More Chats, Less Quality? What We Learned After Launching a Chatbot

When Chatbots Go Live

Chatbots promise a lot: more interaction, faster responses, lower entry barriers for users. Like many companies, we introduced a chatbot on our website to improve accessibility and enable easier contact.

What happened next was interesting - and more nuanced than expected.

Within a short time, interaction numbers increased significantly. More messages, more conversations, more touchpoints. At first glance, a clear success. But when we looked closer, another pattern emerged: while volume increased, the quality of inquiries declined.

More Interaction Does Not Mean Better Leads

The chatbot lowered the threshold for engagement. Visitors who might not have reached out before now sent quick messages, short questions or generic requests. From a UX perspective, this worked exactly as intended.

From a business perspective, however, the picture was more complex. Many of the incoming messages lacked context, depth or clear intent. Compared to traditional contact forms or direct outreach, the inquiries were noticeably less specific and less actionable.

This doesn’t mean the chatbot failed. It means it changed the type of interaction.

Why This Happens

Chatbots are designed for immediacy. They invite spontaneous communication, not reflection. A form asks users to think before submitting. A chatbot invites them to start typing.

In addition, SEO-driven traffic plays a role. Chatbots often attract users earlier in their journey, sometimes before a real need or decision has formed. The result is more conversations, but fewer qualified ones.

This creates a learning curve - not only for the AI, but for the organisation using it.

The Learning Curve Is Real

After launching the chatbot, it became clear that success is not about switching the tool on, but about continuously refining how it is used.

Questions such as:

• What types of inquiries should the chatbot encourage?

• Where should it guide users instead of engaging them?

• How can early-stage interest be filtered without losing accessibility?

These questions don’t have one-time answers. They require iteration, data analysis and alignment with internal processes.

Chatbots Create Signals, Not Answers

One key insight from our experience: chatbots are excellent at generating signals. They show what users are curious about, where confusion exists and which topics attract attention.

But signals are not the same as qualified leads. Turning interaction into value requires structure, context and follow-up processes. Without that, volume remains volume.

What This Means for Companies

Launching a chatbot is not a shortcut to better customer interaction. It is a strategic decision that reshapes how and when users engage.

Companies should ask:

• What role should the chatbot play in the customer journey?

• How will interaction quality be measured, not just quantity?

• Which processes are needed to turn conversations into insight?

Chatbots are powerful tools - but only when expectations are realistic and processes are prepared.

Our Takeaway

More chats are not automatically better chats.The real value lies in understanding what those interactions reveal and how they can be integrated into a broader strategy.

Like most AI tools, chatbots don’t replace thinking. They make it more necessary.