AI trend detection reads social media, influencer content, and weather to predict what sells where
They'd just written off $8M in dead inventory — hoodies that didn't sell in SoCal stores but would have sold out in PNW. Meanwhile, their bestselling collab dropped and sold out in 3 hours, leaving $2M in unmet demand. Their VP of Merchandising said: 'We're either drowning in product or starving for it. There's no middle ground.'
This Costa Mesa-based action sports brand operated 120 retail locations plus DTC e-commerce. Trend cycles in streetwear/action sports are brutally fast — what's hot on TikTok today is dead in 6 weeks. Traditional demand planning with 9-month lead times meant buyers were essentially guessing what would sell next spring based on last spring's data.
We built a demand sensing platform that combines social media trend analysis (TikTok, Instagram, Reddit), influencer content monitoring, regional weather forecasts, and real-time POS data. The system identifies emerging trends 4-6 weeks before they peak and recommends inventory allocation by location cluster. Our overnight team monitors Asian social media trends (which often lead US trends by 2-3 weeks) and updates forecasts daily.
The AI spotted a color trend on Xiaohongshu three weeks before it hit TikTok in the US. We shifted our spring allocation and had the right product in the right stores before our competitors even placed their orders.— VP of Merchandising
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