How Machine Learning and AI Can Help You Make Efficient Pricing Decisions with Alex Galkin

Alex Galkin is the Co-Founder and CEO of Competera, a pricing optimization SaaS company converting technologies into ready-to-use products for enterprise retailers worldwide. Alex has been a mentor at his startups for several years, and he’s a Ukrainian who left four days before the war started. In this episode, Alex helps us understand the pricing and ML work that they do at Competera as he talks about the three models they always put into use.   Why you have to check out today’s podcast: Understand why you should treat pricing as a process Find out how Competera helps their clients in making pricing decisions Discover three models that Competera puts into use as MLs look for reasonable factors to make a price adjustment   “Pricing is a process, and you need to continuously improve as any other process in your organization.” – Alex Galkin   Topics Covered: 01:04 – How Alex got into pricing 03:07 – The work that Competera does in relation to pricing, and how they do it 08:28 – Using ML-driven price recommendations: Competera creating a ‘gray box’ 12:35 – Talking about the portfolio-wide pricing/portfolio optimization 14:12 – An ML example of the decoy effect 17:20 – Alex explains how their smart product segmentation works; a product bringing more people in the store 23:09 – Alex’s pricing advice 23:49 – Connect with Alex     Key Takeaways: “ML is not a human. He’s not trying to play with the price; he's changing only if he sees the reasonable factor to make this price adjustment.” – Alex Galkin   People / Resources Mentioned: Competera: https://competera.net/   Connect with Alex Galkin: Email: [email protected] LinkedIn: https://www.linkedin.com/in/alexandrgalkin/   Connect with Mark Stiving: LinkedIn: https://www.linkedin.com/in/stiving/ Email: [email protected]