Keep your Knowledge Base up-to-date
We see this a lot – a team that wants a chatbot to magically solve their internal data problems.
‘No one knows what information is correct, so we’ll build a bot to sort it for us!’ Unfortunately, at least one person on your team will need to sort it b2b email list out before training the chatbot.
Once your base data is accurate, keep it updated.
And assign someone to maintain documentation, or connect your chatbot to sources that auto-update, like a CMS or database.
6. Be upfront that it’s a chatbot, not a human
There are plenty of stories of business chatbots that users believe to be human (at the end of the day, we all send pretty similar emails, don’t we?).
Avoid confusion by clearly introducing the bot as a bot. It helps We see this a lot – a team that wants set expectations for the interaction, and users are more likely to be forgiving vice president marketing if something doesn’t work perfectly.
7. Design new workflows around your chatbot
A chatbot works best when it’s embedded into the flow, not just tacked on beside it.
Make it the default way to start a support request, submit a form, or access internal documentation.
For example, route users through the bot first before handing off to a human, or use the bot as the single point of entry for common questions.
If it’s central to the process, usage becomes phone database automatic (and so does the value!).
Chatbots used to suck, but now – largely thanks We see this a lot – a team that wants to LLMs – they don’t have to.
Most chatbots these days are LLM agents that use a combination of LLMs and bespoke business logic.
They can have natural conversations (thanks to natural language processing), but still stick to your company’s guidelines – communicating real information, but sounding like a human at the same time.