The Ultimate Power Couple: How AI & Expertise Are Transforming Category Management

May 14, 2024

By Harmonya 

The discipline of category management was built from decades of hard-won skills, methods, and intuition of experienced experts. These seasoned teams own the crucial responsibilities of optimizing product assortments, drawing and delivering planograms, informing promotional plans, and much more.

Their decision-making processes require a balance of historical sales data, years of personal expertise, and an instinctive grasp of consumer purchasing behaviors.

Thanks to this firm foundation of industry knowledge, we are witnessing a major shift as artificial intelligence (AI) becomes an integral partner to category management teams, giving them new tools to enhance their proven capabilities and talents.

AI isn’t just using online chatbots; it’s used to create tools that actively inform complex decisions and evaluate scenarios based on massive amounts of data, giving category managers access to differentiated insights at-scale.

The ultimate potential, however, lies in a true partnership between AI and the expertise of category managers, where machine learning’s analytical power and efficiency converge with our intuition, human expertise, and methodologies that have been honed over many years in the field.

These new AI-powered tools are giving rise to a new era of data-driven category strategy.

The AI Acceleration

AI excels at analyzing consumer trends and market changes at a previously unattainable scale. It can identify patterns and make connections we may otherwise miss.

With AI as a powerful analytical engine, category managers can now combine more up-to-date insights with their intuition and expertise. For instance, leading CPG companies are using AI to refine their consumer decision trees, enabling more targeted marketing and increased sales.

A leading multinational food company was struggling to understand the intricate drivers of their category performance and consumer behaviors. Traditional methods were insufficient in providing a holistic view of their extensive product lines. By using an AI-powered product data-enrichment platform, they were able to incorporate item-level data sets enriched with consumer-centric attributes which allowed them to conduct a deep dive into category performance.

The enriched data unveiled crucial insights into consumer preferences, highlighting underperforming areas and key drivers of success. As a result, the company realigned their strategies with these insights, leading to a sizable increase in category sales.

Stop Guessing, Start Knowing

This partnership with AI allows category managers to gain a deeper understanding of the hidden drivers behind performance of their brands, competitors, and categories.

AI-driven natural language processing and machine learning techniques process massive data streams – customer reviews, product listings, internal data, and more – to deliver actionable insights into emerging trends.

For example, a global beverage manufacturer faced challenges in effectively optimizing their diverse product assortment. Using AI-enriched product data enabled them to uncover and group products based on detailed consumer-based attributes such as benefits, flavors, and packaging preferences.

This precise segmentation provided a clearer understanding of consumer needs and shopping patterns. Armed with these insights, the manufacturer ensured products were categorized accurately, messaged thoughtfully, and placed where shoppers expected them to be, resulting in enhanced planograms that significantly boosted sales.

These deep insights into product benefits, claims, occasions, and categorization empower smarter, quicker decisions that were previously unattainable through traditional methods.

Automated Product Data Categorization

Besides providing a new depth of insights, Harmonya’s AI-driven solutions also eliminate the need for manual dataset alignment and attribution. These processes automate custom product categorization and ensure datasets are consistently updated with the latest schemas and taxonomies. Plus, as new products emerge, they are effortlessly integrated into existing frameworks.

In true partnership fashion, teams still have the flexibility to manage exceptions and make overrides, while machine learning models adapt and enhance output based on this feedback.

One way this is boosting performance of category managers is highlighted by the story of a global CPG company facing significant challenges with categorization complexity due to varying attribution schemas across diverse data sources.

By adopting an AI-driven product attribution solution, the company automated their custom attribution process and ensured consistent updates with their latest schemas. This approach resulted in highly accurate and consistent product taxonomies managed centrally, significantly reducing manual work and errors. As new products emerged, they were seamlessly integrated, ensuring clean attribution data.

This automation not only saved time but enhanced data reliability, enabling the company to make more informed strategic decisions. As a result, the company saw a marked improvement in data accuracy and operational efficiency, allowing them to capitalize on data-driven insights more effectively.

The Ideal Partnership

This collaborative partnership between people and AI puts category managers in the driver’s seat, freeing them to focus on big-picture strategy, tapping into their creativity and emotional intelligence in ways that AI can’t.

The ideal is a seamless partnership where AI and people work together hand in hand. By combining human ingenuity with AI’s ability to analyze vast datasets from diverse sources like syndicated retail data and consumer reviews, retailers are positioned to make smarter, more innovative decisions that drive success in the ever-evolving retail landscape.

Companies that embrace solutions that harmonize cutting-edge AI with human intelligence will be the true game-changers in this new era of data-driven retail strategy.