{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/c55dad53fc3542b9a96d54e93a3026ee\" frameborder=\"0\" width=\"1918\" height=\"1438\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1438,"width":1918,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1438,"thumbnail_width":1918,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/c55dad53fc3542b9a96d54e93a3026ee-2013f8e9200ca722.gif","duration":212.907,"title":"Docs | What is Data Enrichment?","description":"In this video, I discuss how Dimension Labs utilizes AI enrichment to enhance conversational data, specifically focusing on our analysis of a chatbot with approximately 1,500 sessions. Over a three-month period, we identified that around 100 of these conversations per month are categorized as high effort for users. We achieve this by employing prompts as data enrichment tasks for large language models, which help us evaluate the effort score of each conversation. I encourage you to consider how we can leverage these insights to improve user experience and streamline our interactions. Please feel free to reach out if you have any questions or need further clarification on this process."}