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The Common Pricing Mistakes That Could Send Your Margins Spiraling

Due to fashion retail’s overly promotional environment in recent years, consumers have become accustomed to looking for a deal. But now that retailers are attempting to retrain shoppers to buy at full price, artificial intelligence and analytics can help make over consumer behavior through a personalized, targeted approach.

Consumers today are armed with more information than ever before. Whether shopping in a store or remotely via e-commerce, they are able to quickly benchmark prices for the same product or product types across competitors. This transparency has made pricing more competitive in driving both foot traffic to stores and sales, and it has also made the process of deciding costs more complex. Pricing used to be determined by small teams using gut decision-making and institutional knowledge, but retailers now have more customer data and technology at their disposal, turning discounting into more of a science.

Pricing doesn’t exist in a vacuum. Even though retailers do not need to win a race to be the cheapest among their competitors, they need to pay attention to how their pricing compares to what others charge. Artificial intelligence can help retailers find and keep track of their competitive set through image searches for similar products.

Another consideration when offering promotions is how one markdown can either cannibalize or provide a halo effect to another. For instance, discounting one pair of jeans might hinder sales of another, or it could create opportunities for retailers to upsell consumers on related items.

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When it comes to promotions, not all products are created equal. Factors such as brand image, scarcity, quality and more can make some garments or accessories sell at full-price, while others lacking these attributes might require more of an incentive to drive a purchase. Because fashion is highly seasonal, weather can also have a huge impact on when and how garments are marked down. A warm winter could mean that heavy coats need to be discounted earlier in the season to clear out inventory before it is too late, for example.

However, the biggest indicator of whether a markdown is needed is demand. “One of the most important things is to make sure you start marking down while there’s still demand,” said Jeff Smith, founder and executive vice president of corporate strategy and development at Revionics, a firm that offers SaaS-based pricing, promotion and markdown solutions. “The retailers too often wait too long before starting the markdowns, and the demand has gone away. So it doesn’t really matter how much they mark it down. The demand has gone away, people aren’t going to buy it.”

One of the key challenges for fashion retailers is the cyclical nature of their product offerings. Amit Rohatgi, vice president product consulting at analytics solutions company Manthan, noted that while past transactional data is available, SKUs and styles are typically revolving, making the performance of the current season’s designs more of a guessing game. He explained that even though items might be new, data and analytics can be used to extrapolate attributes that match earlier styles to give a better understanding of how an item is likely to perform.

While products require a differentiated approach, consumers are also varied.

For instance, some have the affluence or desire to buy at full price, whereas others are constantly looking for more of a bargain. Rather than using a blanket approach towards promotions, experts suggest a more tailored and individualized strategy to encourage sales with better margins.

“It’s not just about having general pricing activity, but about communicating directly to your customer,” said Hélder Gomes, international managing director at Itim, which is focused on improving financial and operational performance. This could mean looking at past transactional data or demographic or economic indicators of an ability or willingness to spend.

“If you do a mass discounting, you essentially end up changing behaviors of consumers who are not even discount sensitive,” Rohatgi said. “I think we need to go back and basically segment our consumers well to understand what their needs are.”

Retailers are looking to move away from heavy markdowns to preserve their brand image or margins, requiring more creative approaches for dealing with supply that exceeds demand. Today’s technology allows retailers to use artificial intelligence to rebalance merchandise, sending products from stores that have too much inventory to locations where there is still demand. This helps to delay markdowns by weeks and sell more of the goods at full price while also giving consumers access to merchandise that was previously out of stock or unavailable in their area.

Smith noted that a retailer’s pricing does not have to be the same across channels or store locations, since the demand and consumer drivers may be different. For instance, consumers may pay more for the benefit of being able to walk out immediately with an item from a brick-and-mortar store. Analytics can also be used to take characteristics of a particular geographic area and create groups of stores with customer bases that have similar price sensitivity and then pricing accordingly.

Targeting to the individual also means serving up promotions when she has a propensity to actually buy. While promotions may still be a necessity to help retailers woo some consumers, one of the first steps in reducing promotions is having a regular price that consumers deem fair.

Retailers also need to crunch the data on what impact past promotions have actually had on business so they can act on it in the future. “There’s been a lot of effort put into the supply side of retail, and cutting costs out of the supply chain and getting that to run most efficiently, but there hasn’t been work until recently on the demand side and on the pricing and really understanding that and putting a lot of effort on that side,” Smith said.