Inventory backlog is a nightmare for online retailers. This scenario creates waste of both profits and products, forcing retailers to add discounts. In fact, the retail industry tosses over $163 billion in inventory every year because of poor inventory management.
The clearance section, or the last-ditch effort to sell these products, isn't all that great for shoppers either. Despite the low prices, the items on clearance are often the less desirable styles and sizes, leading shoppers to scroll through the sales yet leave with an empty cart.
That's why retailers need to invest in artificial intelligence to reduce the size of the clearance section. Retailers can achieve this by incorporating AI into every step of the product lifecycle, from product discovery to checkout.
Aiding product discovery
The way consumers search for their next purchase is changing before our eyes. Research firm PwC found 71% of consumers prefer using voice search instead of typing their query, and an industry news site reported 43% of shoppers start their product discovery process on social media. As these channels evolve, the language used to search for products will change, revealing a more relaxed tone that mirrors the voice of the consumer.
Imagine that a popular concert tour like Taylor Swift's Eras Tour or Beyonce's Renaissance Tour is sweeping the country. In these scenarios, attendees may look for fashion items that fit the essence of the artist's show, like sparkly jumpsuits or cowboy boots. To find the sparkly jumpsuit, for example, they might search "sparkle," when they're really looking for rhinestones or a textile with a glittery finish. If a retailer has these additional keywords embedded in their product copy, they will help more shoppers find what they are seeking in less time.
Regardless of which style is "in" or which trend is fostering a boom in online searches, retailers must take the voice and the preferences of the consumer into consideration when developing website content.
With artificial intelligence and generative AI, retailers can evaluate the search terms shoppers are using and automatically incorporate those phrases into product attributes and product descriptions, improving SEO. In addition to keyword research, generative AI tools can also manage meta-tag optimization and back link analysis. This automation increases efficiency and frees up marketing teams to spend more time on other aspects of the customer experience.
These AI-driven initiatives will improve SEO and product discovery, driving higher average units per sale and reducing unnecessary markdowns of the items shoppers didn't find in their search.
Guiding informed decisions
Once a shopper finds a product that intrigues them it's up to the product attributes, descriptions, and reviews to showcase why the product is desirable. Whether it's details about the product's size, color, or quality, accurate and complete product attributes help a shopper determine if the item will fit their needs. With generative AI, retailers can automatically complete missing product attributes and values and correct inaccuracies.
One way AI can improve product attributes and descriptions is by monitoring customer reviews. For instance, if eight shoppers have recently said the retailer's products labeled "red" look more like "maroon," the AI tool can notice this pattern and recommend the retailer adjust the product description.
This small adjustment can make a big difference. For example, if a shopper is looking for a red shirt to match their favorite red shoes, they'll rely on the product attribute to determine if the items will match. Their satisfaction will be based on the reliability of the color description, and without AI, the retailer might not have seen the feedback in the customer reviews in time.
Similarly, if shoppers are reporting that a product's material feels soft or the size runs large, AI can help retailers react and incorporate this messaging into the product decision so shoppers can feel confident in their purchases.
As a result of this AI-driven initiative, customers will thoroughly understand the products in their cart before they buy them, leading to more customer satisfaction, more repeat purchases, fewer returns, and ultimately a smaller clearance section.
Setting effective prices
Another critical component in the process of reducing the clearance section is pricing. Setting the right price is a complicated balance that considers competition, business strategies, elasticity, and cannibalization across brands. Fortunately, retailers can use AI to set the optimized price the first time, reduce discounts, and keep the clearance section to a minimum.
AI can automatically forecast upcoming changes in supply and demand and recommend optimal price points that drive greater margins and reduce unnecessary markdowns. The technology can also suggest key adjustments like relocating inventory to stores where the stock is selling through more quickly or offering a buy-one-get-one promotion to increase units sold without decreasing margins too drastically.
This proactive, AI-driven approach to price management quickly accounts for market factors and shopper trends, protecting price perception and fostering stronger margins without relying on a clearance section.
Using AI to reduce the clearance section
In an ideal world, retailers would never need a clearance section. They'd be able to sell through their inventory at full price. With AI, this goal is more achievable than ever because retailers can improve SEO and generate better, more accurate product descriptions in the voice of the consumer. AI also empowers retailers to set optimal prices by consistently reviewing customer feedback, market trends, competitor offerings, and more.
By taking these key purchasing factors to the next level with AI, retailers can sell through their inventory more effectively without price cuts while simultaneously increasing customer lifetime value. It's a win-win situation for retailers and their customers.