Customer Service
Knowledge article gap detection and drafting
Identify the questions agents and customers ask that the knowledge base does not answer, and draft the missing articles from resolved cases for a knowledge manager to approve.
40–60%
reduction in knowledge base maintenance effort
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
Relatively straightforward. Off-the-shelf tools handle the core task. Implementation is well-understood with good examples to follow.
Light data requirements. Uses straightforward inputs — documents, product descriptions, customer records — that are usually accessible with minimal prep.
Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.
Light people impact. A new tool slots into an existing workflow. Minimal training needed. Most people will adapt quickly.
Tooling required
Things to consider
Knowledge bases decay because maintenance is nobody's main job. Automating gap detection and first-draft authoring converts it from a project into a background process.
Failed searches and escalated contacts are the best gap signals. An article nobody searches for is not a gap however incomplete it looks.
Drafting from resolved cases risks encoding a workaround as policy. Require the knowledge manager to confirm each draft reflects the intended process, not just what an agent did once.
Experiment starter: Analyse a quarter of failed searches and escalations, generate drafts for the top twenty gaps, and measure contact volume on those topics for the three months after publication.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Experimentation FrameworkThis is an augmentation opportunity — see the relevant playbook section for how to approach it.More in Customer Service
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Classify incoming complaints by type and urgency, then generate a first-draft response. Agent reviews, personalises, and sends. Faster turnaround, consistent tone.
Knowledge base chatbot (FAQ deflection)
Answer common customer questions using a RAG system over the knowledge base. Deflects repeat queries from contact centre. Escalates complex issues to humans.
Customer feedback synthesis
Aggregate and summarise customer reviews, survey responses, and support tickets into themes. Weekly digest for product and commercial teams.
AI Transformation Playbook
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