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In-Ear Insights: Generative AI Data Management Best Practices
In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss generative AI data management best practices and how to leverage qualitative data for content marketing. You will learn how to extract valuable customer questions from various sources like webinars and forums using AI. Discover effective methods to prioritize this wealth of information based on your ideal customer profile and keyword strategy. Finally, understand how to use AI tools to quickly generate content by referencing your existing materials and repurposing previous work.
Watch the video here:
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
https://traffic.libsyn.com/inearinsights/tipodcast-generative-ai-data-management-best-practices.mp3
Download the MP3 audio here.
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Machine-Generated Transcript
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
Christopher Penn – 00:00
In this week’s In Ear Insights, let’s talk about the stuff you’ve got laying around, specifically data. Katie, one of the things you’ve said time and again, which is 100% accurate, is that data isn’t just numbers. Data is any information you have laying around. One of the things we try to do for our own marketing is make use of the data we have because we have so much of it. I’ve been collecting questions from webinars and things that we’ve done. Every time I’m speaking at a virtual event, I copy and paste the chat log because there’s a lot of people who have really good questions. As much as I would like to say, yeah, every question gets followed up afterwards, that doesn’t always happen, particularly if it’s not our event.
Christopher Penn – 00:46
I’ve been looking at our back catalog, and our back catalog of questions that we have left over from events is enormous. Hundreds and hundreds of questions. So, Katie, when you think about content marketing strategy and using AI to make use of the stuff we have laying around, why aren’t more companies, including us, to some degree, why aren’t more companies doing more with this enormous goldmine of data?
Katie Robbert – 01:24
In my experience, the qualitative data feels daunting to try and analyze. When you have the quantitative data, the numeric data, there’s something—at least this is the way that I’ve understood it. When I’ve worked with other data teams, it’s quote-unquote easier to put all of the numbers in a spreadsheet and get them to make sense. It’s not the same process for getting feedback and sentences and unstructured data. That’s the stuff that’s like, yeah, we totally should collect it, but we don’t know how to analyze it because it’s harder to— I guess, what am I trying to—basically, math is a language, but math is a language that isn’t open to interpretation.
There’s no slang, there’s no regional
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By Trust Insights
5
99 ratings
In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss generative AI data management best practices and how to leverage qualitative data for content marketing. You will learn how to extract valuable customer questions from various sources like webinars and forums using AI. Discover effective methods to prioritize this wealth of information based on your ideal customer profile and keyword strategy. Finally, understand how to use AI tools to quickly generate content by referencing your existing materials and repurposing previous work.
Watch the video here:
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
https://traffic.libsyn.com/inearinsights/tipodcast-generative-ai-data-management-best-practices.mp3
Download the MP3 audio here.
[podcastsponsor]
Machine-Generated Transcript
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
Christopher Penn – 00:00
In this week’s In Ear Insights, let’s talk about the stuff you’ve got laying around, specifically data. Katie, one of the things you’ve said time and again, which is 100% accurate, is that data isn’t just numbers. Data is any information you have laying around. One of the things we try to do for our own marketing is make use of the data we have because we have so much of it. I’ve been collecting questions from webinars and things that we’ve done. Every time I’m speaking at a virtual event, I copy and paste the chat log because there’s a lot of people who have really good questions. As much as I would like to say, yeah, every question gets followed up afterwards, that doesn’t always happen, particularly if it’s not our event.
Christopher Penn – 00:46
I’ve been looking at our back catalog, and our back catalog of questions that we have left over from events is enormous. Hundreds and hundreds of questions. So, Katie, when you think about content marketing strategy and using AI to make use of the stuff we have laying around, why aren’t more companies, including us, to some degree, why aren’t more companies doing more with this enormous goldmine of data?
Katie Robbert – 01:24
In my experience, the qualitative data feels daunting to try and analyze. When you have the quantitative data, the numeric data, there’s something—at least this is the way that I’ve understood it. When I’ve worked with other data teams, it’s quote-unquote easier to put all of the numbers in a spreadsheet and get them to make sense. It’s not the same process for getting feedback and sentences and unstructured data. That’s the stuff that’s like, yeah, we totally should collect it, but we don’t know how to analyze it because it’s harder to— I guess, what am I trying to—basically, math is a language, but math is a language that isn’t open to interpretation.
There’s no slang, there’s no regional
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