How Big Data is helping retail stores fight back

Share this:

image retail data analytics

Bricks-and-mortar retailers continue to feel the pain of dwindling footfall in physical stores as customers drift to online shopping. The trend gathered momentum during the pandemic, with lockdowns pushing even more consumers to e-shop.

In 2021 more than 80% of Australian households purchased something via the internet. They outlaid a record $62.3 billion online for the year, representing 19.3% of the nation’s total retail spend.1

But digital is a double edged sword. The same cloud technology leveraged for eCommerce, coupled with advances in mobile, IoT, Big Data and Analytics, allows retailers with physical stores to better understand customers and manage their assets more effectively.

Retailers can mine information already in their systems to learn not only what shoppers want, but also when, where and how they want to buy it. By collecting and analyzing customer demographics, buying patterns, responses to promotions and loyalty program trends, retailers can:

Avoid inventory shortages and pile ups:

Identifying better performing brands, products and categories ensures inventory is managed to meet demand.

Place products to sell more:

Both in store and online displays can be organised so the optimal mix of desired and moving products are prioritised.

Target promotions for increased conversion ratios:

Offers and suggested add-ons (upselling) can be personalized based on a customer’s buying patterns and recorded interests.

Evaluate marketing campaigns:

Data is available to support recency, frequency, and monetary (RFM) reports, store and product-level analysis of promotion effectiveness, the impact of merchandising and re-arrangement efforts and other marketing activities, providing an evidence base to assess marketing investments.  

Forecast demand:

Identify emerging trends across product ranges and compare these with historical figures for more accurate forecasts.  

Personalise loyalty programs and promotions:

Improving data collection for more nuanced segmentation allows for more targeted loyalty rewards and promotions. Understanding enrolment growth rates, activity trends of loyal customers, purchase details (points earned/redeemed/expired) and total purchases versus purchases by registered customers empowers retailers to evaluate their loyalty programs for better return on investment.

Staff and stock by store demands:

Data on shopping trends across different customer segments – like preferred day and time of purchase, goods category, and brand preferences – can be cross-referenced with footfall and staffing levels down to store area level. Stock and staff decisions can be managed more responsively, providing a more rewarding experience for customers and staff alike.


Retail data analytics makes all of this possible. The right data, analysed intelligently, is a powerful tool.

The advantage of retail analytics, however, runs deeper than improving the bottom line for physical stores. It helps any retailer adopt an omni-channel approach to consumer sales, dovetailing a traditional in-store presence with online and social media-driven shopping for a seamless, customer focused approach.

1. Australia Post | Inside Australian Online Shopping eCommerce update | February 2022


Sonata Connected Retail

Sonata Software is an industry leader in data platform services. Our Platformation™ approach supports enterprises pursue digital transformation by anchoring data as a primary asset. With retail industry-specific solutions and 30+ years global experience in the retail sector, we leverage platforms and technologies from leading industry players – Microsoft, Amazon and Open Source – to implement data analytics and visualization solutions.

Read about Sonata Connected Retail here. If you’re ready to talk more about retail data analytics for your business, email us or fill in the form below.