Potansiyel Müşteri Otomasyon Sistemi
Akıllı potansiyel müşteri değerlendirme ve yönlendirme sistemi. Gelen talepleri işler, belirlenen kriterlere göre puanlar ve nitelikli müşterileri otomatik olarak yönlendirir.
Zorluk
Her talebe kişiselleştirilmiş, yüksek kaliteli yanıtlar vermeyi sürdürürken müşteri adayı işlemedeki manuel darboğazı ortadan kaldırmak.
Sonuçlar
- Otomatik değerlendirme puanlaması
- Yapay zeka ile kişiselleştirilmiş yanıt üretimi
- Gerçek zamanlı müşteri adayı panosu
- Sıfır manuel değerlendirme gereksinimi
Teknoloji
The Problem
Service businesses live and die by lead response time. Research shows that responding within 5 minutes makes you 21x more likely to qualify a lead compared to waiting 30 minutes. But manually reviewing every inquiry, qualifying it, and crafting a personalized response takes time — time that competes with actual client work.
The Lead Intake Automation System solves this by handling the entire triage process automatically, while maintaining the quality and personalization of a human response.
How It Works
The pipeline runs on n8n, an open-source workflow automation platform:
- Capture: New inquiry arrives via website form, email, or referral channel
- Extraction: Structured data is parsed from the submission — project type, budget signals, timeline, specific requirements
- Enrichment: Company information is gathered from public sources to add context
- Qualification: AI evaluates the lead against predefined criteria — project fit, budget alignment, timeline feasibility, scope clarity
- Response: Qualified leads receive an immediate, personalized acknowledgment with relevant next steps; out-of-scope inquiries get a helpful redirect
- Routing: Qualified leads are assigned based on project type, expertise match, and current workload
Every interaction is logged in Supabase, building a dataset for pipeline optimization.
AI Qualification
The qualification step uses Claude AI to evaluate each lead holistically. Rather than simple keyword matching, the AI considers:
- Does the project align with our service capabilities?
- Is the implied budget realistic for the scope described?
- Is the timeline feasible given current commitments?
- Is the inquiry specific enough to act on?
The AI produces a qualification score with reasoning, giving the team visibility into why a lead was scored the way it was. Borderline cases are flagged for human review rather than auto-rejected.
Current Status
The core workflow is functional and processing test data. Current development focuses on refining qualification criteria based on historical conversion data and improving the personalization engine for automated responses.