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Customers Say Our Chatbot Will Not Let Them Talk to a Person. How Do We Fix It?

A chatbot trapping customers in loops, with no way to a person, costs goodwill. SpiderHunts audits your live bot and rebuilds its escape routes and handover.

Updated 3 min readBy SpiderHunts Technologies

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Quick answer — TL;DR

Bots trap people when they were set up to deflect contact rather than resolve it, and when handover was treated as failure. We review your real transcripts to find the loops, add clear routes to a person that always work, detect frustration and repetition automatically, and pass the full conversation to your team so nobody repeats themselves.

Stuck talking to a bot

A customer types 'speak to a person'. The bot replies with three article links. They type 'agent'. The bot asks them to rephrase. They type 'HUMAN PLEASE'. The bot says it did not understand and offers the main menu again.

Eventually they find your phone number elsewhere, ring, and start the whole story again, now annoyed. Or they leave a review about your chatbot. Or they simply go away.

You may have seen this in complaints, or you may not know it is happening at all, because nobody reads the transcripts.

How a bot ends up as a wall

It is rarely deliberate. Chatbots are often bought or measured on how many conversations they 'deflect' from the support team. That number looks good in a report even when the deflected customer simply gave up. When the target is fewer contacts, the easiest design is a bot that makes contact hard.

Handover is also often an afterthought. It needs a staffed queue behind it, rules for out-of-hours, and a way to pass the conversation over. If that plumbing was not built, the bot has nowhere to send people, so it keeps them.

And older, intent-based bots simply fail on anything they were not trained for, which includes many ways of asking for a person.

What the loop costs you

What happensWhat it costs
Customer gives upLost sale or lost customer, invisible in reports
Customer rings insteadLonger, angrier call that starts from scratch
Customer posts about itPublic reviews about being stonewalled
Deflection figures look goodManagement believes the bot is working

The last row is why this can run for a long time unnoticed. The metric says the bot is succeeding at exactly the moment it is failing.

How SpiderHunts fixes a bot that will not let go

  1. Read the transcripts. We review a sample of real conversations, find the loops, dead ends and abandoned chats, and show you what customers experienced.
  2. Make the route to a person always visible and always working: a clear 'talk to a person' option, and recognition of the many ways people ask, from 'agent' to 'this is useless'.
  3. Detect frustration and failure automatically: repeated questions, the same answer given twice, negative wording, or several turns without progress. Any of these offers a person straight away.
  4. Build the handover properly: to live chat when staff are available, to a ticket or callback request when they are not, with an honest message about when a person will pick it up in your normal working pattern.
  5. Pass the full conversation and anything the bot collected, such as the order number, to the person taking over, so the customer never has to repeat themselves.
  6. Keep the bot to topics it handles well, and route sensitive topics, such as complaints, cancellations and vulnerable customers, to people from the start.
  7. Replace deflection as the main measure with resolution: did the customer get what they needed, whether from the bot or a person.

We can usually do this within your existing chatbot platform, such as Intercom, Zendesk, Tidio or LivePerson, if it exposes the right controls. If it does not, we explain what the limits are and what the alternatives would be.

A bot that knows when to step aside

Customers who want a person can reach one, on the first ask. The bot still handles the routine questions it is good at, and when it hands over, your team sees the whole conversation. Frustrated customers are caught early rather than after they have written a review.

Handover also becomes a source of improvement. Every conversation the bot passes on is a question it could not answer or a situation it should not handle. Reviewing them shows you which new topics are worth teaching it and which should always go straight to a person.

Your reports show whether customers actually got help, which is a better guide to whether the bot is earning its place.

Is your bot a wall?

  • Complaints or reviews mention being unable to reach a person.
  • Your chatbot is measured mainly on deflection.
  • Typing 'speak to a person' does not reliably reach one.
  • Staff taking over from the bot have to ask the customer to start again.
  • Nobody regularly reads the bot's conversations.

FAQ

Frequently asked questions

The questions readers ask us after this guide.

Still have a question?

Ask us directly — a senior engineer will get back to you.

Ask about your project

Will more handovers overwhelm our team?

Some conversations that were silently abandoned will now reach your team. In return, the bot is tuned to resolve more of what it handles, and handovers arrive with context so they are quicker to deal with.

What if nobody is available when a customer asks for a person?

The bot says so honestly, takes the details and creates a ticket or callback request, rather than pretending someone is coming.

Do we have to replace our chatbot?

Usually not. Most fixes can be made within the platform you have, if it allows handover and conversation export.

How do you find the problem conversations?

We review a sample of transcripts and use automated checks for repetition, negative wording and abandonment to find the worst ones.

Keep reading

More on Problems We Solve

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