Artificial Intelligence is changing the landscape of modern commerce. In our next session, we’ll interview Dr. Jay van Zyl, to discuss the practical applications of integrating AI technologies into your business. Dr. van Zyl begins by explaining why AI is essential to business, citing its ability to automate mundane tasks, identify patterns and trends, and [...]
Responding to customers requires an understanding of the ever-changing human contexts in which they exist. It is important to remain knowledgeable and aware of current trends, industry changes, and the needs of customers. We will discuss methods of monitoring customer responses to experiments using dashboards and activating further dynamic experimentation in ecosystem.Ai.
Dynamic experimentation for customer recommendations in real-time is an innovative approach to providing customers with tailored recommendations based on their individual preferences. ecosystem.Ai uses a combination of machine learning and computational social science to predict customer behavior and provide personalized recommendations.
Using ecosystem.Ai, you can utilize the power provided by the easy to navigate low-code platform, real human behvaioral based algorithms, and a truly momentus real-time engine. Make all the right recommendations, and give your customers the attention they deserve.
There's no time like the present Live in the moment Be present This is not just guru magic for a better life. It is the philosophy that all businesses wanting to succeed with automated interventions, should follow.
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...
Bring your own daquiris, it's happy hour on the promenade! This week we are talking about nudges, progressive exposure, personalized info drops, and other behavioral techniques.
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).