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AI Recommendation & Product Positioning

Transform product discovery into a data-driven, personalized experience that aligns customer intent with real-time recommendations to increase conversion, basket size, and loyalty

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Generic merchandising and static product positioning fail to meet evolving customer expectations, limiting retailers’ ability to deliver relevant experiences, reduce decision friction, and maximize commercial performance across channels

WHY THIS “AI RECOMMENDATION & PRODUCT POSITIONING” CHALLENGE?

From static merchandising to real-time, intent-driven product discovery

Traditional approaches rely on intuition and fixed rules, limiting the ability to adapt product visibility, pricing, and recommendations dynamically to customer behavior and context

Key benefits

Turning customer intent into measurable commercial outcomes

Personalization, precision, and scalable growth

Higher conversion through relevant recommendations

Align product exposure with real-time customer preferences, reducing friction and increasing purchase likelihood at each interaction

Increased basket size through intelligent cross-sell and upsell

Identify complementary and higher-value products dynamically, driving higher average order value without relying on discounting

Stronger engagement through personalized journeys

Deliver contextual, intuitive experiences that increase interaction time, repeat visits, and long-term customer loyalty

Improved decision-making through reliable data foundations

Strengthen data quality and governance to enable consistent, explainable, and actionable AI-driven insights

How NTT DATA helps

01

Designing advanced recommendation models

Develop algorithms that improve product discovery and increase cross-sell effectiveness

02

Enabling merchandising analytics and insights

Provide visibility into product performance, positioning, and customer behavior

03

Implementing real-time personalization capabilities

Adapt recommendations dynamically based on behavior, context, and availability

04

Optimizing performance through continuous monitoring

Track impact on conversion, engagement, and revenue to refine models

05

Strengthening data governance and quality frameworks

Ensure reliable inputs for accurate, scalable AI outputs

Proven impact

Aligning customer intent with product visibility to drive higher conversion, basket value, and engagement at scale

Results that matter

Measurable impact on conversion, revenue, and customer loyalty:

+5–15% increase in conversion rate

More relevant product exposure reduces friction and accelerates purchase decisions

+10–25% uplift in average order value

Context-aware cross-sell and upsell strategies expand basket size

+15–30% improvement in retention and engagement

Personalized experiences increase repeat visits and customer lifetime value

Stronger consistency in commercial decision-making

Data-driven insights improve confidence and reduce reliance on intuition

Increase conversion and basket value with AI-driven product recommendations

Deliver personalized, high-impact retail experiences

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