AI-Powered Customer Support Automation

Deploy AI chatbots and agent assist to handle 60-70% of support tickets automatically while improving customer satisfaction.

Beginner2-4 months

Transformation

Before & After AI

What this workflow looks like before and after transformation

Before

Support agents handle 50-100 tickets per day, with 60-70% being repetitive queries (password resets, order status, FAQ). Average response time is 4-8 hours. Customer satisfaction (CSAT) sits at 72-78%. Agent turnover is high due to repetitive workload. Scaling requires proportional headcount increases.

After

AI handles 60-70% of incoming queries instantly through chatbot and automated workflows. Agents receive AI-suggested responses for complex issues, reducing handle time by 40%. CSAT improves to 85-90% due to instant resolution of simple queries. Support scales without linear headcount growth.

Implementation

Step-by-Step Guide

Follow these steps to implement this AI workflow

1

Analyse Support Patterns

2 weeks

Review 3-6 months of support tickets. Categorise by: type (FAQ, transactional, complex), channel (email, chat, phone), resolution path, and automation potential. Identify the top 20 query types that represent 80% of volume. These become the AI automation targets.

2

Build AI Knowledge Base

3 weeks

Create structured knowledge base articles for every automatable query type. Include: answer text, required context (order number, account info), escalation triggers, and tone guidelines. This knowledge base powers both chatbot and agent assist.

3

Deploy Chatbot & Agent Assist

3 weeks

Configure AI chatbot for customer self-service on high-volume query types. Build agent assist that suggests responses, surfaces relevant knowledge articles, and auto-fills templates for human agents. Integrate with your ticketing system and CRM.

4

Train & Launch

2 weeks

Train support team on working with AI assist. Run chatbot in "suggest mode" first (AI suggests, human approves) before "auto mode" (AI responds directly). Monitor chatbot containment rate and escalation quality. Launch publicly with clear "talk to human" options.

5

Optimise Continuously

Ongoing

Review conversations where customers asked to escalate from AI. Improve knowledge base for common failure cases. Add new query types as they emerge. Track: containment rate, CSAT for AI vs. human, resolution time, and cost per ticket.

Tools Required

Conversational AI platform (Zendesk AI, Intercom, Freshdesk)Knowledge base / help centreCRM integrationTicketing systemAnalytics dashboard

Expected Outcomes

Automate 60-70% of support queries through AI chatbot

Reduce average first response time from hours to seconds

Improve CSAT from 72-78% to 85-90%

Reduce agent handle time by 40% with AI suggestions

Cut cost-per-ticket by 50-60% for automated queries

Solutions

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Frequently Asked Questions

Research shows 74% of customers prefer chatbots for simple queries because they get instant answers without waiting. The key is being transparent ("I'm an AI assistant") and making it easy to reach a human when needed. CSAT for well-implemented chatbots often exceeds human support for routine queries.

With a good knowledge base, chatbots can handle 40-50% of queries from day one. Within 2-3 months of learning from conversations, containment rates typically reach 60-70%. The improvement curve steepens as you add more query types and refine responses based on customer feedback.

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