Revolutionizing Category Management: The AI Impact

Category management has long been the unsung hero behind retail shelves, deciding what products make it to consumers, their pricing, and the quantities available. However, this crucial aspect of retail has been hampered by outdated planning cycles, fragmented data, and manual processes that struggle to keep pace with the dynamic shopping environment.

While the challenges in category management seem straightforward to resolve, the reality has been far from simple. Lingering sales cycles, complex technology integrations, and the daunting task of training already-burdened teams have stifled meaningful progress, relegating improvements to the ‘someday, maybe’ category.

Can AI Change the Game?

With the advent of advanced AI technologies that provide faster and more user-friendly solutions, many wonder if the time for transformation has finally arrived. The short answer is: potentially, but it hinges on aligning suitable use cases with the right human resources and established habits that, according to a BCG retailer survey, drive 70% of AI’s value.

The Role of AI in Category Management

AI thrives in environments with clear rules, clean data, and well-defined success criteria. This is why category management, with its emphasis on spreadsheets and planograms, is gradually shifting out of stagnation.

The Shelf: Assortment, Merchandising, and Execution

• Localized assortment optimization: AI aids merchants in determining which products to stock and their respective mixes by analyzing demand signals, margin data, and shopper preferences.
  • Impact Analytics raised $40 million in 2024 to assist consumer packaged goods (CPGs) in analyzing shopping behavior to recommend product mixes and pricing tailored to specific retail accounts.
  • Aravita, a Brazilian startup funded by Qualcomm Ventures, utilizes data on weather, demand trends, and inventory to optimize order amounts for perishable goods.
• Digital visual merchandising and store execution:
  • Flagship secured $5.5 million in 2024, creating digital twins of retail environments through computer vision technology. This allows teams to experiment with layouts and product placements to enhance sales effectiveness before implementing physical changes.
  • Retailers like Lowe’s are leveraging AI and digital twins to test store layouts, adjust product placements based on seasonal or weather changes, and quickly adapt to emerging retail trends.

The Signal: Forecasting, Trends, and Pricing

• Forecasting that sees what’s coming: AI enables retailers to use real-time data signals to prevent empty shelves and to anticipate demand shifts before they become evident in traditional market research.
  • Black Swan Data, now part of Mintel, is transforming how brands perceive rising trends by utilizing AI to analyze online conversations and consumer behaviors to predict future product demands.
• Smarter pricing and promotion planning: AI analyzes historical sales data and pricing elasticity to suggest optimal times for price changes or promotions to encourage consumer purchases.

The Shopper: Personalization and Relevance

• AI that understands the shopper:
  • Constructor, which raised an additional $25 million in 2023, uses clickstream-based AI to personalize product discovery and search in real time. Their partnership with Target Australia led to a 9% increase in search revenue and a staggering 93% reduction in bounce rates.

Why the Slow Adoption of AI?

Despite the promising advancements in AI, adoption remains sluggish. Key factors shaping this hesitance include data readiness, human resources, and operational processes, which are often the real hurdles for many teams.

A 2025 BCG survey revealed startling insights:

• 1 in 3 data points used by merchants was incorrect.
• Approximately 40% of available technology is not utilized.
• Half of the merchants lacked training on analytical tools.

The main challenges stem from organizational resistance, outdated systems, and time constraints, indicating that technology alone won’t suffice. AI solutions must integrate seamlessly into existing workflows while fostering necessary behavioral changes to ensure lasting impact.

Continuing the Conversation

Join industry leaders from BCG, Deloitte, Daisy Intelligence, and AgFunder portfolio company Lumi AI on July 30 for a live discussion on how AI is shaping category management and merchandising, along with insights on moving from pilot programs to practical application.

Webinar: AI Data-Driven Category Management
July 30 | 12pm ET | Online
Find out more and register here