Reklam Bütçesi Olmadan Müşteri Bulmak: #claudecode ve Apify kullanıyorum

Business-focused summary (customer acquisition automation + no ad budget)

• The presenter describes building and monetizing multiple micro-SaaS/AI apps (as a “studio” concept) that generate revenue with high margins using subscriptions and minimal ongoing expenses.
• Key strategy: begin with organic growth and little/no advertising to validate which niches and acquisition funnels work. Then increase ads gradually only after ROI signals are clear.
• The video is framed as a “how-to” for building a customer acquisition agency automation system using:
  • Cloud Code (Claudecode)
  • An agent that uses Apify to source leads and generates a ranked, ready-to-contact list

Reported results, economics, and targets (KPIs)

App studio performance

• Built 20+ apps over ~1 year
• Total revenue: ~€400,000 in 12 months
• Example outcomes:
  • Protbal: $105,000 in one year
  • Another simpler app: ~$800
  • Dekorbizyon application: ~$3,500

Profit model (SaaS vs. e-commerce)

• E-commerce illustration:
  • If $1M sales, profit max is ~$150k (implied margin ~15%)
• SaaS illustration:
  • 60%–75% typical profitability
  • Some apps: near 100% profitability due to “almost no expenses”
• Emphasis: subscription apps can create a “snowball effect” (compounding growth over time).

Advertising growth plan

• Earlier year earnings from ads: nearly €400k (video references both organic and ad involvement; the plan is still to scale ads after validation)

• Next 2-year target: €1.2M–€1.6M

• Prototype metric:

  • Reached ~106,000 in ~1 year (not clearly stated as users vs. revenue; treated as a product growth metric)

• Specific Protbal claim:

  • $105,000 all-time with zero ad spend
  • Then ads can be used once there’s proof customers will pay.

Lead acquisition cost

• Example test run:
  • Produced 50 leads in ~5 minutes
  • Cost: “40 cents” for the lead sourcing step (likely Apify/data scraping/automation cost)

Frameworks / playbooks / processes emphasized

• SaaS-first unit economics
  • Prioritize recurring subscriptions to improve margin and compounding growth.
• Staged growth playbook (organic → ads)
  • Year 1: validate niches/apps and learn what works (prefer organic; minimal ads)
  • Years 2–4: scale via advertising once ROI is proven
• Agentic customer acquisition workflow
  • Automate the loop: criteria → lead discovery → analysis → ranked list → action
• Idea scoring process for choosing micro-SaaS niches
  • Example categories:
    • Convenience
    • Market
    • Earnings
  • Produces a Total score (example score: 22)

Concrete implementation: customer acquisition agent (Cloud Code + Apify)

System design (end-to-end flow)

• The agent runs inside Cloud Code (and can also run locally in CLI).
• Input:
  • A simple criterion / niche selection
• Steps:
  1. Find relevant people/emails (target decision-makers or local business contacts)
  2. Analyze leads
  3. Highlight/produce organized lists for outreach
  4. Take actions (implied: export lists, feed into follow-up processes)

Apify usage constraints (operational limit)

• When using Apify: maximum 50 companies per run
• The system should constantly check until it reaches 50

Apify targeting approach (decision-makers)

• Lead filters include roles such as:
  • General manager
  • Founder
  • Founding partner
  • Company owner
  • (and other similar decision-maker roles)
• Recommendation: start with company-level targeting to reach decision-makers rather than random individuals.

Output format (what the agent produces)

• A ranked list of prospects
• Example interface includes:
  • Company/business name
  • Contact info such as phone number
  • Comments/reasoning why they match
  • Additional attributes (e.g., website presence)

Actionable recommendations / tactics extracted

• Build an acquisition agent instead of manual prospecting
  • Manual research is described as slow, hard to track, and expensive in time.
• Create a simple user interface
  • Help users review and export results
  • Outputs can be downloaded/exported.
• Use a “generate → rank → act” pipeline
  • Generate leads via Apify
  • Analyze and rank them
  • Follow up via email/website outreach (implied next step)
• Monetize around the same asset
  • Sell as:
    • a cloud app / micro-SaaS, or
    • an agency-style service (e.g., website creation for leads missing one)
• Run locally for transparency
  • Users can see results on their own machine/IP via CLI-local execution

Example business idea selected and how it would be monetized

Selected niche micro-SaaS idea (from a 100-idea list)

• Idea: Google Maps comment responder (AI-driven)
• Stated market: B2B for restaurants
• Pricing: $29–$59/month
• Scoring shown:
  • Total score: 22
  • Convenience: 8
  • Market: 8
  • Earnings: 6

How acquisition would work for that idea

• Use Apify Google Maps scraper to extract:
  • restaurants listed on Google Maps
  • contact details (emails/websites/phone where available)
• Conversion strategy:
  • For businesses without websites, offer website services as an upsell/cross-sell.

Sources / presenters

• Presenter: Not explicitly named in the subtitles (video title indicates “#claudecode” / “Apify,” but no person name is captured here)

• Tools/sources referenced:

  • Cloud Code (claudecode / Cloud COD)
  • Apify
  • ChatGPT
  • Google Maps