Retail giant Amazon changes the prices of its products 2.5 million times each day, leading to an average product’s price changing every 10 minutes. With access to Big Data generated from 200 million users and 1.5 billion items, Amazon can effectively price, target, and personalize its products with data-driven suggestions. This is just one example of an e-commerce retailer using technology to concurrently price and attract customers.
Emerging technologies in the retail marketplace are impacting e-commerce and brick-and-mortar retail pricing strategies. Retail is digital, and the changing landscape needs a complex understanding of customer data and dynamic pricing strategies. While high-low pricing and everyday low pricing has defined some retailers, customers’ buying behavior is no longer dependent on price alone.
Consumer-decision journey is driven by technology
The factors contributing to the development of new pricing strategies are influenced by customer expectations and demand. Retailers need to leverage technology to enhance their customers’ decision journeys as well as their buying experience. More customers are making cross-channel buying decisions before they purchase, whether the item is in store or online. Deloitte’s Mobile Consumer Survey finds that 88% of Australians have smartphone access and anywhere between 50% to 70% of consumers research product prices on their mobile devices. This means that customers can make informed decisions about price points across retailers, track price drops, and instantly access competitive pricing of items on-the-go. It’s imperative for retailers to promote effectively by marketing to the right target audience and to manage their campaigns because customers are bombarded with choice.
Managing price, personalization, and promotion
Revamping the approach to key value categories (KVCs) and key value items (KVIs) is necessary in digital retail. Keeping prices low to beat competitors is unprofitable as retailers operate and compete in both online and brick-and-mortar stores. A dynamic, segmented approach to pricing allows retailers to optimize their objectives, whether it be factors like price perception or profit margins, and customer decision journeys. Retailers need management systems that utilize customer data to personalize deals based on previous buying history and predicting the likelihood of future purchases.
For example, if a customer purchases a mobile phone on Kogan, the website will also suggest purchasing a phone case or a screen protector based on what other customers have also purchased. Accessing Big Data and analytics allows retailers to provide a tailored customer experience while pricing to dynamic buyer segments. Collecting data from different channels and point-of-service data for analysis ensures that retailers can take advantage of in-memory technology to access data in real-time and on-demand forecasting for seamless customer experiences.
The combination of high-low pricing and everyday low pricing strategies, data, and advanced analytics allows for a dynamic pricing strategy that addresses churn and keeps up with customer demand. Customers have more decision-making power through their mobile devices. Retailers need to understand their customer, personalize their products, and refine their KVCs and KVIs to ensure competitive pricing.
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