The times have changed. Rapidly. In less than a year, you probably weren't expecting a store to offer curbside or in-store pickup. Today, that may not be possible.
A seamless, easy, and fast shopping experience is what customers expect. Companies must use retail analytics to deliver the experiences customers want and remain competitive. Here are the three top trends in retail analytics that retailers are using to stay competitive.
Why should retailers use data analytics?
Taking a retail analytics approach will enable companies to automate seamless customer experiences between online and physical channels while putting customers at the centre of their decisions. The retailers who are utilizing retail analytics proactively are already seeing significant improvements in business results by acting on their own insights quickly.
Furthermore, the most successful retailers are finding ways to exploit second and third-party datasets to propel their business strategy. First, it is critical to building a data foundation that incorporates internal and external data to provide the required details of the customer experience.
What are the major retail trends?
Here are 3 key trends in retail analytics companies are using to gain a competitive advantage. A few of them include personalized experiences, predictive analyses of spending and demand, and dynamic pricing models. In retail analytics, such capabilities are only possible when all data is consolidated into a single source of truth. In order to remain competitive, many retailers turn to data analytics services to help build and deploy the required modern data infrastructure. After establishing a retail analytics approach, your organization can take advantage of the following trends.
Provide hyper-personalized service to a niche market
As part of a 2017 survey, Epsilon surveyed 1,000 consumers aged 18-64 with the goal of helping brands to maintain and grow customer relationships. According to the survey, 80% of respondents are more inclined to do business with a company that offers personalized services. Since then, the demand for personalization has only increased. A 2020 McKinsey article on retail differentiation suggests that the best experiences “involve customers in the process and leverage data to create one-on-one individualization.”
This is only possible with Customer 360, a comprehensive view of a customer's data across all their interactions with the company. A variety of information is collected during these interactions, including transactional data, customer feedback, shopping preferences, and website and mobile app usage.
In tracing customer interactions at this level of detail, management is able to gain a much greater understanding of shopper expectations and needs. By delivering unified experiences, retailers can provide customers with niche offers that are relevant to highly refined segments of the market. By creating a hyper-personalized retail experience for your customers, you can significantly increase total sales by increasing loyalty and share-of-wallet.
Having a unified data and analytics platform is necessary for implementing and scaling this level of personalization. The level of information that can be uncovered through a Customer 360 strategy goes well beyond personalization, providing unprecedented value. It has been shown that retail analytics can improve business decisions in areas like innovation, marketing, merchandising, supply chain management, and customer service in addition to others.
Identify spending trends and forecast demand.
Using advanced analytics, retailers are making predictions using algorithms and machine learning. Advances in analytics provide retailers with the ability to predict the future of their businesses based on trends founding a defined time period.
Through timely notifications and valuable offers on relevant products, business leaders are using demand forecasting to bring back the most profitable customers. Therefore, retailers are able to make sure they are shipping products that their customers want on shelves at the right time while improving their supply chain at the same time.
According to a recent Forbes article, Patrick McDonald, Director of Data Science at Wavicle Data Solutions, advanced analytics can help retailers boost their sales by dynamically increasing inventory margins:
Using stochastic analysis to analyze forecasts enables us to make better inventory decisions. Analyzing future events by analyzing alternative outcomes is a form of scenario analysis. Rather than showing a precise view of the future, it presents multiple alternative future scenarios. Analysts can calculate the optimal inventory range when they can see a range of possible future outcomes.
Some retail leaders even use predictive analytics to calculate their customer's lifetime value to improve customer retention.
Automate and dynamically price products.
Keeping a percentage of their prices low helps retailers stay competitive. Regardless of price, low-priced, doorbusters and key-value items (KVIs) are often the best sellers and driving force behind a retailer's price brand. The result is that KVIs may represent up to 80% of a retail company's revenue, but only 50% of its profit. As compensation for the low margin of KVIs, retailers tend to raise the prices of their higher-margin items and position them in creative ways alongside doorbusters and KVIs to encourage shoppers to add higher-margin items to their carts.
Increasing the profit margin on their products enables retailers to sustain themselves and grow. The introduction of dynamic pricing algorithms in particular has made a tremendous difference to retailers. Pricing models that use dynamic pricing can automatically make a recommendation on prices, freeing management to make more informed and timely decisions that positively impact the company's bottom line. In order to be truly effective, we recommend consulting with an analytics firm to build a custom solution that is developed in accordance with a retail company's business objectives, internal operational processes, and customers.
The company faced several challenges, such as losing market share to competitors that had developed a more advanced data infrastructure, enabling them to offer lower prices with a wider selection of products. As a result, clients choose Wavicle's data analytics consultants to build a customized cloud-based order management portal to make it “faster and easier to evaluate and optimize prices, search for products, and manage inventories.”
Follow-up
For retailers to compete with e-commerce giants and local brick-and-mortar stores, they must prioritize a customer-centric data and analytics approach. A new generation of AI models and advanced machine learning algorithms will continue to emerge, leading retailers to leverage retail analytics in order to uncover insights that will lead to a more loyal customer base.
Are you lacking the expertise or resources to adopt a retail analytics approach? You can align your strategy with your desired business outcomes by working with experienced data analytics consultants.
