Retail Data Analytics - How Data Science Improves Retail Market
Both are crucial for maximizing sales capacity in the highly-competitive marketplace.
Retail data analytics, a big data and data science-based approach, is about collecting and studying customer data to discover customer preferences and identify trends. These are vital to making more accurate business decisions. Taking a strategic, data-driven look at retail transactions yields invaluable insights into consumer needs. It also tells a lot about the performance of stores, products, and vendors.
How can vendors increase sales and optimize business costs with data? We looked at the key benefits that retail data analytics will bring to your business.
Increasing revenue with retail analytics
Analytics of various data points can play a major role in increasing revenues. According to Boston Consulting Group, retail industry companies that successfully adopt a data-driven approach to retail can boost their revenues by up to 20%. Here’s how.
In-depth insights into customer inquiry
Retail data analytics can provide retailers with information about customer data, like product search inquiries. An in-depth look into what products (or sets of products) customers search for online helps them to discover exact customer needs, even in the narrowest segments.
In fact, retail analytics help sellers understand the specific qualities consumers are looking for in a given product and subsequently use them to quickly and effectively streamline sales.
With these key insights, retailers can meaningfully expand the range of their products to include those that will actually sell. You will know what products (or product ranges) are in demand and thus be able to refine your offering accordingly.
In addition, by analyzing transactions, retail industry can identify products whose sales are under-performing overall or in certain customer segments. They can then investigate the reasons behind the under-performance and use the information to refine products to meet customers' needs better.
Precise customer segmentation
Retail analytics fuels advanced customer segmentation, allowing retailers to prepare highly-personalized funnels for each customer segment and ensure customized customer journey. By collecting and cross-referencing numerous data points within specific customer groups, vendors can effectively pinpoint customers’ needs and meet them with ease.
You will not only understand what customers are buying and in what quantities, but also their purchase history, when and in what context. If you use this data wisely, you will be able to predict and answer customer demands before they arise and adjust customer journey to these demands.
With retail data analytics, you can improve customer experience by using actionable microclusters based on particular attributes assigned to your customers and increase the chances of upselling and cross selling. Businesses should capitalize on this opportunity, since they are more likely to upsell or cross sell ( 60-70% according to Hubspot) than sell to new customers.
Understanding seasonal products
Apart from customer segmentation and deep insights into customers’ inquiries, retail data analytics identify sales patterns that enable retail businesses to forecast sales and reveal which products are in true demand exclusively over a specific period of time. Inventory data allows retailers to improve their inventory management to offer specific, seasonal products when they’re in high demand and temporarily de-stock them while they don’t sell.
Retail analytics can also help vendors to understand why certain products aren’t in demand throughout the remainder of the year and optimize consumer flow accordingly.
What is more, understanding the seasonality of products allows retailers to effectively plan and diversify their supply chains. You will be able to identify the lifecycle of specific products, as well as the length of the season and time of purchase, which allows you to streamline the supply chain in a more optimal way.
Reducing costs with retail data analytics
Retail data analytics can be instrumental in reducing business expenditures. Companies that evaluate their data effectively note as much as a 30% increase in cost efficiency. Here are the advantages they can benefit from.
Effective inventory management
The ongoing pressure to adjust one’s offering to changing market demands may sometimes push retailers to bear unjustified costs, e.g. stocking products that don’t sell well. Applying retail data analytics to manage inventory and supply chains enables effective inventory management and improving the overall control of stock.
This approach lets you manage the inventory levels - what you need to store, when, in which stores and in what quantities, as well as when to remove stock from your warehouses. It also helps to understand which items are the bestsellers (and how much revenue they account for) and which don’t drive this much revenue and aren’t worth space in your inventory.
Without good insights into inventory data retailers are exposed to delays and disruption of their supply chain operations, which ultimately translate to revenue losses. Advanced retail analytics are your protective shield against these problems.
Retail marketing strategy optimization
The pandemic fueled economic uncertainties and made consumer buying behavior even more unpredictable. Knowing what products to focus on became a great challenge for retail marketing teams. However, data analytics made planning targeted marketing campaigns much easier and more effective even in uncertain times.
Deploying retail data analytics helps to quickly discover anomalies in buying behavior, allowing marketing teams to make informed adjustments to their campaigns and optimize marketing costs. Retailers will also understand in which segments they are ineffective, and plan their marketing accordingly.
Last but not least, retail analytics enables vendors to observe real-time pricing and performance of direct competitors (in accordance with applicable laws and regulations). They can then quickly react to changing market conditions and find the right balance between price and sales volume. Ultimately, they are able to maximize the income and find the equilibrium revenue.
Virtual try on applications
Customers value personalized shopping experiences and offering size matching is one way to do it. With retail data analytics, sellers will provide this feature with ease.
Some retailers analyze the sizes across different brands and, based on customer reviews and shoppers’ choices, communicate whether the size is smaller or larger than the regular measurement. Others recommend relevant product sizes based on previous purchases. Regardless of the option you choose, virtual try on applications will reduce the costs related to handling returns and exchanges.
Safe experimentation with retail solutions
Customer demands are changing fast, which forces retailers to experiment with different solutions. If this isn’t challenging enough, retailers have to face increasing competition, declining sales, and shifting to e-commerce at an unprecedented pace. To thrive in such a landscape, they have to be able to respond swiftly to these evolving market demands.
Retail data analytics ensures vendors have all the information they need to make the right business decisions under pressure. Using historical data, shopper insights and sales data, they are more likely to make smarter decisions and stay ahead of their competition.
With retail analytics, sellers can quickly experiment and test different approaches to marketing specific products within different customer segments - not at random, but based on meaningful insights. A/B testing is no longer the king. Validate multiple scenarios simultaneously and obtain valuable insights.
Improving your business with retail data analytics
Retail data analytics are essential for businesses to thrive in today’s dynamically changing markets, amid fast-evolving consumer preferences. It allows retailers to stay on top of these changes and improve the decision-making process oriented at reducing costs and increasing revenues and ensure a high level of customer satisfaction.
By collecting and analyzing data in large and diverse volumes, retailers are able to understand the deepest customer needs and adjust their offering to meet shoppers’ demands and offer personalised, hard-to-resist deals.
We provide support with data analytics software to numerous retail customers and we are happy to help you improve the decision-making process in your organization as well. Get in touch with us directly and we will be happy to discuss how we can help your business.
