How to implement AI in customer service
- Collect the real questions. Read recent conversations and group them by topic. This shows what comes in most often and what the AI can answer safely.
- Build the knowledge base. Gather policies, timelines, terms and approved answers, and name who keeps everything up to date. The agent is only as reliable as this base.
- Write down the limits. Define what the AI can't do, such as giving discounts, promising timelines outside the rules or handling serious complaints. Those cases go to a person.
- Design the handoff to a human. The person needs to receive the conversation with its history and a summary. If the customer has to repeat everything, the automation just created more work.
- Start with one topic and review. Release one topic, read a sample of conversations every week, fix the knowledge base and only then expand the scope.
What AI takes on in customer service
AI handles frequent requests with known answers and low risk. Everything else stays with the team, which gains time for the cases that call for judgment.
- Questions about products, services, timelines and published terms
- Topic triage and routing to the right person
- First response outside business hours
- Logging the conversation alongside the customer's history
Customer service AI or a sales agent?
The difference lies in the goal of the conversation. In customer service, the AI resolves questions from people who have already contacted the company or are already customers. The sales agent qualifies, books meetings and re-engages leads. Both can run on the same number, with different rules.
How Nexo deploys it in CRPRO
CRPRO is the CRM for WhatsApp built by Nexo. Implementation starts with an assessment of your customer service, moves through the knowledge base and the limits, and continues with ongoing review of the conversations after the agent goes live.
Customer service and the sales funnel live in the same place, so an answered question stays visible to whoever is handling the sale.
What to track after go-live
Resolution rate on its own is misleading, because the customer may simply have given up. Look at the metrics together.
- Conversations resolved without a person, confirmed by sampling
- Requests for human support
- Time to first response
- Satisfaction after the interaction
- Conversion of conversations with purchase intent