From the granular details of measuring intent and LLM-based chatbot effectiveness to the strategic implementation of AI across business units, Eric provides an in-depth analysis on the importance of data-driven decisions in the era of AI transformation.

Join us as we discuss how businesses can leverage analytics to optimise customer interactions, the common pitfalls in current AI strategies, and the future of AI in customer service.

In this episode

00:00 Introduction and UNPARSED conference - Find out more at https://unparsedconf.com

4:32 Welcom Eric Griffing

7:25 Best practice for measuring LLM agents

12:10 Differences tracking ML and LLM bots

14:00 Goal completion

19:00 What's missing

22:00 How to set up tracking on chatbots

24:50 Tracking LLM chatbots

30:37 Air Canada's chatbot issues

33:38 LLM guardrails

37:00 Using data to inform your AI strategy

41:00 Effort over satisfaction

44:30 Tracking customer effort in chatbots

48:40 Market demand for AI analytics

55:40 Wrap up

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Learn more from Dashbot:

https://www.dashbot.io/blog/360-bot-framework

https://www.dashbot.io/blog/inside-the-black-box-analyzing-your-llm-bot

https://www.dashbot.io/blog/navigating-the-shift-from-intent-based-to-language-model-chatbots

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