🏷️Merchandising 2.0: How AI Drives Personalised Product Recommendations

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🧐 FEATURED STORY

Imagine walking into a team store that knows your favourite player, jersey size, and what you bought last season. That’s not fantasy — it’s AI-driven merchandising.

In sports commerce, personalisation is becoming the new playing field. Rights holders are now blending fan data, AI models, and creative automation to recommend the right product to the right fan at the right time — turning engagement into direct revenue.

The next frontier of fan monetisation is personal relevance at scale.

🔑Why This Matters

Sports merch isn’t about shelves anymore — it’s about signals.
Fans scroll, click, and cheer differently, and AI can learn from each of those actions.

Here’s why it’s mission-critical now:

• Attention is scarce. Personalised recommendations cut through noise and increase conversion.

• Inventory pressure is real. Smart algorithms match long-tail SKUs to the right fan, reducing unsold stock.

• Commerce is fragmented. Fans shop across apps, web, and chat — AI connects the dots for a seamless experience.

💡 The takeaway: Personalisation isn’t just a marketing upgrade — it’s a business advantage.

🏆 How Rights Holders Win

• Centralise fan data - Combine ticketing, app, e-commerce, and social signals into one view.

• Deploy recommendation models - Personalise every digital surface from shop pages to emails and chatbots.

• Automate creative - Use generative AI to create hundreds of player-led, fan-specific variations of the same product ad.

• Test and measure - Track not just clicks, but conversion lift, AOV, and repeat purchase behaviour.

• Personalise in real-time - Use in-game moments to trigger product recommendations tied to highlights or player performance.

🌍 Who’s Doing It Already

Fanatics (March Madness 2025):
By integrating Google Cloud Vertex AI Search, Fanatics improved discoverability for thousands of March Madness SKUs in a short window, helping fans find relevant items during peak shopping moments. Better search + smarter personalisation = reduced friction and higher conversions.

Real Madrid (Adobe Experience Cloud):
Real Madrid unified ticketing, content, and e-commerce data to power one-to-one fan personalisation. With Adobe’s CDP and personalisation tools, the club now sends customised merch offers based on each fan’s behaviour and player affinity.

Mumbai Indians (GAN.ai Personalisation):
The IPL giant created personalised fan videos at scale, each one featuring fan names and favourite players. These personalised touchpoints doubled engagement rates and boosted merchandise clicks.

Rajasthan Royals (WhatsApp Commerce):
Using conversational AI via Gupshup, the Royals built a personalised WhatsApp shopping experience, turning chat threads into checkout flows.

📊 Real Impact: Case Studies

🏈 College Sports (USA)

Learfield (NCAA Partners):
Learfield’s integration of AI tools via Sidearm Sports and Nota enabled schools to personalise content and product recommendations for students, alumni, and donors, converting engagement into merchandise sales.

Fanatics College Stores:
AI-powered search and recommendation engines helped fans find team merch faster during March Madness and Bowl Season, leading to measurable conversion uplifts.

🏀 WNBA

WNBA x Second Spectrum (Genius Sports):
Optical tracking data now powers highlights personalisation and product recommendations linked to real-time player moments — connecting data to direct merch opportunities.

WNBA x Deloitte (App Personalisation):
Fans receive tailored content and merch recommendations in the WNBA app, increasing engagement and purchase intent for player and team gear.

WNBA x nVenue (Predictive Analytics):
By using AI-driven game insights, the league can surface contextual product suggestions (e.g., a player’s jersey after a highlight play).

⚽ NWSL (Women’s Soccer)

NWSL x BreakingT (Real-Time Merch):
AI-driven social listening identifies trending player moments, enabling BreakingT to drop fresh merch designs within hours of viral highlights — turning conversation into commerce.

NWSL x Greenfly (Player-Led Content):
Players share AI-tagged visuals that link directly to team store SKUs. Authentic player-led posts drive fan trust — and higher conversion.

NWSL x WSC Sports (AI Highlights):
Instant, personalised highlight clips are published to social channels, each linked to related merchandise for impulse-driven buying.

🇯🇵 Japanese Sports (J.League & Beyond)

J.League x WSC Sports:
AI-powered highlight personalisation delivers “in-app stories” tailored to each fan’s favourite team. These micro-moments now lead fans directly to related merch — player kits, collectibles, or limited drops.

J.League Clubs (Localised Personalisation):
Top clubs are using AI segmentation to tailor merch messaging by region — matching local culture and fan tastes.

Rakuten Monkeys (Japan/Taiwan Baseball):
Rakuten’s AI personalisation engine recommends products based on real-time fan data across its e-commerce ecosystem, lifting AOV and loyalty scores.

🛠️ AI Tools in Play

• Google Vertex AI Search for Commerce – powering Fanatics’ personalisation engine.

• Adobe Experience Cloud + Real-Time CDP – enabling 1:1 fan targeting for Real Madrid.

• GAN.ai – automating personalised video content for fans.

• Gupshup / WhatsApp Business API – driving conversational commerce for IPL teams.

• WSC Sports – creating AI-driven personalised highlights that double as merch triggers.

• Dynamic Yield / Bloomreach / Salesforce Interaction Studio – powering segmentation and recommendations for clubs worldwide.

🎯 Playbook: Steal These Moves

1️⃣ Build Unified Fan Profiles
→ Use CDPs (Adobe, Segment) to link ticketing, e-commerce, and social signals.
💡 Example: Real Madrid unified fan IDs to personalise offers by favourite player.

2️⃣ Use Search as Personalisation Gateway
→ Fanatics’ AI search model ranks products based on fan preferences, reducing friction.

3️⃣ Automate Player-led Creative
→ Mumbai Indians used GAN.ai to make 1000+ personalised fan videos in a single campaign.

4️⃣ Go Conversational
→ Rajasthan Royals’ WhatsApp commerce flow converts fans directly in chat — no website needed.

5️⃣ Launch Moment-Based Merch
→ NWSL x BreakingT’s rapid-production drops monetise viral match moments within hours.

🔮 Key Takeaways

AI personalisation is reshaping how fans buy and how rights holders sell.
The new rule of merch is simple: the closer the recommendation feels to the fan, the higher the conversion.

Start small — personalise one surface (search, email, or chat) — and scale once you see lift.
AI can’t replace passion, but it can make passion profitable.

📥 Call To Action

👉 Got a Merchandise 2.0 story? Share it with us.
👉 Want help to identify or activate Merchandise 2.0 around your club, league, or brand? Let’s chat.

📬 Want More?

Next week’s feature: How AI Fuels Fantasy Leagues, Second-Screen Experiences, and Watch Parties. Stay subscribed, stay ahead.

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