This session will cover the key principles behind building recommender systems that go beyond basic personalization, focusing on approaches that enhance user engagement and drive business results while keeping the human element at the forefront.
With the rise of personalisation came the expectation of personal accuracy - it is more important than ever to truly know your customers, and act accordingly. One of the key ways to achieve this is through understanding their Spend Personality. This approach is about understanding the nuanced ways in which people spend, offering [...]
This session will provide a clear and practical overview of the module’s features, with particular attention to the generative tools that drive its predictive capabilities.
Providing a superior customer experience and having a band of happy customers has not only become a crucial barometer of a company’s success. It’s also a major differentiating factor for consumers choosing who to spend their hard-earned money with. Customer happiness is typically captured with customer satisfaction (CSAT) and Net Promoter Scores (NPS) [...]
In our last blog post we discussed the importance of creating novelty through experimentation to keep your communities engaged. Today we’re going to discuss the benefits of low code technology to help data scientists get these experiments and predictions into production faster. Why choose low-Code technology? To keep [...]
It's our birthday... At least, we think it is ;) This week, let's be nostalgic and just hang out. Let's discuss all the coolest things we've discussed over the past many many many months. What struck you the most?
This week we are opening up the discussion about using low-code tools for complex machine-based tasks. What are the reasons we should pursue this, and what are the possible challenges? Consider Pi for a moment...
Open discussions about Behavioral Predictions, Real-Time Artificial Intelligence and Low-Code Environments for Machine Learning 7am (San Francisco). 8am (Denver). 9am (Chicago). 10am (New York). 3pm (London). 4pm (South Africa). 5pm (Eastern Europe).
Open discussions about Behavioral Predictions, Real-Time Artificial Intelligence and Low-Code Environments for Machine Learning 7am (San Francisco). 8am (Denver). 9am (Chicago). 10am (New York). 3pm (London). 4pm (South Africa). 5pm (Eastern Europe).
Open discussions about Behavioral Predictions, Real-Time Artificial Intelligence and Low-Code Environments for Machine Learning 7am (San Francisco). 8am (Denver). 9am (Chicago). 10am (New York). 3pm (London). 4pm (South Africa). 5pm (Eastern Europe).