5 Ways Retailers Should be Using Big Data Analytics
5 Ways Retailers Should be Using Big Data Analytics
Big data is powering millions of businesses across industries. It’s transforming how companies interact with their customers, sell products and services, and approach business strategy. Organizations can now access more data today than ever, but this information is useless unless you know how to put it to work.
Big data – huge datasets collected by organizations, characterized by VOLUME of information, the VELOCITY at which the information is collected, and the VARIETY of information.
Companies must analyze the data they collect to bolster decision-making to win in today’s busy retail market. Data analytics software turns these vast data sets into actionable insights that can spur product innovations and deliver high-quality and multi-channel experiences—two things in today’s world that offer brands a competitive edge.
Big Data Analytics for the Retail Space can help companies make short-term strategic decisions regarding things like product merchandising and in-store optimization, and it’s beneficial when companies must make the riskier, long-term decisions such as forecasting demand for new product launches or deciding where to open retail locations.
Companies that analyze big data gain a deeper understanding of the market and their consumers. They can leverage these insights to set more realistic business goals and deliver better customer experiences. The businesses that don’t? They simply fade into the background.
Here are 5 ways we think retailers should be using big data.
1) Develop better products
A core benefit of big data analytics is learning what consumers want. What problems are people struggling with, and how can your product solve them?
Today’s world changes at a rapid pace. Innovations solve old problems only to create new problems. Thanks to the internet, new trends are constantly replacing current ones. Big data analytics is the tool you need because it will help you anticipate these trends and predict customer demand. Any data you collect from your eCommerce platform, social media, or customer surveys can guide your strategy when developing, producing, and launching new products. This can include browsing and purchasing behavior, viral internet trends, and customer feedback.
Plus, you can classify key attributes of past and current products and then model the relationship between those attributes and the commercial success of the offerings. This can help you build predictive models for new products and services. You’ll have to analyze a high volume of data in varying formats, so segmenting this data according to customer behavior is best.
2) Elevate the customer experience (and improve customer satisfaction)
Big Data gives retailers a clear view of customers’ engagement with your brand. You can fine-tune your decision-making by tracking user behaviors on your website, eCommerce platform, email campaigns, and social media. And everything is about keeping consumers on your website, moving through a great customer experience. Big data makes a big impact such as:
- Optimize your product displays and web layouts
- Creating targeted marketing campaigns and personalizing offers
- Enhance your quality of customer service
- Train your customer service team to fix certain issues proactively
- Update payment methods to meet customer preferences
Numerous other retailers compete for customers, so your goal is always to maximize the value you deliver. This builds brand trust and loyalty among your customer base. In a climate where consumers are more knowledgeable about brands than ever, this trust can be the differentiating factor between you and your competitors.
Excellent products and intuitive shopping experiences are key to winning customer loyalty, and you can only successfully deliver these one once you understand what customers want. And since consumer behavior is constantly evolving, tracking and analyzing your customers’ interactions with your brand will help you stay looped in on the newest trends and preferences.
3) Identify your most valuable customers
Behavioral analytics provides insights into online browsing behavior and spending patterns; you can identify your best customers using these insights. We’re talking to your high-value customers who are repeat buyers and advocates of your brand—knowing who they are would enable you to tailor your business strategy to ensure they stick around. Sales teams can devote more time to them, and customer service can work more proactively if incoming data indicates they may leave.
Which age group do your repeat customers fall in? What is their gender? Geographical location? Big data can provide these important details and more to help you create products that appeal to these demographic groups.
Most importantly, knowing who your most valuable customers are gives you the advantage of sending the right message to the right people, sometimes even at the right time. You can send personalized communications, offers, and discounts to these customers to elevate their experience with your brand. Birthday discounts? Special offers? Count us in.
4) Optimize the in-store shopping experience
Many retailers are starting to analyze data from mobile apps, in-store purchases, and geolocations to optimize merchandising in their brick-and-mortar shops. This is a great strategy to encourage customers to complete purchases, manage product stocks, and reduce the need for price markdowns. Leveraging your data to determine the age demographic of in-store shoppers, your best-selling products, your store’s busiest time of day, and the frequency of in-store returns are also excellent ways to tailor the in-store shopping experience to meet customer needs.
One thing retailers should keep in mind is that many consumers today like to take a blended approach to shopping. Since the rise of eCommerce, online shopping has become increasingly popular—as of 2021, roughly 27.6 percent of the global population are online shoppers. If you have an eCommerce platform, the smart move would be to integrate your in-store strategy with your online system to create one continuous brand experience.
Consistency of service and experience across channels helps improve customer satisfaction, especially for the savvy customer. These customers may compare online and in-store prices, collect coupons or examine a product in-store before deciding to purchase it online later.
It would be remiss for retailers to focus solely on one channel. Retailers that use an omnichannel strategy earn 91 percent greater year-over-year customer retention rates than those that don’t.
5) Improve product pricing
Retailers need to know the true profitability of their customers, how markets can be segmented, and the potential of any future opportunities.
Big data removes the need to rely solely on market prices and enables retailers to adopt the best pricing strategy based on customer information such as social media preferences, product reviews, browsing behaviors, transactions, geographical location, and more. The insights generated from this information can identify pricing improvement opportunities, reduce the frequency of price markdowns, and identify areas where profits may leak.
Conclusion
Big data unlocks massive potential for businesses to deliver better value as brands and equips them to adapt to the changing market faster. In a rapidly digitizing world, retailers that don‘t leverage big data to guide their business decisions will inevitably lose to their competitors who do.
So what does this mean for you? If you don’t already have a data strategy, it’s worth investigating how Data Science can boost your e-commerce operations. If you have one in the works but haven’t touched it in a long time, Particle41 can help you. Book a call with us today to discuss your goals, and we’ll offer no-pressure professional insight into what you need for your business to succeed.