AIAutomationSupport

Conversational Automation: Reducing Support Load and Driving Qualified Leads

A B2B SaaS provider offering workflow automation tools was experiencing a sharp increase in customer inquiries as its user base scaled. The support team was overwhelmed by repetitive Tier-1 questions, leading to long response times and reduced customer satisfaction. At the same time, many inbound chat interactions were from potential leads that were not being captured effectively.

B2B SaaS Company
8 Weeks
SaaS / Technology
Conversational Automation: Reducing Support Load and Driving Qualified Leads

Key Results

24 minutes
was: 2 hours
First Response Time
38%
was: 100% baseline
Tier-1 Ticket Volume
90%
was: 72%
CSAT Score
+30%
Qualified Leads
94%
was: 60%
Escalation Accuracy
62%
Ticket Deflection

The Challenge

The client wanted to reduce dependency on manual support while maintaining a consistent and personalized user experience. Key challenges included: large volume of repetitive Tier-1 queries (password resets, billing, onboarding), response time exceeding 2 hours during peak usage, missed lead opportunities due to lack of automated qualification, and inconsistent escalation to Tier-2 support and sales teams. The goal was to deploy an intelligent chatbot that could handle both customer support automation and lead qualification, seamlessly integrated with existing systems.

Why Not Off-the-Shelf?

The client had previously used a generic chat widget with canned responses. However, it lacked contextual understanding, CRM integration, and multi-channel support. They required a conversational AI system capable of understanding intent, personalizing interactions, and triggering workflows in HubSpot and Slack.

Why They Chose Us

The client selected our team for our expertise in AI-driven automation and ability to bridge technical execution with business outcomes.

Experience in implementing intelligent bots integrated with CRMs and support systems

Deep understanding of conversational design, NLU (Natural Language Understanding), and escalation logic

Focus on measurable KPIs: ticket deflection, CSAT, and lead qualification rates

End-to-end ownership — from conversation flow design to post-launch optimization

Our Solution

The project was executed in three structured phases:

Phase 1 – Conversation Design and Workflow Mapping: Analyzed historical support tickets to identify repetitive queries. Designed conversation flows covering FAQs, troubleshooting, and lead capture journeys. Defined escalation rules for human intervention and lead routing.

Phase 2 – Chatbot Development and Integration: Built the chatbot using Dialogflow with custom webhook integrations. Connected to HubSpot CRM for lead creation and tagging. Integrated Slack notifications for escalations and AWS Lambda for serverless execution.

Phase 3 – Training, Testing, and Optimization: Trained the NLP model with domain-specific utterances and synonyms. Deployed A/B tests for conversation flows and monitored real-time analytics. Iteratively improved response accuracy and engagement metrics.

Technologies Used

DialogflowNode.jsWebSocket APIHubSpot CRMSlack IntegrationAWS Lambda

Key Highlights

Automated over 60% of repetitive Tier-1 queries

Real-time lead qualification integrated with HubSpot

25% improvement in customer satisfaction scores

Seamless escalation to support and sales via Slack

Continuous NLP training for accuracy improvement

"The chatbot has fundamentally improved our support efficiency and lead pipeline. Our team now focuses on strategic conversations instead of repetitive questions. The implementation was fast, smooth, and impactful."

Head of Customer Success

Head of Customer Success

B2B SaaS Company

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