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How SaaS Teams Can (and Can’t) Leverage AI for Customer Research

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Manage episode 445191404 series 3527720
Inhalt bereitgestellt von Forget the Funnel. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Forget the Funnel oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

AI is everywhere. We’re using it in our marketing, in our products, in our day-to-day task management. We’re all using it in one way or another.

But when it comes to learning from and understanding your customers and what drives them to make decisions, proceed with caution.

Here’s how we see it:

To grow revenue, you need to increase conversions. To increase conversions, you need to create better customer experiences. To create better customer experiences, you need to understand the why - that critical context that leads your customers to make the decisions they do.

Are AI tools capable of that? Cue the sad trombone. But - that doesn’t mean AI has no role to play in customer research. And that is what this latest episode of the pod is all about.

This week on Forget the Funnel, Georgiana takes on the 100-ton elephant in the room: whether AI can help us learn more about our customers.

Drawing from a recent months-long Custom GPT experiment and conversations with SaaS teams and colleagues, Georgiana shares her take on using it as a research tool.

Timestamps
02:10
— What is the role of AI in customer research? Georgiana explores this burning topic and gives examples of what AI can and cannot do.

05:00 — Georgiana explains why the results of their Custom GPT research experiment fell flat and why they needed a human to connect the dots.

10:16 — Georgiana highlights the importance of foundational customer intelligence and explains why customer knowledge shouldn’t be guesswork but insight-driven, especially when integrating AI.

13:51 — She discusses how AI helped her leverage a large set of customer surveys and interpret their results.

17:10 — She breaks down the potential risks of using AI for customer research, privacy policy issues, and other potential threats.

19:06 — She finishes off by sharing the current stage of experiments and goals for collaborating with AI in customer research.

Links

Previous Episodes

  continue reading

21 Episoden

Artwork
iconTeilen
 
Manage episode 445191404 series 3527720
Inhalt bereitgestellt von Forget the Funnel. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Forget the Funnel oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

AI is everywhere. We’re using it in our marketing, in our products, in our day-to-day task management. We’re all using it in one way or another.

But when it comes to learning from and understanding your customers and what drives them to make decisions, proceed with caution.

Here’s how we see it:

To grow revenue, you need to increase conversions. To increase conversions, you need to create better customer experiences. To create better customer experiences, you need to understand the why - that critical context that leads your customers to make the decisions they do.

Are AI tools capable of that? Cue the sad trombone. But - that doesn’t mean AI has no role to play in customer research. And that is what this latest episode of the pod is all about.

This week on Forget the Funnel, Georgiana takes on the 100-ton elephant in the room: whether AI can help us learn more about our customers.

Drawing from a recent months-long Custom GPT experiment and conversations with SaaS teams and colleagues, Georgiana shares her take on using it as a research tool.

Timestamps
02:10
— What is the role of AI in customer research? Georgiana explores this burning topic and gives examples of what AI can and cannot do.

05:00 — Georgiana explains why the results of their Custom GPT research experiment fell flat and why they needed a human to connect the dots.

10:16 — Georgiana highlights the importance of foundational customer intelligence and explains why customer knowledge shouldn’t be guesswork but insight-driven, especially when integrating AI.

13:51 — She discusses how AI helped her leverage a large set of customer surveys and interpret their results.

17:10 — She breaks down the potential risks of using AI for customer research, privacy policy issues, and other potential threats.

19:06 — She finishes off by sharing the current stage of experiments and goals for collaborating with AI in customer research.

Links

Previous Episodes

  continue reading

21 Episoden

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