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Retail Analytics: How ERP Systems Transform Data into Profits

Retail analytics provides powerful insights into how retailers can transform their businesses from just making ends meet to enjoying profitable success.
Retail Analytics: How ERP Systems Transform Data into Profits

The Importance of Data Analytics for Retailers

Modern companies with access to powerful retail analytics tools can unlock new opportunities for expansion that were unimaginable in the past. Retailers use accurate, easy-to-access data from different sources within and outside their company to figure out what customers buy, when they buy it, why they buy it, and how they buy it. This helps them see what might happen in the future and make better decisions. Internal data sources may include a point of sale, inventory tracking, or enterprise resource planning (ERP) system, and external sources may include demographics and market data.


The Role and Benefits of Retail Analytics

Gathering and analyzing accurate sales, inventory, pricing, and planning information helps modern retailers make better, more customer-friendly decisions that can lead to an expanding customer base and higher profits. Knowing how much inventory to keep on hand, how to price products, and what steps need to be taken now and in the future paves the way for the best, most profitable outcomes.

In addition to improving decision-making, data analysis benefits retailers by offering visibility into:

  • Product performance and sales.
  • Customer behavior.
  • Optimal inventory levels and price points.
  • Lost sales.
  • Staff levels.
  • Profit margins.

Retail analytics also helps retailers develop effective marketing strategies, maximize physical store layouts, and nurture sales in-store and online.

The Need for ERP Systems in Retail Analytics

Modern retailers rely on enormous amounts of data, and the traditional, time-and-labor-intensive methods of sorting that data manually, plotting numbers in Excel, and making forecasts based on personal expertise are no longer viable. In other words, retailers operating in today’s digital economy need a comprehensive business management solution, such as an Enterprise Resource Planning (ERP) system, that can draw data from every department and third-party application in a company and automatically store, organize, analyze, and report on that data.

But not just any ERP system will do. Retailers should select a solution that facilitates all four types of retail data analytics: descriptive, diagnostic, predictive, and prescriptive.

ERP Systems and Descriptive Analytics

Descriptive analytics answers the question: “What happened?” It gives retailers a complete picture of what’s going on in their businesses, including sales, inventory levels, and customer information. A modern ERP solution should include business intelligence (BI) and analytics capabilities that take raw data from multiple sources and transform it into easy-to-read visuals (e.g., data tables, pie charts, bar graphs, etc.), so retailers can understand, explore, and use the information efficiently.

ERP Systems and Diagnostic Analytics

Diagnostic analytics answers the question: “Why did this happen?” It uses the information gained from descriptive analytics to help retailers identify and diagnose organizational problems and patterns. Diagnostic analytics applies artificial intelligence (AI) and machine learning (ML) to process more data and variables than is humanly possible. The right ERP solution will provide this AL and ML technology right out of the box.

ERP Systems and Predictive Analytics

Predictive analytics answers the question: “What will happen next?” It uses sophisticated algorithms and statistical models to provide retailers with insights into future trends. It’s the foundation for forecasting customer demand based on historical data. A modern ERP system can be used to gather historical data, analyze it with automated calculations, and act upon it in real time.

ERP Systems and Prescriptive Analytics

Prescriptive analytics answers the question: “What is our next move?” It uses technology—like an ERP system equipped with AI and ML features—to analyze datasets and prescribe optimal courses of action. According to Investopedia, when used effectively, prescriptive analytics “can help organizations make decisions based on highly analyzed facts rather than jump to under-informed conclusions based on instinct.” Not all ERP systems cover prescriptive analytics in the same way, so savvy retailers must carefully consider each vendor and choose technology that fulfills its promises of “real, concrete results.”


Data analytics for retail is quickly becoming a foundational requirement in today’s technology-driven marketplace. ERP systems are integral to establishing concrete retail analytics that will improve customer satisfaction and profitability levels—providing the critical information and analytical capabilities that companies need to succeed.

“Access to data is the winning factor. [With Acumatica], we’re now able to put together budgets and forecasts and make wise financial decisions because we have data available to do that.” – Nakuma Scott, Vice President of Technology, Killer Merch

“We’ve come to rely on Acumatica to run the whole company. It’s cool to see how far we have come and that we don’t have to make guesses anymore. We can make decisions based on the information in front of us in Acumatica.” – Jenni Arant, Chief Strategy Officer of Jeffree Star Cosmetics and Executive Vice President of Killer Merch

See what’s possible when you have a future-proof ERP platform that truly puts customers first.

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