Retail and
consumer goods

At Algorithma, we empower retailers to enhance customer experiences and drive sales through AI. Our solutions enable personalized recommendations, dynamic pricing, demand forecasting, and market basket analysis, helping retailers optimize inventory, improve customer loyalty, and increase profitability. By leveraging data-driven insights, we support smarter decision-making and a more competitive edge in the retail market.

“ Embracing AI in retail isn’t just a trend—it’s essential. By combining cutting-edge AI with human creativity, retailers can craft personalized shopping experiences. With smart demand forecasting, efficient inventory management, and dynamic price optimization, businesses can boost sales, reduce waste, and stay ahead of the competition.”

Anna Samuelsson, Data Scientist

How AI can be applied in the sector

  • AI enhances personalization in retail by analyzing customer data to deliver tailored product recommendations, individualized offers, and dynamic shopping experiences. This technology enables retailers to predict preferences and provide personalized customer service, ultimately driving sales, engagement and loyalty.

  • AI transforms inventory management in retail by optimizing stock levels, predicting demand, and automating replenishment processes. This technology reduces costs from overstocking and stockouts while improving customer satisfaction through better product availability and data-driven decision-making.

  • AI enhances price optimization in retail by enabling dynamic, data-driven pricing strategies that maximize profitability and customer satisfaction. By analyzing factors like demand, competition, and inventory levels, AI allows retailers to adjust prices in real-time, improve margins, and personalize offers. This technology helps retailers respond quickly to market changes, ensuring competitive positioning and better overall revenue management.

  • We use AI to identify complex purchase patterns and product associations that might be missed by traditional methods. By analyzing transaction data, AI enables retailers to optimize product placement, create targeted promotions, and enhance cross-selling strategies, ultimately boosting sales and improving the shopping experience.

Our latest thinking

Complete library
Beyond deployment: Embracing AI sustainment for lasting value
Beyond deployment: Embracing AI sustainment for lasting value

Deploying AI systems is just the beginning. To create business impact and realize value, these systems must be sustained to remain reliable, adaptive, and compliant over time. AI sustainment is a strategic approach to extend the lifecycle of AI models, ensuring they are performant, scalable, and aligned with business needs. Algorithma emphasizes a proactive methodology that continuously improves models, manages data effectively, and follows responsible AI guidelines—maximizing value and maintaining a competitive edge.

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Navigating data drift to future-proof your ML models
Navigating data drift to future-proof your ML models

Companies are increasingly relying on machine learning models to make critical decisions. ML models come with a fundamental assumption: they expect the future to look like the past. In reality, the world is constantly changing, and so is the data it generates. This change, known as data drift, can silently undermine the performance of your models, leading to poor decisions, increased costs, and missed opportunities.

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Building the algorithmic business: Machine learning and optimization in decision support systems
Building the algorithmic business: Machine learning and optimization in decision support systems

The ability to leverage the combined strengths of machine learning and optimization to enhance decision-making processes can significantly transform business operations. By integrating these technologies, businesses can achieve increased efficiency, reduce operational costs, and improve overall outcomes. This transformative potential is realized through practical applications in decision-making, whether by supporting human decisions or performing them autonomously.

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Some of our experts

Team
Anna Samuelsson
Anna Samuelsson

AI Leader

Emely Wiegand
Emely Wiegand

Data Scientist

Jonas Röst
Jonas Röst

Data Scientist

Simon Althoff
Simon Althoff

Data Scientist

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