Freelance Data Entry Specialists in BengaluruFreelance Data Entry Specialists in Bengaluru
Automation Consultant β€” n8n & Make.com | Lead Intake Systems
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Automation Consultant β€” n8n & Make.com | Lead Intake Systems
Cover image for Agency Onboarding Automation β€” From
Agency Onboarding Automation β€” From Contract to Project Launch Without Manual Setup Built a client onboarding machine for a digital agency that eliminates 2+ hours of manual admin every time a new client signs. THE PROBLEM: New client signs the contract β†’ account manager manually creates a Slack channel, Google Drive folder, Asana project, and sends a welcome email 2 days later. Clients felt ignored. Projects started slow. Project managers wasted hours on setup instead of strategy. THE SYSTEM I BUILT: β†’ TRIGGER: PandaDoc/HelloSign contract signature instantly fires webhook β†’ QUALIFY: Parse contract value, service type (SEO, PPC, Web Design), and team size to determine onboarding tier (Standard vs. Premium) β†’ CREATE: Auto-generate Slack channel with client + internal team, Google Drive folder structure with template documents, and Asana project from pre-built template with all milestones β†’ ASSIGN: Push client data to HubSpot CRM, notify finance team in Slack, and assign project manager based on current workload and expertise match β†’ WELCOME: Client receives personalized welcome email with project timeline, team contacts, kickoff meeting link, and onboarding checklist within 10 minutes of signing β†’ SYNC: All project data synced to agency dashboard for leadership visibility THE RESULTS: β€’ Onboarding initiation: 48 hours β†’ 10 minutes β€’ Admin time per new client: 2 hours β†’ 5 minutes β€’ Client satisfaction score (onboarding phase): +40% β€’ Project setup consistency: 100% across all teams TECH STACK: Make.com (http://Make.com) | PandaDoc | Slack | Google Drive | Asana | HubSpot | Google Workspace WHY THIS WORKS: First impressions are everything. This system makes clients feel like they're working with a machine-precision agency from minute one β€” because they are.
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Cover image for E-Commerce Auto-Fulfilment System β€” From
E-Commerce Auto-Fulfilment System β€” From Order to Label Without Touching a Spreadsheet Built a fully automated order-to-fulfillment pipeline for a D2C brand selling across Shopify, Amazon, and their own store. THE PROBLEM: The operations team manually copied orders into spreadsheets, checked inventory against 3 separate sources, created shipping labels one by one, and updated tracking numbers by hand. 3 hours of daily grunt work. 8% error rate. Delayed shipments. Angry customers asking "where is my order?" THE SYSTEM I BUILT: β†’ CAPTURE: Shopify order webhook fires instantly on every purchase. Amazon SP-API pulls orders every 15 minutes into the same pipeline. β†’ VALIDATE: Auto-check inventory in Google Sheets. Flag low-stock SKUs for reorder. Route expedited orders to priority queue. β†’ PROCESS: Generate shipping label PDF automatically via Shiprocket API. Create invoice in Zoho Books. Update inventory count across all channels in real-time. β†’ SYNC: Push order status, tracking number, revenue data, and shipping cost to master Google Sheets dashboard for ops visibility. β†’ NOTIFY: Customer receives automated email/SMS with tracking link within 5 minutes of order confirmation. β†’ ALERT: Operations manager gets daily summary + instant alert on failed orders with retry logic and error context. THE RESULTS: β€’ Manual processing time: 3 hours/day β†’ fully autonomous β€’ Order processing errors: 8% β†’ 0.2% β€’ "Where is my order?" support tickets: -60% β€’ Scales to 10,000+ orders/month without adding staff TECH STACK: Make.com (http://Make.com) | Shopify | Amazon SP-API | Google Sheets | Shiprocket | Zoho Books | Twilio | PDF Generator WHY THIS WORKS: E-commerce margins are thin. Every minute of manual processing and every fulfillment error eats profit. This system runs 24/7 without breaks, mistakes, or overtime pay.
