Business use cases: lead, sales, support
Apply your 5‑day toolkit to real business scenarios. Steal these templates, adapt them, and deliver value immediately.
🎯 From tools to business impact
📌 You have the superpowers. Now where to use them?
Days 1‑5 gave you a complete automation toolkit: prompt engineering, Zapier, Make, OpenAI API, and a full lead system. Today we zoom out and look at the most common, high‑ROI business patterns. You'll see how to mix and match the tools for each scenario.
🏢 Three departments, endless automations
Sales
Lead qualification, follow‑up emails, meeting scheduling, CRM enrichment.
Support
Ticket categorization, auto‑responses, sentiment analysis, Slack alerts.
Operations
Data entry, report generation, invoice processing, cross‑app syncing.
📈 Sales playbook – 3 ready templates
1. Hot lead alert + personalized video
Scenario: A prospect fills a "contact sales" form. You want immediate notification and a custom intro.
Tools: Zapier + OpenAI API (Day4) + Gmail
Flow:
- Trigger: Typeform / Gravity Forms (new entry).
- OpenAI API: Generate a 2‑sentence icebreaker based on their message (Day1 prompt).
- Gmail: Send email to sales rep with lead details + icebreaker.
- Slack: Post to #sales-leads with a button to schedule meeting (Calendly).
2. Meeting no‑show recovery
Scenario: A scheduled meeting (Calendly) was missed. Automate a graceful follow‑up.
Tools: Make.com + OpenAI API + Gmail (draft)
Flow:
- Trigger: Calendly "event cancelled" or 5 min after start if not started.
- OpenAI: Generate a soft, re‑scheduling email (tone: understanding, not pushy).
- Gmail: Create draft for sales rep to review & send.
- Sheets: Log missed meeting for reporting.
3. Lead scoring from email inquiries
Scenario: General inbox (hello@) receives inquiries. Automatically score leads based on content.
Tools: Gmail trigger (Day2) + OpenAI API (Day4) + Sheets (Day2) + Slack (Day3)
Flow: (This is Day5 simplified)
- Gmail: Watch for new emails.
- OpenAI: Classify as "hot/warm/cold" with reason.
- Sheets: Log all.
- Slack: Only hot leads posted to #sales.
Reuse Day5 qualifier prompt.
🎧 Support playbook – 3 ready templates
1. AI‑powered ticket triage
Scenario: Support emails arrive at support@. Auto‑categorize and set priority.
Tools: Gmail → OpenAI (classify) → HelpScout / Zendesk (or Sheets)
Prompt (Day1): "Read this support email. Return JSON with: category (billing/tech/account), priority (high/medium/low), and a 1‑line summary."
2. Sentiment alert for angry customers
Scenario: Detect negative sentiment and notify a senior support agent immediately.
Tools: Make.com + OpenAI API + Slack
Flow:
- Trigger: Gmail (new email to support).
- OpenAI: Sentiment analysis (positive/neutral/negative).
- Router: if negative, post to #urgent-support with email snippet.
- Always log to sheet.
3. Auto‑reply for common questions
Scenario: Frequently asked questions (password reset, pricing) get instant answers from a knowledge base.
Tools: Zapier + OpenAI API + Gmail
Flow:
- Trigger: Gmail with label "faq".
- OpenAI: "Answer this question politely based on our FAQ: [insert FAQ text]. If unsure, say 'I'll connect you with a human.'"
- Gmail: Send reply.
Safety: Always add "If this doesn't help, a human will reply within 24h".
⚙️ Operations playbook – 3 ready templates
1. Invoice data extraction
Scenario: Invoices arrive as PDF attachments. Extract amount, due date, vendor.
Tools: Make.com + OpenAI API (vision if needed) + Google Sheets + accounting software
Flow:
- Trigger: Gmail (invoice label).
- Extract attachment, send to OpenAI (with prompt: "extract JSON: total, due_date, vendor").
- Add row to "Invoices to pay" sheet.
- Slack alert: "New invoice ${amount} from ${vendor} due ${date}".
2. Daily report generator
Scenario: Every morning, gather data from multiple sources and email a summary.
Tools: Make.com (scheduler) + OpenAI + Gmail
Flow:
- Scheduled trigger (8 AM daily).
- Get new leads from CRM (API), new support tickets, sales figures.
- OpenAI: "Summarise these stats in a friendly 3‑bullet update for the team."
- Email to team.
3. CRM enrichment from email signatures
Scenario: When someone emails, extract their job title, company, phone from signature and update CRM.
Tools: Gmail trigger + OpenAI API + HubSpot / Pipedream
Prompt: "Extract from this email signature: name, job title, company, phone. Return JSON."
🧠 Choosing the right tool for the job
- Simple, linear workflows (≤5 steps).
- Quick integration between two apps.
- You want pre‑built OpenAI actions (no HTTP).
- Example: Typeform → OpenAI → Sheets.
- Complex logic: routers, iterators, aggregators.
- Full HTTP control (custom API calls).
- Need error handling & data transformation.
- Example: multi‑path lead router with AI.
Blueprint templates (copy & adapt)
Sales: Lead → Slack
Zapier: Gmail (label "lead") → OpenAI (summarize) → Slack (message)
Support: Negative → urgent
Make: Gmail → OpenAI (sentiment) → router → Slack (urgent) + Sheets
Ops: Invoice parser
Make: Gmail (attachment) → OpenAI vision (extract) → Sheets → Slack
These are not theoretical – they are directly built from Days 1‑5 skills.
⚠️ Pitfalls to avoid (real business lessons)
- Automating a broken process: Fix the manual process first, then automate.
- No error handling: If API fails, do you have a fallback? (Make: error routes).
- Over‑automating: Not every email needs a reply. Use filters (Day2).
- Ignoring privacy: Be careful with sensitive data in AI calls (anonymize if needed).
💰 Quick ROI calculator
Example: Lead qualification (Day5)
- Time saved per lead: 5 minutes (reading + typing).
- Leads per month: 200.
- Hours saved: 200 × 5 / 60 = 16.7 hours.
- Hourly cost $50 → monthly saving $835.
- AI cost: ~$0.01 per lead × 200 = $2.
- ROI = 417x 🚀
Use this formula for any use case.
📚 Real-world case studies
Day 6: You've applied automation to real business cases
✔ 9 ready‑to‑use templates (sales, support, ops)
✔ Decision framework: Zapier vs Make
✔ ROI calculator to justify your work
✔ Avoid common pitfalls
✔ Reused all skills from Days 1‑5 in new combinations
From prompt engineer to automation architect.
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