💡 Customers were unhappy with products, leading to the establishment of the Customer and Partner Experience Team to address issues and gather data.

💡 Analyzing data helped reduce the return rate of mobile devices from 80% to 20% by understanding customer needs and making practical changes.

💡 Data science revealed the five key things customers wanted in a phone: making calls, stability, battery life, email access, and calendar management.

💡 Influencers for product recommendations are not limited to famous individuals but can include professionals in specific micro-communities, like plumbers and doctors.

💡 Large language models, such as GPT, predict the next word or pattern of words, providing convenience but lacking insight and creativity.

In this episode 136 of "Failing to Success", Bob Rapp, principal AI architect at Envorso, discusses his experiences in data science and customer experience. He shares insights from his time at Microsoft, where he worked on addressing customer dissatisfaction with products and reducing the high return rate of mobile devices. Through data analysis, they identified the five key features customers desired in a phone. Bob emphasizes the surprising influence of professionals like plumbers and doctors in recommending products within their micro-communities. He also discusses the capabilities and limitations of large language models like GPT, which predict the next word but lack deeper insights and creativity. Bob concludes by highlighting his current work at Envorso, where he collaborates with software and automotive experts to enhance user experiences and transform auto companies into software-driven entities.

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Timestamps:

00:00:00 Intro

00:00:04 When Microsoft Came Calling

00:02:28 Building the First Android Phones with Samsung

00:05:00 Redefining "Influencer"

00:06:40 LLMs (Large Language Models)

00:10:19 Favorite AI Tools

00:15:00 What is Envorso?

00:16:51 Tesla and the Ford F150 Lightning

00:19:12 Contact Bob