Novela

@kyrylosilin Thanks, Kyrylo! So, the scenarios are based on my own experiences working with brands over the last 15 years. The scenario in our free trial is based on my time working as the strategy lead for a luxury retailer. We refresh the product frequently, but what we're always looking at is the core learning objective we want to achieve. As one of our customers put it (better than I could), "It teaches people to drive, not to drive a specific car." If we chase every single update from Google/Meta, we lose sight of what we're really trying to achieve. We follow the updates and we weigh up whether adding new changes would add to or detract from the learning, then we take the call. Oh, there have been unexpected challenges! One of the hardest parts is to balance lifelike realism (in the data and the auction) with a clear educational experience. Often, reality is confusing and we don't want to spoonfeed people easy lessons. Equally, if they are confused then they aren't learning much. So, I found it tricky to work through this - our auction is complex and we use a lot of data to simulate market conditions. It was also challenging to implement AI for in-the-moment feedback. It needs to be contextually relevant and clear, as feedback is fundamental to learning. Getting the AI to be flexible enough to adapt to each user, without veering off in other directions, took some work too! Thanks so much for your interest in what we're building :-) Clark

@djordjevic_nikola Thank you, Nikola! We really appreciate the support :-)

@nadia_horwood How very kind of you, Nadia! It has been a pleasure for us to work with you and the team! :-) Clark

@tony_creator Thank you, Tony! That is precisely it: we've been involved in online education for a while now and the passive, video-driven methods are truly ineffective. We believe our approach is the future of online learning and we're thrilled to share our journey so far with all of you!

@emma_schneider Thank you, Emma! Very much appreciated :-)

@rohitk35 Thank you, Rohit! We use AI in a number of areas: we have AI customer personas, which the students can interact with to understand their brand's market positioning and to decide which customer segments to target. These are built using a database of real customer data across demographics, psychographics, and behavioral dimensions. We then have a co-pilot in the product called Ela (she's the one in our logo!) Ela gives feedback during the simulation and helps students break down complex problems. And then of course, we use AI in our ad analysis system, which judges the quality of a student's campaign and dictates their performance in our competitive auction! Clark