The retail industry is experiencing never-seen-before digital disruptions from online and instant shopping to quick home deliveries. In times of new experiences, it is vital to understand the drivers behind the perceived behaviour – especially when it comes to differences in sales revenue. Retailers who use data analytics in their organisations are ahead of the curve when it comes to customer experience, customer motivations, effectively marketing to customers, and market trends. With an integrated tech infrastructure, retailers are driving competitive advantage by gathering, analysing, and leveraging their unique business data with data from their industry. Using data-driven insights goes beyond merely tracking trends; efficiencies in daily operations become available and these directly affect cost savings and market position.
Let’s explore the variety of ways in which retail data analytics is used in the retail industry.
Key Market Trend Insights
Advanced analytics (with machine learning techniques) allows retailers to see current market trends and predict future market trends. Predictive analytics is a pre-emptive approach, where retailers use data from the past transactions to predict future sales growth based on consumer behaviour changes and market trends. This can help retailers stay ahead of the curve, compete effectively and gain considerable market share.
This allows retailers to make data-driven decisions regarding employees and business growth – preventing organisations from being over/short-staffed and not having high-demand inventory well stocked.
Inventory Access and Customer Expectations
Due to the advancement in technology, customers expect to easily be able to view what is in stock at different store locations online. This means retailers need to practice excellent inventory management with radio-frequency identification technology to ensure full inventory transparency for curious customers. Retailers are using data analytics and predictive analytics to maximise this capability to increase online, cross-channel, and physical sales. By understanding how much inventory is available, where it is located, and where the demand for it is, retailers can ensure they meet customer needs and expectations.
Data analytics allows retailers to understand exactly which people are buying their stock. This provides retailers the opportunity to ensure their marketing efforts are relevant to their target market and that their efforts are effectively interesting their potential customers. Retailers can analyse their customer data to produce a tailored shopping experience that customers value and enjoy. For example, by analysing customer profiles from social media data, retailers can find insights into how to more effectively target specific customers. A customer whose data contains searches for “work clothes” with an active Facebook presence would be a great re-marketing target for work clothing retailers. By analysing customer data this way, retailers encounter higher conversion rates and a reduction in customer acquisition costs. Research shows that modern customers expect customised marketing messaging that result in a more productive store visit: this is why data analytics is essential to provide customers with their own unique shopping experience.
Online shopping and mobile applications serve many functions for retailers: from providing a personalised, location-specific digital shopping experience to the customer to delivering insightful data to the retailer. Research has shown that 75% of online customers are more likely to purchase online when a company knows their name, purchase history, and can suggest products based on their preferences. Physical retail sales are decreasing as online shopping continues to grow. In order to attract new customers and keep existing customers loyal, retailers need to improve their availability and services online while baring in mind statistics (like the previously mentioned). The key to keeping customers happy, lies in analysing customer data.
Data analytics has the potential to help retailers lighten the load of stressful “unknowns”. In order to make the most of the potential that customer data can offer, retailers must ensure they have an easily-understandable data analysis system in place to collect, store, and analyse their data. The effective retail organisations turn to well-known technological leaders to make their data analysis goals achievable. Microsoft’s Power BI is a collection of software services that bring data together from different sources into visual and interactive business insights. This data analytics software allows users to discover what is important in their data and ultimately allows for business decisions that is based on unique company and market-related data. Does your retail business use data analytics to drive business decisions?
Contact Agile Analytics to begin creating a retail business that is data-driven.