The retail industry is a growing part of the big data revolution, but exactly how should retail organizations start integrating data analytics into their business models? The question doesn’t have a straightforward answer, but it helps to understand the role of data for modern retail companies. You might be tempted to hire your own data analyst or data scientist, or even a team of them for large-scale operations, but is that really your most efficient use of resources?
Let’s start by breaking down some of the ways that data is important for retail companies:
- Profitability analysis: Store owners can study any retail key performance indicator to get a better understanding of how their business works. They can quickly forecast revenue, determine profitability, and ultimately pinpoint areas where the business might be underperforming. KPIs like average transaction size, average units per customer and rate of return can tell you everything you need to know about the health of your business.
- Customer understanding: Data is also indispensable in getting to know your customers better. With the right market research and suitably sophisticated levels of analysis, it’s possible to get a glimpse into how your customers tick, understanding their wants, needs, beliefs and values. Retailers can then use that information to create or sell better products.
- Competitive analysis: With enough resources, it’s possible for retail companies to look into their competition and understand how they operate. They can analyze competitors’ profitability, and study the variables that make them different. With enough information, it’s possible to improve your business in a way that exploits your competitors’ weaknesses.
- Predictive analytics: Predictive analytics are another key area for the retail industry, with practically unlimited applications. Retail companies can project things like the ebb and flow of trends, the transformation of customer demand, and the optimal pricing for products. With the right equations, they can change their investments, employees and even their annual goals to compensate for these predictions.
- Inventory and supply chain management: Data is valuable for keeping tabs on inventory levels, which retailers need to keep in careful balance in order to keep profits high. Through insights rooted in big data, companies can analyze weaknesses in the supply chain and hammer them out to improve efficiency.
- Marketing and advertising: Retail companies active in marketing and advertising can also find applications for data analysis. Understanding customers and target markets is a good start, but with the right equations and data platforms, it’s easy to analyze how and why your advertisements work, using that information to improve future campaigns.