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The Metrics Resurrections: Action! Action! Action!

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Manage episode 423218799 series 3474148
Contenido proporcionado por HackerNoon. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente HackerNoon o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/the-metrics-resurrections-action-action-action.
User Reported Metrics, while important for assessing user perception, are difficult to operationalize due to their unstructured nature.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #llms, #conversational-ai, #ai-applications, #ai-agents, #google-assistant, #user-reported-metrics, #hackernoon-top-story, #user-perceived-metrics, and more.
This story was written by: @pmukherjee. Learn more about this writer by checking @pmukherjee's about page, and for more stories, please visit hackernoon.com.
User Reported Metrics, while important for assessing user perception, are difficult to operationalize due to their unstructured nature. However, recent advancements in LLMs allow for the conversion of unstructured user feedback into structured, actionable metrics. This enables teams to better prioritize performance improvement projects by assessing their impact on user perception alongside system-level metrics. While not foolproof, this combined approach provides a more comprehensive understanding of the effectiveness of changes made to conversational AI agents. It's crucial to remember that both types of metrics are valuable for accurately assessing and improving user perception.

  continue reading

472 episodios

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Manage episode 423218799 series 3474148
Contenido proporcionado por HackerNoon. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente HackerNoon o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/the-metrics-resurrections-action-action-action.
User Reported Metrics, while important for assessing user perception, are difficult to operationalize due to their unstructured nature.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #llms, #conversational-ai, #ai-applications, #ai-agents, #google-assistant, #user-reported-metrics, #hackernoon-top-story, #user-perceived-metrics, and more.
This story was written by: @pmukherjee. Learn more about this writer by checking @pmukherjee's about page, and for more stories, please visit hackernoon.com.
User Reported Metrics, while important for assessing user perception, are difficult to operationalize due to their unstructured nature. However, recent advancements in LLMs allow for the conversion of unstructured user feedback into structured, actionable metrics. This enables teams to better prioritize performance improvement projects by assessing their impact on user perception alongside system-level metrics. While not foolproof, this combined approach provides a more comprehensive understanding of the effectiveness of changes made to conversational AI agents. It's crucial to remember that both types of metrics are valuable for accurately assessing and improving user perception.

  continue reading

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