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AI-powered returns management for fashion retailers | White paper

November 21, 2024 — By Wendy Mackenzie

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AI-powered returns management for fashion retailers | White paper

The world of supply chain is as exciting and dynamic as it is unpredictable. And in the world of retail, the glamorous fashion industry occupies a special place as it sets trends and follows socio-economic patterns more closely than most other verticals. Seasonal changes, celebrity preferences, expression of social and political opinions and several other factors play an important role in determining the trajectory of this industry. According to McKinsey & Company, “While luxury has led in value creation in recent years, the McKinsey Global Fashion Index forecasts that [...] it is nonluxury that will drive the entirety of the increase in economic profit for the first time since 2010 (excluding the COVID-19 pandemic).”

Amidst all these challenges, managing inventory returns plays a pivotal role in overall inventory management. With shoppers treating their homes as dressing rooms and ordering multiple sizes and styles to try on at their convenience, return rates are soaring—costing retailers billions each year. Traditional returns processes are no longer adequate to handle the volume and complexity of modern shopping behaviors.

What causes returns?

Fashion retail customers return products due to several reasons besides just dynamic trend changes. Below are some common reasons:

  • Defective or damaged goods: Defective products or damaged goods can initiate returns.
  • Online shopping: Seamless return policies, easy payment methods and options have made returning goods much more manageable.
  • Bracketing: This involves buying the same item in multiple sizes and colors and returning those that are not needed.
  • Wardrobing: Customers buy clothes just to appear on social media, or photographs for a for special occasion and then return them to the retailer.
  • Delivery discrepancies: Late deliveries and delivery of wrong inventory lead to returns.
  • Free returns: Several companies offer a free returns option, resulting in greater returns.

How can AI-driven solutions help fashion retailers with returns management?

Retail returns can affect operational and financial costs, as well as the environment, negatively due to increased wastage and overconsumption. Adopting AI-powered inventory management processes allow fashion retailers to transform how they manage returns starting with pre-purchase value as well. Here are a few examples of AI use cases in retail.

  • Virtual try-on: Online tools can give personal recommendations and create virtual try-on tools to help customers see how they will look in a particular gear. Personalized recommendations can analyze customer data like purchase history, demographics, and browsing behavior to recommend products for them. AI-powered virtual try-on tools allow customers to see how clothes will look on them, helping them make more informed decisions, reducing size-related returns, and giving the retailer a competitive advantage.
  • Improved product information: Customer opinions and feedback are analyzed and compared to returns data, and product information and images can be improved.
  • Streamlining the returns process: AI can automatically approve or deny returns by pre-defining rules and regulations. For example, to mitigate returns by wardrobing, the retailer can state that goods without product tags and price stickers cannot be returned. This can streamline and speed up the returns process.
  • Intelligent routing: AI can analyze the most speedy and thrifty route in real time for process returns. This is an indication of a sustainable returns management process.
  • Inventory planning: AI can predict likely-to-be-returned items. Once identified, this leads to better inventory planning, reducing storage and wastage.
  • Restocking and processing: Stocking, refurbishing or disposing of items can lead to an effective returns management process using AI-powered insights.
  • Dynamic pricing: Accurate pricing is crucial for the success of a retail business. AI can adjust the price of the product based on market demand and product condition. Thus, the maximum value can be recovered even from returned items.

These gold medal-winning strategies lead to reduced return rates, cost savings and increased efficiency and sustainability for the retail industry. AI is transforming how retailers manage returns, offering a win-win solution for both businesses and customers. As AI technology continues to evolve, we can expect even more innovative and effective solutions in the future, resulting in a healthier bottom line for the struggling fashion industry.

Stay up-to-date with the latest trends by adopting AI-driven solutions for your fashion retail business by connecting with an invent.ai retail expert.