# PHT Automated Sales Flow
**Created:** March 11, 2026  
**Goal:** Fully automated prospecting → enrichment → personalized outreach → 3-week follow-up sequence

---

## 🎯 The Complete Flow

```
1. DISCOVERY (Find Companies)
   ↓
2. ENRICHMENT (Company Details)
   ↓
3. CONTACT FINDING (Top 3 Quality/Ops Managers)
   ↓
4. PERSONALIZATION (Custom Email Copy)
   ↓
5. SEQUENCING (Load into Instantly)
   ↓
6. FOLLOW-UP (3 touches over 3 weeks)
```

---

## Step 1: DISCOVERY - Find Target Companies

### Tools:
- **Apify** (Google Maps scraping)
- **Apollo** (company search)
- **Manual databases** (industry directories)

### Criteria:
- Cool rooms with 10+ storage rooms
- Storing: apples, citrus, pears, bananas, or kiwis
- Location: USA, UK, Canada, Australia, NZ, South Africa
- Confirmed CA storage (controlled atmosphere)

### Automation:
```python
# Max runs this weekly/monthly
1. Apify: Search "apple cold storage [region]"
2. Apollo: Filter by industry, size, location
3. Output: CSV of new companies (Name, Domain, Location, Type)
```

### Output Example:
```csv
Company Name,Domain,Country,Fruit Type,Estimated Rooms
ABC Fruit Storage,abcfruit.com,USA,Apples,25
XYZ Cool Rooms,xyzcool.co.za,South Africa,Citrus,15
```

---

## Step 2: ENRICHMENT - Get Company Details

### Tools:
- **Apollo API** (company data)
- **Hunter.io** (email patterns)
- **LinkedIn** (verification)

### Data to Gather:
- Company size (employees)
- Estimated revenue
- LinkedIn URL
- Address
- Phone number
- Email domain pattern (e.g., first.last@company.com)

### Automation:
```python
# For each company from Step 1:
1. Apollo API: Get company profile (size, revenue, LinkedIn)
2. Hunter.io: Get email domain pattern
3. Output: Enriched company CSV
```

### Output Example:
```csv
Company Name,Domain,Employees,Revenue,Email Pattern,LinkedIn,CA Rooms
ABC Fruit Storage,abcfruit.com,50-100,5M-10M,{first}.{last}@,linkedin.com/company/abc,25
```

---

## Step 3: CONTACT FINDING - Top 3 Quality/Ops Managers

### Tools:
- **Snov.io** (best for NZ/AU/global)
- **Hunter.io** (domain search)
- **Apollo** (contact enrichment)
- **LinkedIn Sales Navigator** (manual backup)

### Target Roles (in priority order):
1. Quality Manager / QA Manager
2. Operations Manager
3. Production Manager
4. Technical Manager
5. Facility Manager
6. General Manager (if no specific quality/ops role)

### Automation:
```python
# For each company:
1. Snov.io domain search: company.com
2. Filter results by job title keywords: ["quality", "operations", "production", "technical"]
3. Pick top 3 most relevant contacts
4. Verify emails via Hunter.io
5. Output: Contact CSV with 3 rows per company
```

### Output Example:
```csv
Company Name,Contact Name,Title,Email,Verified
ABC Fruit Storage,John Smith,Quality Manager,john.smith@abcfruit.com,Yes
ABC Fruit Storage,Sarah Jones,Operations Manager,sarah.jones@abcfruit.com,Yes
ABC Fruit Storage,Mike Brown,Production Manager,mike.brown@abcfruit.com,Yes
```

---

## Step 4: PERSONALIZATION - Generate Custom Email Copy

### Tools:
- **Claude API** (via Max)
- **Clay** (optional - for advanced personalization)
- **Custom data points** from enrichment

### Personalization Tokens:
- `{{first_name}}` - Contact first name
- `{{company_name}}` - Company name
- `{{fruit_type}}` - Primary fruit stored (apples, citrus, etc.)
- `{{case_study}}` - Relevant case study (Zespri for kiwis, Stemilt for apples, etc.)
- `{{roi_stat}}` - Custom ROI stat based on room count
- `{{location}}` - Country/region-specific reference

### Email Template Structure:
```
Subject: {{first_name}}, reducing ethylene damage at {{company_name}}

Hi {{first_name}},

I noticed {{company_name}} handles {{fruit_type}} storage in {{location}}. 

[Personalized pain point based on fruit type]

We recently helped {{case_study}} reduce quality claims by 34% using real-time ethylene monitoring across their CA rooms.

{{roi_stat}}

Would a 2-month pilot (10 units, free) at {{company_name}} make sense?

Best,
Jonny Shannon
PostHarvest Technologies
calendly.com/jonny_shannon/30mins
```

### Automation:
```python
# For each contact:
1. Select case study based on fruit type:
   - Apples → Stemilt
   - Citrus → Wonderful Citrus
   - Kiwis → Zespri
   - Bananas → Costa Group
2. Calculate ROI stat based on room count:
   - 10-25 rooms → "Even with 15 rooms, operators save $50K+ annually"
   - 25-50 rooms → "Facilities with 30+ rooms typically see $120K+ in savings"
   - 50+ rooms → "At your scale (50+ rooms), we're seeing $200K+ impact"
3. Generate personalized opening based on location + fruit type
4. Output: Personalized email CSV ready for Instantly
```

### Output Example:
```csv
Email,First Name,Company Name,Subject,Body
john.smith@abcfruit.com,John,ABC Fruit Storage,"John, reducing ethylene damage at ABC Fruit Storage","Hi John,\n\nI noticed ABC Fruit Storage handles apple storage in Washington State..."
```

---

## Step 5: SEQUENCING - Load into Instantly

### Tools:
- **Instantly API**
- **Instantly web interface** (for review)

### Sequence Structure:
**Campaign Name:** PHT - [Region] - [Fruit Type] - [Month Year]

**Email 1** (Day 0): Initial outreach
- Personalized introduction
- Case study reference
- Free 2-month pilot offer
- CTA: Book 30-min call

**Email 2** (Day 3): Value add
- Share relevant resource (case study PDF, ROI calculator)
- No hard ask, just "thought this might be useful"

**Email 3** (Day 7): Social proof
- "Just closed a deal with [similar company]"
- Brief recap of value prop
- CTA: "Worth a quick chat?"

