system-prompts-and-models-of-ai-tools/dealix/docs/business/FIRST_100_TARGETS_PLAN.md

Dealix — Day 1 Operating Playbook

100 Saudi B2B accounts queued. Zero auto-send. This file is your morning script.

What's in this folder

File	What you do with it
day1_outreach_queue.csv	100 ready accounts with Arabic message drafts. Open in Excel, Sami approves row-by-row before any send.
saudi_directory_normalized.csv	All 6,957 unique Saudi B2B companies after dedupe + scoring. Master record.
import_payload_high_fit.json	1,000-row payload to POST to /api/v1/data/import after deploy.
day1_scorecard.json	Pipeline metrics for the build.
PRICING_AND_PACKAGES.md	Pilot 499 SAR → Starter 999 SAR → Pro 5K SAR ladder.

Queue split (100 accounts)

Sector	Count	Why this segment
real_estate_developer (Riyadh)	25	Inbound leads, slow Arabic response = lost deal. ICP gold.
real_estate_developer (Jeddah)	20	Same as above, second-largest market.
events / قاعة حفلات	15	Each lead = 5K-100K SAR booking. Fastest pilot conversion.
hospitality / فندق	15	MICE + Iftar + Suhoor inquiries. Heavy Arabic inbound.
logistics / شحن	15	RFQ response time = revenue. Pure B2B.
saas / Software company	10	Saudi SaaS founders — Dealix is in their stack stack.

All 100 → priority=P2, channel=phone_task. Personal-email rows demoted to phone (PDPL guard).

Day 1 — 9:00 AM → end of day

9:00 — Coffee & open the queue

Open day1_outreach_queue.csv in Excel. Sort by total_score descending.

9:30 — Top 5 phone calls

First 5 P2 real-estate Riyadh accounts. Script (Khaliji Arabic):

السلام عليكم، أنا سامي من Dealix. اتصلت لأن نشتغل على AI sales rep بالعربي يخدم شركات التطوير العقاري السعودية — يرد على lead خلال 45 ثانية بدل ما يعلق نص يوم. هل تواجهون مشكلة وقت الرد على leads الـ inbound؟

Stop after 5 calls. Log results in pipeline_tracker.csv (create if missing).

11:00 — 5 emails (with opt-out)

Top 5 accounts that have a business email (filter is_personal_email=False). Use the message_ar column as draft. Send from Sami's Gmail. Always include the opt-out line.

14:00 — 1 LinkedIn message

Manual research first (use the LinkedIn URL only as research — never automate). Pick 1 Saudi SaaS founder from the queue. Send a personalized note referencing their company.

16:00 — Pricing-page demo

Walk a real prospect through the demo using PRICING_AND_PACKAGES.md as reference. Lead with: "Pilot 499 ريال، 7 أيام، نرد على leadsكم بدلاً منكم. لو ما اقتنعتم — استرجاع كامل خلال 3 أيام."

18:00 — End-of-day scorecard

Update day1_scorecard.json with:

• messages_sent_today
• replies_today
• demos_booked
• pilot_signups
• payment_requested

Day 1 success criteria

Metric	Target
Outbound reaches	11 (5 calls + 5 emails + 1 LinkedIn)
Replies	≥ 2
Demo booked	≥ 1
Pilot pay request sent	≥ 1
Hours worked	≤ 6

If you hit ≥ 1 demo booked → you've proven the funnel works. Repeat tomorrow with the next 11.

What you don't do today

• ❌ Cold WhatsApp blast (channel violation + spam)
• ❌ Bulk email to all 100 (ramp deliverability slowly)
• ❌ Promise custom features beyond pilot scope
• ❌ Skip the approval gate on any message
• ❌ Use any of the 6,636 personal emails for email channel

Day 2 setup

1. Run python scripts/audit_lead_file.py saudi_directory_normalized.csv — confirm 0 collisions remain.
2. Pull the next 100 from saudi_directory_normalized.csv (filter to priority=P2, sort by score, skip any in yesterday's queue).
3. Same playbook, different segments. Maybe add marketing_agency if Maps key is now live.

When the deploy lands

After Railway env is set + push lands, replace the manual queue with:

# Push 1000-row high-fit payload to the API
curl -X POST https://api.dealix.me/api/v1/data/import \
  -H 'content-type: application/json' \
  -d @import_payload_high_fit.json

# Run the server-side pipeline
curl -X POST https://api.dealix.me/api/v1/data/import/<id>/normalize
curl -X POST https://api.dealix.me/api/v1/data/import/<id>/dedupe
curl -X POST https://api.dealix.me/api/v1/data/import/<id>/enrich -d '{"enrichment_level":"standard","max_accounts":50}'

# Pull outreach-ready
curl -X POST https://api.dealix.me/api/v1/outreach/prepare-from-data \
  -d '{"priority":["P0","P1","P2"],"max_accounts":100,"persist":true}'

The server does what we did locally, plus enrichment via Google CSE + Maps + Crawler chains, and persists to Postgres so you have a real CRM behind the queue.