AI is often touted as the ultimate solution for improving product discovery, personalization, and conversion rates. While AI has the potential to be transformative, it’s not a magic fix. Instead, businesses must carefully evaluate how AI is implemented to ensure it aligns with their brand strategy and objectives.

When considering an AI-powered product discovery solution, three critical factors should be prioritized: control, transparency, and openness.

1. Control: Direct vs Be Controlled by AI

Many AI solutions operate as a “black box,” meaning they process data and generate recommendations without allowing businesses to influence how these decisions are made. While AI can effectively analyze user behavior and suggest relevant products, it doesn’t inherently understand brand guidelines or industry-specific nuances.

Take the luxury retail industry, for example. A customer browsing for Chanel and Dior products may trigger AI to recommend them alongside each other. However, luxury retailers understand that these brands should not be positioned adjacent to one another due to strategic and branding reasons. Without proper controls, AI could make recommendations that contradict business objectives.

Therefore, any AI-based product discovery tool should allow businesses to set rules and parameters that ensure recommendations align with their brand identity and merchandising strategy.

2. Transparency: Understanding the “Why” Behind AI Decisions

For businesses new to AI-driven e-commerce solutions, one of the biggest challenges is understanding why AI makes certain recommendations. Many platforms fail to provide visibility into their processes, leaving retailers uncertain about how AI is influencing their product discovery.

To address this, Fredhopper has developed a Chrome plugin that allows users to see where AI is being leveraged, which models are being used, what rules are applied, and why specific recommendations are made. This kind of transparency builds trust and confidence, helping businesses optimize AI-driven recommendations over time.

When selecting an AI vendor, look for solutions that offer this level of insight and control over AI processes. Transparency ensures that businesses can make data-driven decisions while maintaining confidence in the technology they’re using.

3. Openness: Avoid Being Locked Into a Single AI Model

The AI landscape is rapidly expanding and evolving at lightning pace. Yet, many vendors promote their AI as the ultimate solution, restricting businesses to a closed ecosystem of proprietary models. This limits flexibility and prevents retailers from exploring better-performing models.

At Fredhopper, we recognize that different use cases require different AI models. That’s why we emphasize an open ecosystem where businesses can integrate their own algorithms, blend them with third-party solutions, or compare multiple models to find the best fit. The ability to test, optimize, and adapt AI models is crucial for staying ahead in e-commerce.

Key Takeaways

When evaluating AI-powered product discovery solutions, remember these three guiding principles:

Control: Maintain oversight and apply guidelines over how AI interprets data and makes recommendations.

Transparency: Ensure you have visibility and insights to understand and optimise AI-driven decisions.

Openness: Avoid being confined to a single AI model. Stay flexible and adaptable to be able to embrace the rapid pace of new models and ability to test, blend, and optimise to find the right balance for your given use case.

AI is a powerful tool, but its effectiveness depends on how well businesses manage, and optimize it for their unique needs. By prioritizing control, transparency, and openness, retailers can harness AI’s full potential while ensuring it aligns with their strategic goals and brand story.

Learn more about how Fredhopper is leading the way in AI-driven product discovery by clicking here .