Today, we are another episode in our series, sponsored by our good friends at Railsware. Railsware is a leading product studio with two main focuses - services and products. They have created amazing products like Mailtrap, Coupler and TitanApps, while also partnering with teams like Calendly and Bright Bytes. They deliver amazing products, and have happy customers to prove it.

In this series, we are digging into the company's methods around product engineering and development. In particular, we will cover relevant topics to not only highlight their expertise, but to educate you on industry trends alongside their experience.

In today's episode, we are speaking with Nika Tamayo Flores, Product Lead at Railsware, specifically for the Coupler product. She's been leading complex data-driven products for over eight years, and will enlighten us on conversational analytics, and how they can change a data focused product.

Questions:

Before we jump to the topic, let’s define what exactly conversational analytics is. How does it differ from traditional dashboard-based data analysis?
You’ve been integrating AI capacities into Coupler, Railsware’s product focused on data analytics. How would you describe data analytics in pre-AI and AI era?
What were the key challenges to embedding conversational analytics into Coupler?
And what’s the result? You’ve already released AI Insights – how do they transform user experience for data exploration?
How do you ensure conversational analytics provides accurate and reliable insights?
How does conversational analytics change who can be a "data user" in an organization?
What's the learning curve like for organizations adopting conversational analytics?
Where do you see conversational analytics heading - will it eventually replace traditional BI tools, or complement them?

Links

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