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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how large language models with perfect memory can assist with competitive analysis. They explain how these tools can quickly synthesize vast amounts of public data to provide insights into competitors’ offerings, differentiation, and performance. Katie and Chris note the importance of keeping your own data fresh so tools have current info. They give examples of how to leverage these models, from summarizing competitors’ businesses to analyzing website design and content. Katie and Chris emphasize combining machine learning with human expertise to ask the right questions. They advise using AI for competitive analysis as one more tool, along with classic techniques like regression analysis.
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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
In this week’s In-Ear Insights, competitive analysis is nothing new, we have been doing competitive analysis since the first stall opened at a bazaar in the Middle East.
And when guys look at the other guy’s booth going, hey, those figures look better than mine.
However, we are in a totally new environment now, where you have massive databases, which are essentially what large language models are with perfect memory, meaning that they know so much about an entire landscape.
It with that perspective, knowing that these things have perfect memory and a much bigger point of view than any one person is going to carry around.
Katie, what do you think about how that changes? Competitive analysis? What do you think about how we should be thinking about these tools as a, as a assistant, to helping us be better at competitive analysis?
So John, and I were talking about this at a very high level on last week’s live stream.
And the thing that struck me was that there is an opportunity to think about how do we include artificial intelligence as a set of data points in the competitive analysis.
And so you know, so you have to step back first and figure out where artificial intelligence works in your organization.
And then what it’s actually doing.
And so, you know, for example, if we’re at a very high level, you know, let’s say Trust Insights is generating 90% of their content, using generative AI, does our main competitor want to be a
By Trust Insights5
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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how large language models with perfect memory can assist with competitive analysis. They explain how these tools can quickly synthesize vast amounts of public data to provide insights into competitors’ offerings, differentiation, and performance. Katie and Chris note the importance of keeping your own data fresh so tools have current info. They give examples of how to leverage these models, from summarizing competitors’ businesses to analyzing website design and content. Katie and Chris emphasize combining machine learning with human expertise to ask the right questions. They advise using AI for competitive analysis as one more tool, along with classic techniques like regression analysis.
[podcastsponsor]
Watch the video here:
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
Download the MP3 audio here.
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
In this week’s In-Ear Insights, competitive analysis is nothing new, we have been doing competitive analysis since the first stall opened at a bazaar in the Middle East.
And when guys look at the other guy’s booth going, hey, those figures look better than mine.
However, we are in a totally new environment now, where you have massive databases, which are essentially what large language models are with perfect memory, meaning that they know so much about an entire landscape.
It with that perspective, knowing that these things have perfect memory and a much bigger point of view than any one person is going to carry around.
Katie, what do you think about how that changes? Competitive analysis? What do you think about how we should be thinking about these tools as a, as a assistant, to helping us be better at competitive analysis?
So John, and I were talking about this at a very high level on last week’s live stream.
And the thing that struck me was that there is an opportunity to think about how do we include artificial intelligence as a set of data points in the competitive analysis.
And so you know, so you have to step back first and figure out where artificial intelligence works in your organization.
And then what it’s actually doing.
And so, you know, for example, if we’re at a very high level, you know, let’s say Trust Insights is generating 90% of their content, using generative AI, does our main competitor want to be a

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