How Retail Analytics can Boost your Sales

Just assuming that data alone can do wonders in the retail industry wouldn’t be wise. Data combined with the power of analytics and AI can actually do wonders for retailers and shoppers equally.

To succeed in such fierce competition, one needs to leverage the use of an amazing data analytics ecosystem. This is where retail analytics comes into play. Retail data analytics harnesses the power of data to predict consumer purchase behavior, gives useful insights into hidden patterns and trends. This in turn helps improve business performance and sales.

Pros of Tapping into Retail Analytics for your Business

Inventory Management

An appropriate retail solution is one that accurately predicts the market demand and helps form an optimal inventory management strategy. In this scenario, predictive analytics technology will enhance demand forecast accuracy by a large margin and recommend improved allocation and replenishment techniques. Furthermore, there are specific techniques that allow a merchant to reduce inventory distortion even further.

Customer Behavior Insights

Retail analytics gives you insights into the customer purchase behavior, their identity, shopping habits, and whole journey. Shopper analytics tells you what your customers like and their shopping tastes along with how your customers’ experience has been with your retail shop or businesses.

Identifying Anomalies

Comparative Analysis with the historical data can be of help many times when trying to leverage the power of retail analytics. It can often use the old data to compare with the current trends in order to arrive at useful business decisions and identify anomalies in the data.

You may also like to read: Top 5 AI Applications in Retail

KPIs to look into for Boosting Sales

• YOY(Year-over-year) Growth: A common KPI in retail and many other businesses that compare your business performance against previous year’s.
• Gross Margin Return on Investment: Quantifies profit return on the amount that you invest in your inventory.
• Sales per square foot: Foot traffic analytics helps improve store layouts to maximize sales and space efficiency.
• Average transaction value: On average how much your retail business customers are spending is the average transaction value.
• Conversion Rate: A KPI that measures the rate with which your onlookers are actually converted into your customers.
• Customer Retention Rate: This metric assesses a company’s ability to convert one-time clients into long-term, revenue-generating customers.

Based on a recent Alteryx and RetailWire survey of nearly 350 retailers and brand manufacturers, shopper insights helped them increase their customer retention by 55%, improve customer service by 55%, and improve customer targeting by a whopping 51%. This data clearly tells how much retail analytics holds importance for every retail business and should be implemented in the fastest way possible.