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Klaviyo Data Science Podcast EP 45 | SegmentsAI: An AI Case Study on Delivering Value

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Manage episode 404598607 series 3251385
Content provided by Klaviyo Data Science Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Klaviyo Data Science Team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

In many ways, 2023 was the year of AI in tech, which is a double-edged sword. On the one hand, the basic technology is straightforwardly exciting — but on the other hand, with seemingly every technology solution scrambling to integrate a thin wrapper around ChatGPT, it’s hard to stand out in a saturated environment. This month on the Klaviyo Data Science Podcast, we dive into a case study of how to build AI products, SegmentsAI, and discuss the principles that go into making sure your AI-powered product shines — and, more importantly, actually helps your customers. You’ll hear about:

  • How to know when AI is the right solution for the problem
  • The unique technical challenges that come with building an AI product, from user testing to validation
  • The answer to the AI chicken-and-egg problem

“Why do this, why build another LLM feature? It seems like every website is rushing to get their name next to AI... How you break through the noise is to actually provide value to people, not novelty. Being able to help customers speed up or generate new, interesting segments that they otherwise wouldn’t? I think that’s valuable.”— Rob Huselid, Senior Data Scientist

For the full show notes, including who's who, see the ⁠⁠⁠⁠⁠Medium writeup⁠⁠⁠⁠⁠.

  continue reading

58 episodes

Artwork
iconShare
 
Manage episode 404598607 series 3251385
Content provided by Klaviyo Data Science Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Klaviyo Data Science Team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

In many ways, 2023 was the year of AI in tech, which is a double-edged sword. On the one hand, the basic technology is straightforwardly exciting — but on the other hand, with seemingly every technology solution scrambling to integrate a thin wrapper around ChatGPT, it’s hard to stand out in a saturated environment. This month on the Klaviyo Data Science Podcast, we dive into a case study of how to build AI products, SegmentsAI, and discuss the principles that go into making sure your AI-powered product shines — and, more importantly, actually helps your customers. You’ll hear about:

  • How to know when AI is the right solution for the problem
  • The unique technical challenges that come with building an AI product, from user testing to validation
  • The answer to the AI chicken-and-egg problem

“Why do this, why build another LLM feature? It seems like every website is rushing to get their name next to AI... How you break through the noise is to actually provide value to people, not novelty. Being able to help customers speed up or generate new, interesting segments that they otherwise wouldn’t? I think that’s valuable.”— Rob Huselid, Senior Data Scientist

For the full show notes, including who's who, see the ⁠⁠⁠⁠⁠Medium writeup⁠⁠⁠⁠⁠.

  continue reading

58 episodes

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