO₂ factor per kWh, calculate Scope 2 per production run
- Monthly review call (30 min) with Director: show the numbers, ask “what surprised you?”
Month 3 — Evidence Generation
- Compile anomaly log: total alerts, confirmed events, false positives, actions taken
- Calculate actual energy savings vs. baseline (methodology: same production volume, different energy)
- Generate CBAM carbon report draft (tCO₂ per ton, Scope 2, period covered)
- Prepare pilot results presentation (see template below)
- Book pilot review meeting with Director at Week 11
Pilot Results Presentation Template
SMARTEX PILOT RESULTS — [FACTORY NAME]
3-Month Summary | Prepared by Ahmed Ben Ahmed
EXECUTIVE SUMMARY
Pilot period: [dates]
Machines monitored: [N]
Anomalies detected: [X] events
Confirmed by plant team: [Y] events (precision: Y/X × 100%)
Energy savings documented: [MAD Z] over 3 months
CBAM data generated: [tCO₂] for [production volume], [period]
WHAT WE FOUND
1. [Specific anomaly: Machine X, date, what it was, what would have happened]
2. [Energy pattern: shift Y runs 15% more energy than shift Z — scheduling opportunity]
3. [CBAM insight: your CO₂ per ton = X tCO₂ vs. sector average Y tCO₂]
FINANCIAL IMPACT
Energy savings (3 months): MAD [A]
Downtime prevented (estimated): MAD [B]
CBAM fine avoidance value: MAD [C] /year
────────────────────────────────────────
Total value generated (3 months): MAD [A+B+C/4]
Pilot investment (3 months): MAD [investment]
────────────────────────────────────────
Net gain (3 months): MAD [value - investment]
Annualized projected net gain: MAD [annual]
SUCCESS CRITERIA REVIEW
[✅/❌] Anomaly detection precision ≥ 80%: [achieved X%]
[✅/❌] ≥ 1 real anomaly confirmed by plant team
[✅/❌] CBAM carbon data report generated
[✅/❌] Energy consumption reduction ≥ 3%
NEXT STEP: Annual Contract
Proposed scope: [all lines / additional lines / add NOTQIN Agent]
Annual investment: MAD [price] /month
Expected annual net gain: MAD [projected]
Stage 5 — Conversion
The Conversion Conversation
Timing: Week 12 of pilot (1 week before pilot ends) Who: Director + Energy Engineer (your champion) Format: In-person at factory (never remote for contract conversations)
Conversation structure:
- Recap results (5 min): show the pilot results doc, let the numbers speak
- Surface the expansion (5 min): “Based on what we found, there are [N] more lines we haven’t touched yet. That’s approximately MAD [X] in additional savings.”
- Present the annual proposal (5 min): one page, three options (Standard / Enterprise / Multi-site)
- Handle objections (10 min)
- Define next step (5 min): “To maintain continuity — you’ve now built 3 months of baseline data — ideally we sign before the pilot end date so there’s no data gap.”
Annual Contract Options
| Option | Price | Scope |
|---|---|---|
| Standard | MAD [12,000–15,000]/mo | Full factory, IEIA + Core, monthly report, email support |
| Enterprise | MAD [20,000–30,000]/mo | Multi-line, CBAM audit support, quarterly review, SLA 99.5%, dedicated CSM |
| Multi-site | Custom | 2+ factories, unified dashboard, consolidated CBAM reporting, volume discount |
Conversion lever: “Hardware cost (MAD [X]) is credited toward your Year 1 contract — you’ve already partially invested.”
If they delay: “We can extend the pilot at MAD 5,000/month month-to-month while you finalize internally. But the 3-month data baseline is your most valuable asset right now — the longer we wait, the less accurate the anomaly model becomes without retraining.”
