Transforming Retail Losses into Profits: A New Approach

Transforming Retail Losses into Profits: A New Approach

Retailers today face a challenging landscape marked by fluctuating interest rates, an unpredictable housing market, and persistent inflation. These external economic factors have significantly altered consumer spending habits, making profitability a top priority for retail CEOs.

To navigate these shifting dynamics, retail leaders must adopt strategies that convert losses into profits. One critical area of focus is transforming their businesses into more profitable omnichannel platforms. Despite the growth of ecommerce, retail profitability has been on a decline. According to Deloitte, the median EBITDA for publicly traded retailers dropped from 9.8% in 2012 to 6.7% in 2019, with a modest rebound to 8.6% in 2022 during the pandemic. This decline continued even as ecommerce evolved into a mobile-first business.

Ironically, ecommerce might be contributing to the profitability problem. While brick-and-mortar stores still account for 80% of global sales, many retail CEOs are heavily investing in enhancing online shopping experiences. In 2023, 49% of retail executives planned to increase ecommerce investment while reducing in-store spending. The costs associated with ecommerce – including technology, app development, and fast, free shipping and returns – can be overwhelming and may exacerbate profitability challenges.

A more insidious issue lies in decision-making processes. Surprisingly, many top retailers still rely on gut instinct for key buying decisions and use outdated data, risking excessive or inadequate inventory. This reactive approach can lead to a retail death spiral. The solution? Smart merchandise and assortment decisions driven by customer insights and aimed at profitability.

Putting the Customer at the Center

One effective strategy for enhancing profitability is using predictive analytics for decision-making. Historical and present sales data alone are insufficient. The voice of the customer – data directly from shoppers – is crucial for accurate forecasting and buying decisions. With the rise of AI-powered platforms, combining predictive analytics with customer input can optimize merchandise assortments.

Customer-Informed Product Development

Involving customers at the ideation stage of product design can reduce the risk of creating items that don’t resonate with the market. Staying updated on shifts in consumer behavior and purchasing drivers is essential. Testing fabrics, materials, colors, and technology based on customer feedback leads to better sourcing and price optimization from the start. Collecting actionable data from target consumers about their needs and trends allows retailers to design products that align with future market demands.

Manufacturing Desirable Products

Testing early digital versions of products with customers before manufacturing can maximize profits and eliminate costly in-store testing. Placing the customer at the center of product development aligns retailers with consumer sentiments and needs, reducing the risk of producing too much of the wrong product or too little of the right one. This customer-centric approach boosts profitability, minimizes waste, and supports sustainability efforts. With the right software and predictive tools, designers can make better decisions about new items and attributes across multiple regions, countries, and target personas.

Creating and Optimizing Winning Assortments

Instead of relying on secondary trend information or internal opinions, retailers should ask shoppers directly about potential new products. Testing assortments before financial commitment can significantly improve decision-making around which items to keep, expand, or drop. Listening to customers can guide buyers and merchants in building more successful assortments, optimizing inventory, sales, full-price sell-through, and gross margin ROI.

Testing assortments with targeted customers allows merchants to optimize future inventories with data showing which items shoppers prefer and might buy in multiples. These insights enable retailers and brands to eliminate underperformers before they reach the floor, leading to a more demand-aligned allocation of buying budgets.

By placing the customer at the center of decision-making and leveraging predictive analytics, retailers can transform losses into profits and thrive in a competitive market.

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