The client was losing high-value business leads due to delayed follow-ups and manual data entry

The client was losing high-value business leads due to delayed follow-ups and manual data entryThe client was losing high-value business leads due to delayed follow-ups and manual data entry

The network for creativity

Join 1.25M professional creatives like you

Connect with clients, get discovered, and run your business 100% commission-free

Creatives on Contra have earned over $150M and we are just getting started

Back to feedPost

Mirza Umer

• Jul 2

The client was losing high-value business leads due to delayed follow-ups and manual data entry across disconnected platforms (CRM, email, and advertising channels). The internal team was spending upwards of three hours a day manually copying lead data, resulting in data fragmentation and an average response time of over 12 hours.

The Tech Stack

1. n8n (Advanced Workflow Orchestration).

2. Webhooks & REST APIs (Data Ingestion).

3. PostgreSQL / Airtable (Centralized Data Warehouse).

4. Slack API (Instant Internal Notifications).

The Solution. I engineered an autonomous, multi-stage lead processing engine using n8n. The system captures inbound leads via instant webhooks from front-end marketing platforms, normalizes and enriches the data using secondary API lookups, and instantly populates the centralized data warehouse. Simultaneously, the workflow routes the lead based on custom logic (such as budget or region) and fires an immediate, structured notification to the sales team's Slack channel, allowing for a sub-5-minute response time.

The Business Impact. The automated pipeline eliminated manual data entry, recovering roughly 15 hours of administrative time per week for the internal team. More importantly, reducing the lead response time from 12 hours down to under 5 minutes directly improved lead-to-opportunity conversion rates by over 30%.

AI Automation Data Engineering Business Workflow Automation N8N PostgreSQL Slack

Noah Wainwright

pro

• Sep 30

Simple flow for an ai-powered sales platform

Design Engineering UI Design UX Design

Kaushal Bodar

• Oct 2

Top-notch design.

Darrien Williams

• Oct 1

Built a simple lead intake and follow-up workflow for Nightstack Labs.

The goal was to make handling new customer inquiries more organized without manually moving information between different tools.

The workflow:

Customer submits a form → lead information is organized → lead is logged → the business gets notified → the customer gets a confirmation

Built with Tally, Make, Google Sheets, and Gmail.

AI can also be used to summarize incoming requests when it actually improves the workflow.

AI Automation Business Workflow Automation Make

Johnson Afolabi

• 1d

I like how the form feeds straight into a sheet and triggers the email, cutting out the copy paste step.

sharjeel mansha

• Sep 30

𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐋𝐞𝐚𝐝 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 & 𝐂𝐑𝐌 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦 I built an automated lead generation system designed to simplify the entire sales pipeline from lead capture to follow-up. The system collects leads from multiple sources, processes and qualifies them, adds them directly into the CRM, updates pipeline stages automatically, and triggers personalized follow-up sequences based on lead activity. Instead of managing leads manually across different tools, the entire workflow runs through one connected automation system. 𝐖𝐡𝐚𝐭 𝐭𝐡𝐞 𝐬𝐲𝐬𝐭𝐞𝐦 𝐡𝐚𝐧𝐝𝐥𝐞𝐬:

-Lead capture from multiple sources -Lead enrichment and qualification -Automatic CRM entry -Pipeline stage updates -Automated follow-up sequences -Reply and meeting tracking -Opportunity management The goal is simple: reduce manual work, improve response speed, and make sure valuable leads don’t get missed. 𝐖𝐚𝐧𝐭 𝐭𝐨 𝐛𝐮𝐢𝐥𝐝 𝐚 𝐬𝐢𝐦𝐢𝐥𝐚𝐫 𝐥𝐞𝐚𝐝 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐂𝐑𝐌 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐬𝐲𝐬𝐭𝐞𝐦 𝐟𝐨𝐫 𝐲𝐨𝐮𝐫 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬? 𝐋𝐞𝐭’𝐬 𝐜𝐨𝐧𝐧𝐞𝐜𝐭.