Dynamic pricing through data science
Dynamic pricing through data science
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Data science can be used to optimise prices and help retailers reach a wider audience. This video explains some of the different methods that exist to do so, and presents some examples of machine learning and AI being used for dynamic pricing.
This video has been produced by the Tesseract Academy (tesseract.academy), a company that educates decision makers in deep technical topics such as data science, analytics, machine learning and blockchain.
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About Dr Kampakis
Dr Stylianos (Stelios) Kampakis is a data scientist and tokenomics expert with more than 10 years of experience.
He has worked with companies of all sizes: from startups to organisations like the US Navy, Vodafone and British Land. His work expands multiple sectors including fintech, sports analytics, health-tech, general AI, medical statistics, predictive maintenance and others.
He has worked with many different types of technologies, from statistical models, to deep learning, to large language models. He has 2 patents pending to his name, and has published 3 books on data science, AI and data strategy.
He has helped many people follow a career in data science and technology.
His seminal work in token economics has led to many successful token economic designs using tools such as agent based modelling and game theory.
He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School and CEO of The Tesseract Academy.
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Пікірлер: 13
Very clear presentation. Thank you for this great content
Clear explanation on Dynamic prices and how to optimize with same good examples.
Very clear and engaging, thank you for sharing
Hi Stelios, fantastic video, I'm getting a lot of ideas for the work that I'm doing right now for the US company giant that recently started adopting digitalization in their business. Thank you for sharing.
@stylianoskampakis5208
3 жыл бұрын
Thank you Milan. Feel free to reach out to me at stelios@thedatascientist.com
Thank you very much
2:54 i think there is mistake on the slide where it says "lower elasticity of demand". It should be either "lower ability to pay", or "great elasticity of demand". Why? Because when you lower the price, that has positive effect in term of attracting buyers who otherwise weren't able to pay the regular price. That means there is an "additional" demand which is reacting to this change, hence it is elastic. On the other hand "lower elasticity of demand" as it is written means vertical line, hence no alternatives for buyers when the prices goes up and the high price must be payed, that is inelastic demand, and in this scenario the units are rather low.
How do you solve problem of me telling you that I bought same thing as you did but in almost half price ?
Why apple does not have dynamic pricing?
Showing different users different prices at the same time is kind of discrimination, isn't it?
Uber is the worst example you could use. The whole industry is highly improfitable with horrible losses. Founded in 2008 Uber never managed to be profitable. Same applies to competitors like Lyft. By the way Revenue Management has been implemented in the late 60s, not the 80s.
@stylianoskampakis5208
4 жыл бұрын
It remains one of the best examples of dynamic pricing. The video is about that, not about Uber's business model. It is also one of the most AI-driven companies. Would have it survived that long if that wasn't the case?
@frankfrohmann1504
4 жыл бұрын
Uber is a zombie company. There is a Harvard Professor who states the same. Dynamic Pricing in their case only led to losses. It´s the worst example on Pricing you can show. Point.