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Cover image for Real Estate Auto-Response System β€”
Real Estate Auto-Response System β€” Capture Every Inquiry in 60 Seconds Designed a 24/7 inquiry response engine for a real estate agency handling 50+ daily leads across property portals, Facebook, and WhatsApp. THE PROBLEM: Agents were responding to inquiries 4-6 hours later. By then, prospects had already contacted 3 competitors and scheduled viewings elsewhere. The agency was bleeding money on ad spend but losing deals to response speed. THE SYSTEM I BUILT: β†’ CAPTURE: All form submissions and WhatsApp messages hit a unified n8n webhook β†’ QUALIFY: Parse budget range, location preference, and property type from natural language inquiry text using regex + AI classification β†’ MATCH: Query Airtable inventory database and return top 3 matching listings based on budget, location, and availability β†’ RESPOND: Send personalized WhatsApp auto-reply with listing photos, prices, and agent contact within 60 seconds β€” 24/7, even at 2 AM β†’ LOG: Every conversation automatically logged to Airtable CRM with full context β†’ FOLLOW-UP: Create follow-up task with reminder for agent if no response within 24 hours β†’ ALERT: Agent gets mobile Slack notification with full inquiry context, suggested response, and client LinkedIn profile THE RESULTS: β€’ First response time: 4 hours β†’ under 60 seconds β€’ Inquiries lost to delay: 0 β€’ Agent conversations handled per day: 3x increase β€’ Listing view-to-meeting conversion: +35% TECH STACK: n8n | Airtable | WhatsApp Business API | Google Forms | Slack WHY THIS WORKS: In real estate, speed wins. This system ensures every inquiry gets a personalized, instant response with matching listings β€” while the prospect is still interested.
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Cover image for AI-Powered Lead Qualification System β€”
AI-Powered Lead Qualification System β€” Zero Manual Data Entry Built an end-to-end lead capture and qualification system for a B2B service business using Make.com (http://Make.com), OpenAI GPT-4, and HubSpot. THE PROBLEM: The sales team was manually copying lead data from forms into CRM, losing 6+ hours per day and missing hot leads entirely. By the time a rep reached out, the prospect had already talked to 3 competitors. THE SYSTEM I BUILT: β†’ CAPTURE: Typeform webhook triggers automation the instant a form is submitted β†’ QUALIFY: OpenAI GPT-4 scores lead intent (1-10) based on message content, budget signals, and role seniority β†’ ENRICH: Apollo.io (http://Apollo.io) API appends company size, revenue, tech stack, and LinkedIn URL automatically β†’ ROUTE: Hot leads (score 7+) create HubSpot deals + instant Slack alert to assigned sales rep with full context β†’ NURTURE: Cold leads enter a 7-day email sequence before sales touches them β†’ SYNC: Bi-directional sync between HubSpot and Google Sheets reporting dashboard for real-time pipeline visibility THE RESULTS: β€’ Lead-to-CRM time: 4 hours β†’ 90 seconds β€’ Sales rep prep time per lead: 15 minutes β†’ 30 seconds β€’ Data loss rate: 0% β€’ Sync accuracy: 99.7% TECH STACK: Make.com (http://Make.com) | OpenAI GPT-4 | HubSpot | Apollo.io (http://Apollo.io) | Slack | Google Sheets | Typeform WHY THIS WORKS: Sales teams shouldn't do data entry. This system ensures every lead is scored, enriched, and routed before the prospect even closes the Typeform tab.
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Experienced Virtual Assistant & Business Manager
Experienced Virtual Assistant & Business Manager
DATA CLEANING, ANALYSIS & VISUALIZATION
DATA CLEANING, ANALYSIS & VISUALIZATION
Content Writer & Data Entry Specialist
Content Writer & Data Entry Specialist
Versatile copy expert for hire πŸ“
Versatile copy expert for hire πŸ“
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