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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:
“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:
Connect with Alex Galkin:
Connect with Mark Stiving:
4.8
5050 ratings
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:
“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:
Connect with Alex Galkin:
Connect with Mark Stiving:
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