Retail theft has been a major problem, particularly since the pandemic, costing retailers $112.1 billion in 2022. A number of retail giants have announced they're closing stores across major cities due to theft and organized retail crime. But recent analysis shows that theft is only one of many factors behind these shutdowns. The combination of inflation, rising costs, and retailers’ inability to accurately forecast demand and manage inventory will also take a significant toll on revenue this year.
No matter the source of lost revenue, retailers can find new ways to recover a significant portion of their revenue. Modern tools like artificial intelligence assistants can diagnose retailers’ performance drivers to identify new revenue opportunities that were impossible to uncover before. Let’s take a look at some specific ways AI can help retailers improve their bottom line.
Enhance the Product Portfolio
While SKU rationalization is a critical component of retail to understand what products to keep and which to get rid of, it’s often a challenge to obtain a real-time picture of product performance. Retailers still struggle to manage their excess inventories this year after overstocking merchandise in 2022. In a survey conducted earlier this year, only a third of supply chain executives said they believed their warehouse inventories would go back to normal before the end of 2023. And the retail shutdowns indicate the problem is likely ongoing.
The process of analyzing product performance has been no easy feat for retailers. It’s often prone to bias and quite time-consuming for all stakeholders involved. Analysts spend considerable time cleaning and merging data sources before they manually conduct tests on their data, while executives wait days or weeks for an answer. By the time the executive gets their answer, the data is stale and obsolete. As a result, retailers don't have an accurate picture of which products they need more of and which they should stop ordering.
However, AI assistants can automate the time-consuming tasks of collecting, integrating and analyzing data by using generative AI and machine learning. This tool gives retail executives an interactive and conversational way to access and understand their data, essentially serving as their own personal data analyst. Users can ask specific questions about sales trends, consumer spending patterns, and more, and receive immediate responses in plain English. By identifying and cutting underperforming products, retailers can focus their investments on the products that will win them more money over time.
Forecast Consumer Demands Ahead of Seasons
In addition to maintaining the right inventory, retailers must be able to plan stock levels and pricing strategically, especially around different seasons. Retailers have a small window of opportunity to sell products during each season. Let’s take the holiday season, for example. Strategic planning begins months in advance, and during the thick of the season, teams are scrambling every day to adjust plans, move inventory, fulfill orders, and adapt to unforeseen challenges.
An AI-powered assistant can provide nuanced, data-driven responses to sudden performance shifts. Whether it's a sudden spike in product demand or an unanticipated drop in promo effectiveness, AI not only helps pinpoint the cause but can also suggest counteractive measures. This rapid, informed decision making becomes the key to navigating and excelling in the holiday frenzy. The ability to be agile, proactive and instantly responsive is critical to maximizing holiday sales performance.
For example, let’s say a retailer’s data science team was looking for ways to maximize sales of products during a perishable event like Thanksgiving. An AI analyst could provide the team with pricing recommendations for each product, ranked by revenue impact. It could also advise on moving surplus inventory from one store to another to optimize sell-through. These recommendations considered all relevant factors, including account type, competitor products, sales activity, and more. Generative AI can serve as a force multiplier, giving pioneering retailers the competitive edge they need to succeed.
Overcoming the Retail Crisis
While some factors impacting revenue like retail theft can’t always be prevented, modern technologies can help retailers make a profit in other areas to combat these losses. Optimizing their product portfolios and forecasting consumer demands are only two of many benefits AI assistants can provide. By leveraging AI-powered tools, retailers can rebound from revenue losses and thrive in the coming year.
Pete Reilly is the COO at AnswerRocket, a platform that integrates generative AI technology throughout the data analysis process.