Marketio.net - AI Lead Qualification

1. Context¶

Marketio.net, a digital marketing agency, was struggling with a high volume of inbound leads from their WhatsApp channel. The manual process of qualifying each lead was slow, error-prone, and led to a significant delay in response time. This resulted in lost opportunities and a poor customer experience.

The Challenge: To automate the lead qualification process to instantly qualify and route leads to the appropriate sales team member.

2. Goals¶

• Reduce response time: Drastically reduce the time it takes to respond to a new lead.
• Improve lead quality: Ensure that only qualified leads are passed on to the sales team.
• Increase conversion rate: By responding to leads faster with the right information, the goal was to increase the conversion rate.
• Scale the process: The solution needed to be scalable to handle a growing number of leads.

3. Approach¶

I designed and implemented a custom n8n workflow that integrated with their WhatsApp Business API and their CRM (HubSpot).

The workflow consisted of the following steps:

1. Webhook Trigger: The workflow is triggered by a webhook that receives incoming messages from the WhatsApp Business API.
2. AI-Powered Analysis: The message content is then sent to a large language model (LLM) to analyze the message and extract key information, such as the lead's name, company, and specific needs.
3. Lead Qualification: Based on the analysis, the lead is qualified against a set of predefined criteria.
4. CRM Integration: If the lead is qualified, a new deal is created in HubSpot with all the extracted information.
5. Team Notification: The appropriate sales team member is then notified via a direct message in Slack with a link to the new deal in HubSpot.
6. Auto-response: A personalized auto-response is sent to the lead on WhatsApp, letting them know that their inquiry has been received and that a team member will be in touch shortly.

4. Results¶

The implementation of the n8n workflow had a significant impact on Marketio.net's lead management process:

• 95% reduction in response time: The average response time was reduced from 2 hours to just 5 minutes.
• 80% improvement in lead quality: The sales team reported a significant improvement in the quality of leads they received.
• 25% increase in conversion rate: The faster response time and improved lead quality resulted in a 25% increase in the conversion rate.
• Scalability: The solution is able to handle a high volume of leads without any manual intervention.

5. Next Steps¶

The next phase of the project involves adding more intelligence to the workflow, such as:

• Sentiment analysis: To gauge the lead's sentiment and prioritize follow-ups.
• Automated follow-ups: To send automated follow-up messages to leads who haven't responded.
• Integration with other channels: To expand the automation to other lead channels, such as email and Facebook Messenger.

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