Business owners, this is for you!
Do you want to know what retail analysis is and how it can help your business? Then keep reading because we are about to break it all down for you. Read on and learn everything you need to know about retail analysis.
Definition – What is Retail Analysis
Analytics for retail has become an invaluable tool for gaining insights into customer behaviour and the performance of a business. Retail analytics is the understanding of the data points that revolve around inventory, demand, supply chain movement, sales, and more.
With analytics, retailers can look ahead with confidence and accurately forecast what it takes to drive growth or stay on top of costs.
Additionally, access to detailed analytics helps retailers make meaningful decisions regarding their marketing strategies as well as procuring practices.
In short, retail analytics paints a picture of how well an organisation is doing and makes clear any areas for improvement and optimization.
3 Types of Retail Analysis
1. Descriptive Analytics
Descriptive Retail Analysis is one of the most common tools used by retailers today, looking to gain valuable insights into their performance and results.
While data gathering and reporting would have traditionally been a very laborious job for analysts, now it can be automated using BI tools and integration.
By bringing together raw data from various sources such as POS terminals, inventory systems, OMSs, ERPs and more, Descriptive Retail Analysis helps to show what has happened in your business in the past and present.
This is invaluable when looking to understand how an organisation is performing now and why certain trends are happening over time – something that descriptive analytics alone often cannot answer.
2. Diagnostic Analytics
Diagnostic retail analysis is an advanced analytical tool which can provide valuable insights into the performance of any retail business. Using the same data typically used for descriptive analytics, diagnostic analysis leverages statistical models, algorithms, and even machine learning to uncover correlations between data points that were traditionally hidden in plain view.
With diagnostic analysis, businesses can pinpoint anomalies before they become problems while pre-programmed benchmarks and business rules are in place to flag any issues that do not measure up.
Not so long ago, most of this sophisticated work was done manually by highly trained analysts who had to laboriously sift through every piece of data manually – today though, thanks to rapidly evolving technologies such as powerful diagnostic software, such detailed analysis is easier than ever before.
3. Predictive Analytics
Predictive analytics is a powerful tool that helps retailers to create a roadmap of the future. By combining the insights from descriptive and diagnostic analytics, predictive analytics provides an understanding of current trends and helps to forecast what is likely to happen next.
Through a combination of clustering, exception detection and complex algorithms, it is possible to make accurate predictions which allow businesses to stay ahead of the competition.
All savvy retailers should take advantage of this robust type of analysis that allows them to accurately predict their future customer demand and position themselves for continued success in an ever-changing retail landscape.
With access to detailed analytics, retailers can make informed decisions about their marketing and procurement strategies. Take a deeper dive into the benefits of retail analysis by looking at different providers of retail data. Do not miss the opportunity to gain valuable insights into your business and start upgrading your retail analysis.