JD Sports enters its next growth phase with an AI-ready strategy after clicks jump 747%

From a single store in the North West of England in 1981 to 4,850 locations across 49 countries today, JD Sports has become a global sports fashion leader. Heading into the 2025 holiday shopping season, the brand focused on future‑proofing its approach to meet peak retail demand and modern, AI‑influenced consumer journeys.

The team recognized that search is evolving beyond keyword targeting to include AI-driven discovery and conversational experiences. Anticipating that more shoppers would rely on AI-powered search, JD Sports wanted to ensure its holiday campaigns were ready for this newer way of finding products. To support this shift, JD Sports partnered with Microsoft Advertising to restructure their campaigns to succeed in this more dynamic, AI-led search environment.

As search evolves from simple question-and-answer journeys to more conversational, nuanced queries, JD Sports recognized the need to move beyond static keyword lists. To keep pace, the team worked with Microsoft Advertising to redesign how its products were grouped and strengthen the data flowing into the platform.

This included a full account restructure that simplified legacy structures and created a stronger foundation of data and signals about sales priorities and customer behavior during peak season for AI tools to perform effectively. JD Sports also leaned into automation, using broad match and Performance Max (PMax) to dynamically respond to user intent and match ads to the right queries in real time. The restructure allowed the team to strengthen their data quality and expand AI automation for their workflows, positioning JD Sports as an early leader in AI-first redesign

Here’s how they used PMax, broad match, and automated bidding to meet audience needs in real time...

• PMax to capture cross-channel demand: The team ran goal-based PMax campaigns that served ads across Search and Shopping placements. The system prioritized placements based on conversion potential rather than fixed channel splits.
• Broad match to expand relevant queries: Ads appeared for closely related searches without requiring exact keyword matches. A query like “lightweight running shoes for winter” could trigger JD Sports ads even if that phrase wasn’t manually added, expanding visibility during high-demand periods.
• Automated bidding to react in real time: Bids adjusted dynamically based on signals such as device, location, and probability of conversion. As promotional traffic fluctuated, the system adapted instantly.

By aligning structure, signals, and bidding with how AI-powered search evaluates queries, JD Sports paved the way for record growth.

During peak season, clicks surged by 747% and the brand core conversion rate grew by 99%. Top impression share also rose by 85%, strengthening the brand’s visibility in high-intent searches while competition was at its highest.

Simplifying account structure was critical for AI to perform at scale, ensuring the system could access richer, more complete signals across the full customer journey. JD Sports consolidated its top and mid-funnel account structures, recognizing that in AI-driven, conversational environments, the path to purchase is much shorter with multiple stages of the funnel often occurring in a single interaction.

By bringing Search, Shopping, and PMax together, the team strengthened conversion signals and gave automation a more complete view of user intent. This allowed broad match and PMax to dynamically generate and serve the most relevant ads at the right moment, without the need for manual buildouts across individual placements.

Automated bidding was the final puzzle piece, using the rich intent and behavioral signals seen in chat-based environments to adjust bids in real-time.