Below is a summary of our interview with Alex Galkin. You can listen to the full interview using the embedded media player below or in your favorite podcast app (e.g., Apple Podcast, Spotify and Amazon Music).




In our recent Pricing Heroes podcast episode, we had the pleasure of speaking with Alex Galkin, the Founder and CEO of Competera. With a background in engineering and a passion for AI, Alex brings a unique perspective to the retail pricing landscape. He shares his journey, the evolution of pricing tools, and the future of AI in retail pricing.

To learn more about the future of AI pricing in retail, get a free copy of the Coresight report discussed in this episode of Pricing Heroes: Future of Pricing: How AI is Transforming Retail Pricing.

From Engineer to Pricing Innovator

Alex Galkin’s journey began in Ukraine, where he earned diplomas in computer science and med tech science. His early work involved training computers to recognize smells using neural networks—a precursor to the advanced AI technologies we see today. His experience laid the foundation for his future endeavors in AI and pricing.

"I started using the first neural networks back in 2004, when I trained a computer to smell" Alex shared. "This was seven years before Google acquired distributed neural networks and AI started to take off."

Alex’s career took a turn when he joined one of the big four consulting firms. He noticed a significant gap: traditional pricing methods, which relied heavily on spreadsheets and simple elasticity calculations, were inadequate for modern retail needs. This realization sparked the idea to build a solution to revolutionize retail pricing with data and AI.

Evolution of Pricing Tools

Before the advent of sophisticated AI tools, retail pricing was a manual and often cumbersome process. Early software focused on price automation, using basic logic and limited data. Alex explains that these systems were only marginally better than manual methods, often leading to inefficient pricing strategies.

"Many retailers still use Excel," Alex noted. "Category managers tweak formulas without a comprehensive understanding of performance, leading to suboptimal pricing decisions."

The introduction of elasticity-based pricing brought some improvements, allowing for more nuanced strategies. However, these methods still fell short, primarily relying on internal data and simple assumptions about customer buying behavior.

The Impact of AI on Retail Pricing

AI has transformed retail pricing by considering more pricing and non-pricing factors than humanly possible and providing real-time market insights. Alex highlighted that modern AI tools, like Competera’s own pricing platform, consider 20+ factors beyond elasticity, including local market conditions, seasonality, and customer behavior.

"AI allows us to make pricing decisions based on a comprehensive understanding of the market," Alex explained. "It's not just about elasticity; it's about understanding the entire context."

This shift towards AI-driven pricing has not been seamless. Retailers initially faced challenges in adopting these technologies, including high computational costs, poor data quality, and a lack of trust in AI models. However, as computation has become more efficient and data collection has improved, more retailers are recognizing AI’s value for setting and maintaining optimal price positions.

Overcoming Challenges and Building Trust

One significant barrier to AI adoption is the perception of AI as a "black box." Retailers are understandably cautious about relying on opaque algorithms for crucial pricing decisions. Alex explains that there are ways around this issue. For example, Competera addresses this by providing clear explanations for price changes, highlighting key factors that influence decisions.

"We ask our models why they suggest a price change," Alex said. "We provide transparent reasons, such as cannibalization through competition or seasonality, to build trust with our clients.

The Role of Pricing Analysts in the AI Era

With AI handling the complexities of pricing, the role of pricing analysts is evolving. Alex envisions a future where pricing functions are more integrated and strategic, with fewer manual tasks and more focus on business critical decision-making.

"Pricing analysts will still be needed, but their roles will change," Alex noted. "They will become more like pricing architects, overseeing automated systems and focusing on strategic insights."

Advice for Retailers

For retailers hesitant to adopt AI, Alex’s advice is clear: invest in data foundations. A robust data infrastructure is crucial for leveraging AI effectively. Without accurate and comprehensive data, even the best AI models will fall short.

"Increase investments in data foundations," Alex urged. "Ensure your data is clean, comprehensive, and ready for AI integration."

Looking Ahead: The Future of Retail Pricing

Alex is optimistic about the future of retail pricing. He envisions a landscape where operational expenses are minimized and prices are finely tuned to customer needs. Competera is at the forefront of this transformation, developing tools that automate 98% of pricing decisions, leaving only the most complex cases to human analysts.

"Our goal is to make pricing as efficient and effective as possible," Alex concluded. "With AI, retailers can achieve better margins, improve customer satisfaction, and gain a competitive edge."

Competera is also excited about launching a new product, Competera X, designed for smaller retailers on platforms like Google, Amazon, and Shopify. This freemium product aims to democratize access to advanced AI pricing tools, showcasing Competera’s commitment to innovation and accessibility.

"We’re giving away significant compute power and data insights for free," Alex explains. "It's a huge step towards making AI-driven pricing accessible to more retailers."

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