When chatbots make sense (and when they don’t)

AI chatbots promise faster responses, lower costs, and 24/7 availability. But here’s what the vendors won’t tell you: 74% of enterprise AI customer service projects fail to deliver real value. And 64% of customers say they’d prefer companies didn’t use AI for service at all.

That’s not an argument against chatbots. It’s an argument for being honest about when they work and when they don’t.

When chatbots actually help

Chatbots earn their keep in specific situations:

• High volume, simple queries. If you’re answering the same 10 questions hundreds of times a month, a chatbot can handle 80% of those interactions.
• After-hours coverage. When customers need help at 2am and you can’t staff that shift.
• Order tracking and account status. Straightforward lookups that don’t require judgment.
• Lead capture. Collecting contact info and qualifying prospects before a human follows up.

When these conditions are met, companies see real results: 30% lower support costs and response times measured in seconds instead of hours.

When they don’t

Here’s where most chatbot investments go wrong:

• Low inquiry volume. If you handle fewer than 100 customer interactions per month, the setup and maintenance costs won’t pay off.
• Complex or consultative products. Chatbots can’t navigate nuanced questions or weigh trade-offs. They frustrate customers who need real guidance.
• Relationship-based businesses. If your value proposition is personal attention, a bot undermines it. 46% of customers think chatbots are designed to keep them from humans.
• Emotionally sensitive situations. Complaints, disputes, or anything requiring empathy. Bots make these worse.
• No one to maintain it. Chatbots need regular updates to their knowledge base. Without ongoing attention, they decay quickly.

Red flags when evaluating vendors

Watch for these warning signs:

• “Set it and forget it” promises. Chatbots require ongoing maintenance. Anyone who says otherwise is selling you a problem.
• Vague pricing. Ask about per-message fees, overage charges, and integration costs. They add up.
• No human escalation path. If there’s no clear way for customers to reach a person, you’ll lose them.
• Over-promised accuracy. Industry-standard natural language understanding hovers around 75-78%. Vendors promising 95%+ are setting you up for disappointment.

What good looks like

Quality chatbot implementations share common traits:

• Clear handoff to humans with full conversation context
• Regular knowledge base updates based on actual customer questions
• Realistic scope that starts with high-volume, repetitive queries
• Analytics tracking both cost savings and customer satisfaction

What we’d need from you

If chatbots make sense for your situation, successful implementation requires:

• A clean, current FAQ or knowledge base to train the bot
• Decisions about when and how to escalate to humans
• Someone responsible for ongoing updates and monitoring
• Realistic expectations about what automation can handle

Questions to ask before committing

1. How many customer inquiries do we handle monthly? If under 100, reconsider.
2. What percentage are simple, repetitive questions? Low percentage means low chatbot value.
3. Do we have the content to train it? No good FAQ means no good chatbot.
4. Who will maintain it? Without an owner, it will fail.
5. What happens when it can’t help? The escalation path matters as much as the bot itself.

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Chatbots can be genuinely useful. They can also be expensive mistakes. The difference comes down to honest assessment, not hype.

If you’re weighing whether automation fits your customer service, we can help you think it through.

Talk to us about chatbot strategy.