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Justin MacFarlane
Partner & Managing Director
New York
Beyond the Hype: Realizing AI's potential in retail
How do you drive tangible business results through AI? We’ve partnered with top global retailers to answer this question, resulting in transformative solutions that maximize impact through targeted AI investments.
In this series we explore how innovative AI solutions are transforming the retail industry, driving smarter decision-making and stronger financial performance. Each article breaks down examples of our practical, real-world applications of AI—from forecasting and pricing to inventory optimization and customer strategy— showcasing how retailers can use the AlixPartners AI Profit Engine to unlock growth, improve margins, and stay ahead in an increasingly competitive market. In this first article, we focus on forecasting.
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Top-down strategic planning and forecasting methods no longer suffice. These outdated approaches rely on static assumptions and broad financial targets, often failing to capture key growth drivers, such as customer trends, pricing dynamics, competitive shifts, and macroeconomic factors. As a result, many retailers struggle to align financial planning with real-world market conditions, leading to missed opportunities, costly inefficiencies, and underachieving financial targets.
Traditional forecasting limits business potential
Traditional top-down forecasting and planning can impede a retailer’s success. These forecasts typically oversimplify factors that influence business performance by omitting key levers such as regional performance, customer retention, and competitive dynamics. They are difficult to adapt, requiring frustrating iterations that burden financial teams and delay decisions.
Top-down forecasting is often used alongside siloed bottom-up forecasting, where merchandising, marketing, and retail teams independently create plans and assumptions for the upcoming year. These forecasts are usually combined at the end of the process but often fail to align, resulting in inconsistent and flawed outcomes. Most importantly, these forecasts do not predict the two most crucial factors in a retailer’s success: the number of customers and how much they will spend. The result is a disconnected forecast that, at best, does not align with operational realities and, at worst, sets an unrealistic and unachievable financial plan that results in lost customers, falling revenue, and missed investor targets.
Enhance forecast accuracy with an AI-powered predictive customer forecast
AI-driven predictive customer forecasting has the power to give retailers a strategic edge by providing future visibility into the number of customers and customer spend using a sizable amount of historical company and non-company data and AI and analytics capabilities. The resulting model takes traditional forecasting data points and expands them to include factors such as pricing strategies, marketing investments, inventory availability, competitive pricing, macroeconomic conditions, and more, enabling retailers to predict future customer counts, spend and, ultimately, revenue.
Real-time scenario planning: The game-changer
AI-driven customer forecasting is truly transformative because it enables real-time scenario planning. Unlike traditional forecasts that are static, cannot account for changing market conditions, and require tedious, frustrating cycles with finance teams to update, an AI-driven model continuously analyzes new data to reflect the current market realities. Retailers can simulate different scenarios—adjusting prices, reallocating marketing spend, or increasing inventory—to immediately see how these changes interact with one another and impact customer counts, spend, and financial outcomes.
With AI-driven customer forecasts, retailers improve the quality and speed of their decision-making while alleviating pressure on finance teams.
Case study: A wholesale/retailer’s AI-driven forecast transformation A multi-billion-dollar apparel, omnichannel wholesale/retailer was facing sales pressure, shrinking EBITDA margins, and difficulties accurately forecasting business performance. Their challenges included marketing performance, low productivity due to revenue churn, and pricing challenges due to inflation and promotional planning. Most critically, the company struggled to accurately forecast business performance due to the complexity of the ever-changing consumer and the key inputs and investments into the business. To help with a forecast transformation, AlixPartners developed a comprehensive planning tool centered around an AI-driven predictive customer forecast model. We leveraged hundreds of inputs, over many years, to predict sales for the coming year and provided clear, actionable insight into:
The results? Implementation of the AI customer forecast model and associated recommendations led to EBITDA margin improvement through increased sales and effectiveness in both marketing and promotions. The AI customer forecast also informed longer-term strategic plans through improved inventory buying for future periods. "Implementing AlixPartners’ AI-driven customer forecasting model was a game-changer for our business. For the first time, we had real-time visibility into the levers driving customer growth, allowing us to fine-tune pricing, marketing, and inventory decisions with confidence. The impact was immediate—improved short- and long-term forecast accuracy, stronger margins, and a more agile response to market shifts. This approach didn’t just refine our planning; it transformed the way we operate." — SVP FP&A |
A superior way to drive results
By shifting from traditional top-down forecasting to AI-driven predictive customer forecasting, retailers can align financial targets with operational decisions in a way that is both dynamic and data driven.
AI-driven predictive customer forecasting is not just for annual budget cycles. Retailers can leverage the output to inform various strategic decisions – from validating quarterly guidance, to testing promotional strategies before deploying them. With ongoing insights and endless adaptability, an AI-driven model empowers leadership to optimize resources, respond quickly to changing conditions, and invest strategically in the areas that matter most.
In today’s hyper-competitive and rapidly evolving retail landscape, businesses that fail to evolve will fall behind; the future belongs to those who can predict it.
Contact our experts to learn more about how the AlixPartners AI Profit Engine is helping retailers unlock the power of real-time, data-driven decision-making.
