Robb FahrionGuest
Karl StaibHost
We use AI, um, for a lot of those different, like, data aggregation, uh, reporting being another one, right? So, like, I'll just have operational reports that aren't performance-based, but hey, it's coming from our, uh, VP of SEO to show here's how the last month looked like, and all of that data, we use Claude with APIs, uh, pulls out that data, and then we have structured, basically, reports that it starts to input the data into.

Um, because yeah, that was definitely one of the bottleneck that AI has alleviated for us, was, like, end-of-month reporting.

You know, we have 70-plus active recurring marketing clients, um, and that's a lot of reports to have to create at the end of the month.

So j- and a lot of it, a lot of the time wasn't in understanding what was going on, it was just getting the data, reformatting it, making it look pretty on the actual PowerPoint or slide deck that you were using to present to the client.

So now 70, 80% of that is being automated just through APIs and specific calls for specific information that we want on a monthly, quarterly basis, whatever it may be in terms of that time period.


It's just, "Oh yeah, we use it," but they don't think about integrating it into regular processes.

I love that you said monthly, 'cause it was like, yeah, like, now you've integrated this super smart, you know, computer and helps you process this stuff, and then it frees up bandwidth to do the other stuff.

Like, if you took where we were at a year ago, you know, we were almost getting to the point where we're max out to capacity.

We started leaning on AI and realized, wow, that just freed up 30, 40% of people's time that they were spending on stuff that, yeah, they're just, they are mundane tasks.

You're just kind of moving information from one place to the next, and you're still having to cross-reference the information.

You're still having to provide the context, and we still have to do that with the AI, but now it's just getting all of that kind of, you know, the blocking and tackling basic stuff done for you, um, which is absolutely beautiful and allows our team to spend more high-value time on, yeah, the strategy, what's working, what's not, how are we going to present this information to the client in a way that they can easily understand based on the context of their business as well.

... yeah, we have a lot of different clients, different verticals, right? So when it comes, some like it this way, or some we need to use this type of jargon just based on their understanding or level.

We use AI, um, for a lot of those different, like, data aggregation, uh, reporting being another one, right? So, like, I'll just have operational reports that aren't performance-based, but hey, it's coming from our, uh, VP of SEO to show here's how the last month looked like, and all of that data, we use Claude with APIs, uh, pulls out that data, and then we have structured, basically, reports that it starts to input the data into.

Um, because yeah, that was definitely one of the bottleneck that AI has alleviated for us, was, like, end-of-month reporting.

You know, we have 70-plus active recurring marketing clients, um, and that's a lot of reports to have to create at the end of the month.

So j- and a lot of it, a lot of the time wasn't in understanding what was going on, it was just getting the data, reformatting it, making it look pretty on the actual PowerPoint or slide deck that you were using to present to the client.

So now 70, 80% of that is being automated just through APIs and specific calls for specific information that we want on a monthly, quarterly basis, whatever it may be in terms of that time period.


It's just, "Oh yeah, we use it," but they don't think about integrating it into regular processes.

I love that you said monthly, 'cause it was like, yeah, like, now you've integrated this super smart, you know, computer and helps you process this stuff, and then it frees up bandwidth to do the other stuff.

Like, if you took where we were at a year ago, you know, we were almost getting to the point where we're max out to capacity.

We started leaning on AI and realized, wow, that just freed up 30, 40% of people's time that they were spending on stuff that, yeah, they're just, they are mundane tasks.

You're just kind of moving information from one place to the next, and you're still having to cross-reference the information.

You're still having to provide the context, and we still have to do that with the AI, but now it's just getting all of that kind of, you know, the blocking and tackling basic stuff done for you, um, which is absolutely beautiful and allows our team to spend more high-value time on, yeah, the strategy, what's working, what's not, how are we going to present this information to the client in a way that they can easily understand based on the context of their business as well.

... yeah, we have a lot of different clients, different verticals, right? So when it comes, some like it this way, or some we need to use this type of jargon just based on their understanding or level.
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