**Email 4** (Day 14): Final follow-up
- "Closing up my outreach on this"
- Last chance framing
- Simple yes/no question

**Email 5** (Day 21): Break-up email
- "Sounds like now isn't the right time"
- Leave door open: "Feel free to reach out when storage season picks up"

### Settings:
- **Send window:** 8am-5pm local time (based on company location)
- **Daily send limit:** 30 per account (5 accounts = 150/day max)
- **Delay between emails:** 2-5 minutes randomized
- **Track opens/clicks:** Yes
- **Auto-stop on reply:** Yes

### Automation:
```python
# Via Instantly API:
1. Create campaign: "PHT - USA Apples - March 2026"
2. Upload contacts CSV (3 per company)
3. Map personalization fields
4. Set sequence timing (Day 0, 3, 7, 14, 21)
5. Activate campaign
6. Output: Campaign URL for monitoring
```

---

## Step 6: FOLLOW-UP - Monitor & Respond

### Tools:
- **Instantly** (auto-follow-ups)
- **Gmail** (reply handling)
- **Calendly** (meeting booking)
- **Close.io** (CRM tracking)

### Response Handling:
1. **Positive reply** → Max flags to Jonny → Jonny books call via Calendly
2. **Out of office** → Instantly auto-pauses, resumes after OOO period
3. **Unsubscribe** → Instantly auto-removes from sequence
4. **Bounce** → Max flags email as invalid, finds replacement contact
5. **No response after 21 days** → Auto-archived, flagged for LinkedIn outreach

### Automation:
```python
# Daily at 8am NZDT:
1. Max checks Instantly inbox
2. Categorizes replies:
   - Meeting booked → Add to Close.io
   - Interested but no meeting → Flag for Jonny follow-up
   - Not interested → Archive
   - Bounce → Find new contact
3. Weekly report: Opens, replies, meetings booked
```

---

## 🔄 Full Automation Schedule

### Weekly (Monday 8am NZDT):
1. Discovery: Find 50 new companies (Apify + Apollo)
2. Enrichment: Get details for all 50
3. Contact finding: Get top 3 contacts for each (150 contacts total)
4. Personalization: Generate custom emails for all 150
5. Load into Instantly: Add to active campaign
6. **Result:** 150 new prospects enter the funnel each week

### Daily (8am NZDT):
1. Monitor Instantly replies
2. Flag positive responses to Jonny
3. Handle bounces (find replacement contacts)
4. Update Close.io with progress

### Monthly:
1. Review campaign performance
2. A/B test subject lines
3. Refresh case studies and messaging
4. Expand to new regions/fruit types

---

## 📊 Expected Results

### Weekly Output:
- **Input:** 50 new companies
- **Contacts:** 150 new prospects (3 per company)
- **Emails sent:** 150 initial + follow-ups
- **Expected reply rate:** 10-15% (15-22 replies/week)
- **Expected meeting rate:** 5-7% (7-10 meetings/week)

### Monthly Output:
- **Input:** 200 companies
- **Contacts:** 600 prospects
- **Meetings booked:** 30-40 per month
- **Pipeline:** $150K-$200K in potential deals

---

## 🛠️ Implementation Checklist

### Phase 1: Setup (Week 1)
- [ ] Get Instantly API key
- [ ] Set up Snov.io account (50 free searches/month)
- [ ] Create email templates with personalization tokens
- [ ] Build automation script (Python)
- [ ] Test with 10 companies end-to-end

### Phase 2: Pilot (Week 2-3)
- [ ] Run 100 companies through the flow
- [ ] Monitor deliverability (aim for >95%)
- [ ] Track reply rate (aim for >10%)
- [ ] Refine personalization based on responses
- [ ] A/B test subject lines

### Phase 3: Scale (Week 4+)
- [ ] Increase to 200 companies/week
- [ ] Hire VA to handle reply categorization
- [ ] Set up Close.io integration
- [ ] Build dashboard for Jonny (opens, replies, meetings)
- [ ] Expand to new regions

---

## 💰 Cost Breakdown

### Tools Required:
- **Instantly:** $97/month (5 warmed accounts)
- **Snov.io:** $39/month (1,000 credits) or use free tier strategically
- **Hunter.io:** $49/month (email verification)
- **Apollo:** Free tier (company enrichment only)
- **Apify:** $29/month (already have)
- **Close.io:** $49/month (CRM)
- **Max (automation):** Free (I'm already here!)

**Total:** ~$263/month

**ROI:** 30-40 meetings/month × 10-20% close rate = 3-8 deals/month = $10K-$30K MRR

---

## 🚀 Ready to Launch?

Say the word and I'll:
1. Get the Instantly API key (via browser)
2. Build the automation script
3. Run a test batch of 10 companies
4. Show you the results
5. Scale from there

**Estimated time to first campaign:** 2-3 hours  
**Estimated time to full automation:** 1 week

Let's do this! 🔥