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Slaven

Slaven Bogdanovic, PhD

Sr. Data Scientist

About Slaven

Slaven started his career in market research, where he worked on product and price optimization for clients in the Fast-Moving Consumer Goods (FMCG) industry. He played a pivotal role in managing projects for some of the agency’s fast-growing clients. Over time, his interests led him to customer satisfaction research, where he specialized in segmentation studies.

Slaven then honed his business intelligence and data science skills, with a focus on improving workforce effectiveness. His approach combines statistical and econometric methods with advanced machine learning techniques. He has expertise in using tools such as Tableau, R, and Python to analyze and interpret data effectively.

Slaven has a Ph.D. in research psychology, where he specialized in quantitative methods. This has provided him with a solid foundation in analytical techniques. He completed his graduate studies in psychology at the Faculty of Philosophy at the University of Belgrade.

Recent Articles

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Turn Pricing Data Into Profit

Are you confident you’re getting full value from your pricing and discounting—or is margin quietly drifting? For most manufacturers and distributors, the answer is buried

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The Executive’s Guide to Surge Pricing and Dynamic Pricing Models

While many executives associate surge pricing with Uber or airlines, its real untapped potential lies within B2B industries still reliant on static, annual price lists. This guide unpacks how dynamic pricing models move beyond “cost-plus” formulas, allowing businesses to respond intelligently to market shifts, protect margins from volatile costs, and capture otherwise lost revenue. From manufacturing and distribution to retail, learn how to leverage your data to implement a pricing strategy that boosts profitability and agility.

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AI Won’t Fix Your Pricing Strategy. This Will.

While many leaders are seduced by the promise that a sophisticated AI tool can solve their pricing problems, this illusion of innovation is a dangerous trap. A fancy algorithm will never substitute for a sound, human-led strategy, a solid data foundation, and strong commercial execution. Lasting success comes not from outsourcing your thinking to a black box, but from building a durable, in-house capability that empowers your team to win.

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