The global health & wellness market is expected to be USD 8.946 trillion by the end of 2030 and the global beauty and personal care market is projected to generate a revenue of USD 734.78 billion by 2028.
As the industry continues to gain momentum, criticalities follow suit – seasonality, higher inventory investments driven by intense competition and rapid new product launches, e-commerce, slow-moving products, prescription and substitution drugs, and the high share of promotions make it hard for retailers to contain costs, optimize inventory, and stay profitable while decoding customer demand. Here’s how automation can help!
01 Reduced Inventory Costs
More than 50% of consumers use multiple brands for products like hair, skincare, and fragrance, making accurate demand forecasting difficult.
The health, beauty, and wellness segment has high-bulk, high-value product categories, which means the inventory costs are significantly higher. Microtrends and sudden demand shifts can cause high obsolescence and leave retailers with overstocked shelves.
AI/ML-driven intelligent replenishment solutions can optimize inventory across the supply chain and can adapt to these fluctuations by continuously analyzing real-time data and demand patterns at an ultra-granular level, such as channel, store, category, SKU, and more.
The health, beauty, and wellness segment has a highly competitive environment where trends can shift rapidly, and unpredictable factors like social media influence can render an entire category obsolete.
ML-driven replenishment solutions come with adaptive self-learning models that optimize replenishment plans by modeling variations in key supply-side metrics, such as lead times, fill rates, safety stock, pending orders, and more.
02 Adaptive Replenishment
This volatility makes inventory planning particularly challenging, taking down accuracy rates to anywhere between 30% and 50%.
03 Managing Seasonality
A whopping 80% of German consumers feel the skincare needs change with the seasons, while 48% of Chinese women use different facial skincare brands throughout the year.
AI/ML-driven inventory planning incorporates historical sales data, upcoming trends, available stock, lead times, fill rates, and highly granular sales influencers for specific stores, channels, locations, categories, and more, to manage seasonal and hyperlocal variations in demand.
Smart forecasting and inventory replenishment solutions take
promotional data as input during demand planning to identify, predict, and manage the promotional shifts and lifts in demand across SKUs, categories, channels, etc., to increase profitability.
04 Chaos-Free Promotions
A staggering 96% of commercial directors find running consistently well-performing promotions challenging.
05 New Product Introductions
Nearly 50% of US beauty shoppers buy new products based on online feedback from others but poor inventory management can lead to a 25% loss in potential sales due to oos.
Instead of relying on guesswork, retail automation solutions leverage attribute-based and hierarchical forecasting to analyze similar product attributes and higher-level category trends, ensuring better stock availability, quick adjustments to demand shifts, and precise anticipation of customer needs at the hyperlocal level.