As the level of competition increases, pricing optimization is gaining a central role in most mature insurance markets, forcing insurers to optimise their rating and consider customer behaviour; the modeling scene for the latter is one currently dominated by frameworks based on Generalised Linear Models (GLMs). In this paper, the authors explore the applicability of novel machine learning techniques such as tree boosted models to optimise the proposed premium on prospective policyholders. Given their predictive gain over GLMs, the authors carefully analyse both the advantages and disadvatanges induced by their use. Continue reading
The reality is that Machine Learning as a concept is as old as computing itself. As early as 1950, Alan Turing was asking the question, “Can computers think?” In 1969, Arthur Samuel helped define machine learning specifically by stating, “[Machine Learning is the] field of study that gives computers the ability to learn without being explicitly programmed.”
While the concept has been around for more than half a century, we have finally reached a point in technological advancement where hardware and software can actually help developers match their aspirations with tangible reality. This development has led to not only the rise of machine learning and AI advancements, but, more importantly, also advancements inexpensive enough for anyone to use. Continue reading
The advent of new algorithms, faster processing and massive, cloud-based data sets is making it possible for companies in all industries to experiment with artificial intelligence (AI). And while marketing and sales are particularly ripe for innovation, it’s still early days for adoption. Brands and agencies are working together to navigate a web of quickly evolving solutions.
This report is a great example of eMarketer data and insight that explain the current state of the market for AI, the forces that are driving the market forward and best practices for marketers interested in putting AI to work. Continue reading
This book has been written specifically for marketers. It teaches how to use AI to improve marketing efficiency. The book includes definitions of AI terms, illustrations, case studies for all marketing components: the customer journey, marketing mix, customer lifetime value, marketplace segmentation, social media engagement, merchandising, customer service , etc.
Soon one of the first conferences on the technology of applying artificial intelligence in marketing will take place. The Digiday AI Marketing Summit will dive deep into how marketers can understand and use artificial intelligence and machine learning. Brand and agency leaders will share how they’re using this new technology for everything from shifting how media dollars are deployed, to customer service, to using AI for content curation. Continue reading
Do you look for the most complete text book to understand A.I. tools for marketing? Below is one of the first such books.
The author provides the definition of algorithmic marketing, makes review of predictive modeling, tells about artificial intelligence for advertisements, pricing and product assortiment. So it is one of the first book that describes all marketing tools through machine learning. Continue reading