A version of this Blog was first published on the LinkedIn Pulse.
Before the advent of retail data analytics, retailers depended on traditional business methods. They determined the demand for products based on hunches and intuition instead of using calculative methods and rationality of data and statistics. Critical business decisions like staffing, opening a new retail store in a specific location, pricing, etc., were based on intuition instead of a 360-degree view of the market and demographic study of retail store locations.
Of course, this was not the ideal approach since the retailers might end up stocking more or fewer products without a comprehensive understanding of the trends.
With retail data analytics, entrepreneurs and retailers can study customer behavior data, marketing forecasts, and product demands. With the insights generated, they can determine competitive product pricing strategies, target specific customer needs, and create personalized marketing campaigns to increase the overall efficiency and boost sales.
Retail data analytics involves collecting and studying data on supply chain movement, sales, inventory levels, pricing, consumer demand, and competitor strategies. One of the most crucial aspects of retail analytics is the ability to foresee the competitor's moves by having access to their present data. This proves to be a game-changer for retailers.
The insights on demand and supply data too can also help retailers make crucial procurement and marketing decisions if executed correctly. It allows retailers to gain meaningful insight into the performance of their stores and products, customer behavior, and vendors, among others. Retail analytics gives retailers precise customer insights along with a detailed breakdown of their business processes and identifies core areas for improvement.
Digital transformation demands increased flexibility and a competitive mindset that will set retailers apart from their competitors. Gartner, Inc. predicts that 75% of companies will shift from piloting Artificial Intelligence (AI) to operationalizing it by the end of 2024. This will drive a five-fold increase in analytics infrastructure and streaming data. To achieve this, retailers must combine state-of-the-art technology and business patterns with market-disrupting innovation.
The core aspects that can help retailers maintain their competitive advantage include-
A diverse range of business operations and technology applications yields colossal data mounds. When retail data analytics solutions are re-defined to a more intelligent mechanism, businesses can leverage this data to gain a competitive edge.
Retailers can harness the incredible power of retail data analytics to explore new business methods and retail solutions with the combination of forecasting, advanced analytics, a high-performance blend of insights, and visualization.
The most notable benefits of using retail data analytics are-
If you are still not convinced of the importance of retail data analytics and its impact on businesses, you can look at how some of the biggest global companies have integrated it within their business models.
Enterprises like Amazon and Google rely entirely on business analytics models and use big data to provide enhanced customer services. Data analytics are widely used in hospitality, health, e-commerce, travel, and big retail chains. Using data analytics, companies offer personalized customer services and target marketing campaigns based on customer demography. It also helps them in enhancing customer experience and addressing potential service issues.
Statistics show that by the end of 2022, the global retail analytics market is expected to reach USD 8.6 billion. The figure will continue to rise over time. In such a competitive scenario, if retailers aren’t using retail analytics, they miss out on an ocean of opportunities. Hence, adopting retail analytics is the way to go for modern retail businesses.
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