Data analytics helps companies in the retail industry to uncover operational inefficiencies and discover new sales opportunities. Also, it lets the retail players predict the spending of their customers. Retail businesses use data analytics to increase their sales, deliver targeted promotions, and discover continual growth opportunities. Here is an article on how data analytics is helping retailers do better business.
1) Forecasting Demand in Retail Sector
Many factors are determining the demand in the retail industry. And the weather is an important parameter to forecast retail demand. For example, companies such as Walgreens and Pantene have collaborated with The Weather Channel to forecast weather patterns and customize product recommendations. They serve ads and run in-store promotions focused on anti-frizz products as soon as they forecast an increase in humidity. This increased the sales of Pantene products at Walgreens by 10% over two months and Walgreens witnessed a 4% increase in sales across the hair care category. Besides, different retail forecasting and projection methods help to allocate resources effectively throughout different seasons.
2) Customer Journey Analytics
Customer journey is an important factor. Big data analytics solutions analyze the journey right from customer communications to in-store experiences, and from purchase trends to ad interactions. Consequently, the retail companies get complete control of the customer journey and produce better customer experiences. Furthermore, this helps to decrease the chances of cart abandonment, and increase the likelihood of a sale.
Data Analytics enables retailers to understand how to guide customers to complete their purchases in the best way possible. Analytics solutions help retail companies to answer the below questions:
- Where do customers search for detailed product information?
- Where do businesses lose customers?
- What are the most effective ways to reach customers?
- What are the best methods to convey the USPs to customers?
3) Organizing Retail Customers
Predictive data analytics helps to segment customers better. Data analytics solutions help retail businesses to predict the customer lifetime value. It enables them to predict the value of customers over time and segment the customers.
Retailers apply affinity analysis to organize the customer list based on common parameters. Likewise, they use response modeling techniques to analyze customer response history to predict the effectiveness of future marketing approaches. On the other hand, churn analysis enables retailers to know the percentage of lost customers and the consequent loss in revenue.
4) Understanding Customer Behavior and Marketing Promotions
Data analytics solutions help to track customer behaviors. It enables retailers to understand how their customers shop, what they like, and how they prefer to receive offers. Consequently, retailers optimize their marketing efforts and craft the best offers. Also, they discover methods to personalize products, increase customer retention, and improve sales.
Data analytics helps to know where to spend on ads and promotions. Also, it enables the retails to know when to increase the marketing expenditures.
5) Retail Store Experience Tracking
The in-store experience is an important aspect for omnichannel retail platforms and brick-and-mortar stores. Data analytics powered by sensors and beacons lends a helping hand through tracking customer movements inside the store. This helps to deliver the best customer experiences, knowing where to focus and what leads to the customers visiting the shop again.
6) Operational and Supply Chain Improvements
A poorly maintained inventory is a big problem for retail stores. An optimized supply chain is necessary to ensure better operational efficiency. Data analytics helps to know what to store and discard at the right time. Consequently, the retailers optimize performance and decrease costs. Data analytics enables real-time inventory management and demand forecasting. Furthermore, it helps to speed up the delivery of goods.
7) Price Optimization
Retailers used to drop the prices after a festive season or when the demand becomes dull. But that is all before the advent of data analytics. Now, data analytics solutions help retail companies to utilize price optimization and markdown optimization strategies. As a result, the retail companies know when demands can reduce, and when to optimize the product prices.
8) Discount Efficiency
Data analytics helps to determine the efficiency of discount schemes in retail shops. They use data analytics tools to find the impact of discounts on a long-term basis. And they alter the discount schemes across multiple categories while stopping less profitable discount schemes. Consequently, the average monthly revenue of the retail shop increases.
9) Determines location for new outlets
Data analytics helps retailers to know where people spend most of their time. Furthermore, it provides insights on the customer demographics, customer spending power, and market scenarios. This helps the retail companies to choose the right geographical areas apt for opening a new retail outlet and attracting new customers.
In the end, retailers who use data analytics will continue to win more customers. It helps to know the deeper connection to the customers’ desires and requirements based on actionable insights. As a result, data analytics act as the key to higher sales in the competitive market.