Ongoing Customer Success (Post-Contract)
Monthly Rhythm
- Day 1 of each month: automated energy report generated by IEIA, sent to Director + Energy Engineer
- Week 1 of each month: Ahmed reviews report, adds commentary, sends summary WhatsApp
- Monthly call (30 min): review anomalies, discuss upcoming maintenance, confirm CBAM data quality
Quarterly Business Review (QBR)
- Energy savings YTD vs. baseline
- Anomaly log and outcomes
- CBAM data status and projection for annual declaration
- Upcoming planned maintenance (integrate with IEIA maintenance logs)
- Expansion opportunity: new lines, new sites, add NOTQIN Physics / NOTQIN Grid
Expansion Triggers
| Signal | Expansion Move |
|---|---|
| Factory adds a new production line | Add line to Core monitoring |
| Factory director mentions sister factory | Multi-site proposal |
| EU buyer requests audited CBAM certificate | Add NOTQIN Agent (regulatory compliance module) |
| Plant manager asks about predictive scheduling | Add NOTQIN Physics (physics-informed ML) |
| Factory is expanding and adding power infrastructure | Add NOTQIN Grid (load forecasting) |
Churn Prevention Signals
| Warning Signal | Response |
|---|---|
| Energy Engineer changes jobs | Immediately onboard new contact, re-do training |
| Director changes or new ownership | Re-establish relationship at top, re-present ROI |
| No anomalies detected for 60 days | Proactively explain: “Quiet period = machines running well. Here’s the baseline data.” |
| CBAM regulation delayed or changed | Reframe value around energy savings alone; adjust reporting module |
| Competitor approaches the factory | Emphasize data continuity: “3 years of your baseline data lives in our system — migration = starting over” |
Stakeholder Communication Templates
Initial LinkedIn Outreach (Cold)
Bonjour [Name],
Je travaille sur NOTQIN, un système de monitoring énergétique industriel
développé pour les usines marocaines exposées au CBAM.
En [month], le règlement CBAM imposera à vos acheteurs européens de déclarer
le carbone intégré dans vos produits. Avez-vous déjà un système pour tracer
votre empreinte CO₂ par tonne produite ?
Si ce sujet est d'actualité chez vous, je serais ravi d'échanger 30 minutes
pour voir si notre approche peut vous être utile.
Bonne continuation,
Ahmed
Post-Visit ROI Brief Email
Objet : NOTQIN — Estimation ROI suite à notre visite du [date]
Bonjour [Name],
Suite à notre échange de [day], j'ai préparé une estimation rapide de la
valeur qu'un pilote NOTQIN pourrait générer pour [Factory Name].
[Attach: 1-page ROI Brief]
Les chiffres sont basés sur votre facture ONEE de MAD [X]/mois et votre
profil d'export EU. Le potentiel de gain mensuel estimé est de MAD [Y].
Je suis disponible [deux créneaux] pour revoir ces chiffres ensemble et
affiner le périmètre d'un éventuel pilote.
Cordialement,
Ahmed Ben Ahmed
[LinkedIn] | [Phone]
First Anomaly Alert (WhatsApp to Champion)
[Factory name] — NOTQIN Alert 🔴
Machine: Loom 7 (Secteur B)
Heure: Aujourd'hui 14h23
Signal: Vibration anormale (+34% vs baseline) + pic de consommation (+12%)
Cause probable: tension courroie / désalignement poulie
Recommandation: inspection mécanique avant prochain shift
Capture Grafana : [link]
Rapport IEIA complet : [link]
À confirmer par votre équipe maintenance. On peut en parler si besoin.
Key Files Referenced
- NOTQIN Core — platform architecture, sensor specs
- NOTQIN IEIA — agent tools, FastAPI, Claude API integration
- NOTQIN Agent — CBAM compliance module
- NOTQIN Pilot Playbook — operational deployment steps
- NOTQIN Ecosystem Map — how modules connect
- Morocco UNS Standard v0.1 — architecture + security doc for IT Manager objection
- Management Frameworks × NOTQIN Customers — theory behind this playbook
- Modern Management/Stakeholder & Risk Management in IT — stakeholder matrix deep dive
- Modern Management/Pricing Strategy for Tech Products — pricing theory
- Modern Management/IT Project Governance & PMBOK — charter and WBS templates
- Modern Management/Digital Transformation Frameworks — Kotter change management
- Target Accounts 2026 — prioritized prospect list
- Client overlays: Overlay — Sonasid CBAM Pilot, Overlay — YNNA Steel CBAM Urgent, Overlay — OCP Safi Pilot, Overlay — Lesieur Cristal, Overlay — Tanger Med, Overlay — Managem Tizert Sparkplug B