“You cannot rest… your competitors are going to continue to raise the bar.” – Mary Dillion, President and CEO of Foot Locker at NRF 2025.
Think about Amazon for a moment. What started as an online bookstore is now a global giant with leadership across – cloud computing, e-commerce, eBooks, video streaming, smart home devices, and even last-mile delivery. And it’s not slowing down—over the next decade, Amazon will likely deepen its hold on existing markets while venturing into new ones.
What makes this possible? Their obsession with “METRICS”.
In today’s world, retail runs on numbers—inventory levels, customer visits, sales counts, and more. But unorganized metrics alone don’t drive decisions. They must be organized, analysed, and turned into insights for better decision-making. That’s where retail analytics comes in.
In this blog post, we’ll explore the power of retail analytics and how its applications are reshaping the future of retail.
The Growing Importance of Analytics in Retail Industry
The global retail analytics market is growing rapidly. According to Fortune Business Insights, it s expected to grow USD 31.08 billion by 2032—reflecting a strong CAGR of 17.2% during 2024–2032. This growth spike demonstrates the transformative impact of retaila analytics.
McKinsey’s segment-specific study also highlights how retail analytics can resolve operational complexities and unwire new opportunities. But, in most companies, analytics remain siloed functions across departments like – marketing and planning, limiting the potential value. With data analytics now impacting nearly every business domain, many retailers struggle to decide where to focus their investments on building abilities.
To effectively enhance the possibilities of analytics, retailers need a forward-thinking approach. This starts with figuring out the areas where analytics can drive the most impact. Developing a cross-functional roadmap is pivotal—one that looks across operations to spot complexities, identify growth opportunities, and makes sure that investments in analytics deliver max business value.
Major Application Areas of Retail Analytics
#1 Inventory management with confidence
In the current scenario, poor demand forecasting can cause issues throughout the supply chain. When retailers can’t predict accurately what customers need, it leads to overproduction at the manufacturing level. According to a finding, on average, 12% of all apparel, accessories, beauty, and home goods produced globally remain unsold at the end of every season, resulting in $180 billion in lost sales and an increase in waste.
Leading retail brands are moving towards retail analytics to drive intelligent decisions across forecasting, segmentation, and visibility.
By solidifying supplier collaboration, enabling end-to-end clarity, applying advanced forecasting models, and SKU-level segmentation, retailers can decrease inefficiencies, optimize availability, and accelerate profits. Data-driven strategies can build long-term resilience and resolve short-term issues, ensuring future-ready and agile supply chains.
#2 Autonomous decision-making
Gartner predicts that by 2028, agentic AI will make at least 15% of everyday business decisions autonomously—up from virtually 0% in 2024.
In the retail sector, decisions often depend on instinct and reports. Agentic AI cuts through the noise by offering transparent, data-driven actions rapidly. Whether a corporate team analyses performance trends or a sales associate adjusts floor displays, AI can diminish decision timelines from days to minutes.
That speed can be a significant competitive edge. When inventory issues arise or customer preferences shift, retailers that can act fast and first are more likely to bring sale and retain loyalty.
#3 Set the right pricing
Cost is the starting point of any pricing decision—and for good reason. You cannot set a profitable price point without understanding what it costs to produce and sell your services/products. However, cost alone does not determine pricing. Effective pricing strategies also consider competitor actions, and the value customers perceive.
With pricing analytics at disposal, retailers can max their ROI at the customer level across manifold touchpoints in their buying journey. Cost optimization is not just about cutting expenditures – It’s a strategic imperative, a data-driven perspective that balances efficiency with competitiveness – It’s not just about cutting expenses.
From improved CX and better inventory management to capitalizing on timely opportunities, retail analytics solutions assist businesses to cut costs while enhancing growth. Whether it’s about streamlining operations, running a marketing campaign, or managing warehouse stock, price optimization help retail execs to strengthen performance and positively impact the bottom line.
#4 Know Your Customer Better
In the new omnichannel world, knowing precisely where a prospective customer will start engaging with brands and possibly purchase or abandon their quest for an item is impossible.
This is where the data makes the difference. Currently, data is accessible at nearly every touchpoint where consumers and retailers interact – both online and offline. This diverse data is then analyzed using techniques such as predictive modelling, customer segmentation, basket analysis, and real-time personalization.
By connecting these insights across channels, retailers can understand which products resonate with which customers, identify friction points in the purchase journey, and deliver targeted offers and experiences that drive engagement and conversions.
Final Thoughts
So, it can be stated that, retailers that utilize the power of data will lead the tomorrow’s market. Embracing tech like AI and ML is not optional anymore – it’s a mandate. Metrics doesn’t matter; it is data that curates value when used intelligently.
At Polestar Analytics, our retail analytics experts can help you unwire the complete potential of your data by embedding cutting-edge technologies, advanced analytics, and proven industry best practices to turn info into business benefits.
