All in all, in spite of the rhetoric of the “retail apocalypse,” we can look back on how 2017 ended on a high note with a massive surge in holiday sales. By keeping the focus on innovation at the forefront, digitization single-handedly led the retail industry through a significant transformation in 2017. The core element, retail analytics, powered by big data played a fundamental role in this digital transformation and revolutionized the way retailers are now operating.

Looking back in the past year, retail technology trends have proven retailers have been able to utilize data analytics to overcome the e-commerce challenge. Through data insights and grasping the consumer behavior patterns from multiple channels, retailers have been able to effectively execute marketing campaigns and personalize the customer’s shopping experience to meet their heightened demands.

Moving forward, retailers are applying data analytics into every touchpoint of their business — from predicting sales, optimizing products on shelves, to enhancing loyalty platforms. Coming into 2018, retailers must aim to improvise these strategies to further overcome any obstacles and continuously adapt to the evolving market. To do as such, retailers that are planning to leverage data analytics should consider the following market trends to enable them to progress further into the coming years.

Retail Will Evolve From Predictive to Prescriptive Analytics

From forecasting demands and footfalls to personalizing customer experience through predictive analytics has been the median in retail. Although, the main challenge lies in pricing for retailers who are in competition with the likes of competitors such as Amazon. Armed with prescriptive analytics, retailers can now even tackle this challenge by analyzing different types of data such as location intelligence, customer trends, product availability and peak hours. Allowing retailers to optimize profit margins to capitalize any number of available opportunities.

Data Analytics Will Optimize Store Operations

Optimization of store operations is one of the reoccurring challenges that is faced today to run a profitable retail business. Allocating the correct number of staffing to address the various shopping trends based on a particular day of the week, an event, a holiday can become challenging. This is where another feature of in-store analytics plays a crucial role. Analytics enable retailers to counterproductively manage store operations by optimizing the staff based on various scenarios and historical data.

Data From Omnichannels Will Get Combined

Through multiple channels and various sources, retailers are collecting heightened volumes of consumers, sales and loyalty data. As the number of channels are increasing significantly — maintaining, managing and analyzing the data has become a challenge all of its own. We are seeing retailers trying to solve this by hiring a data scientist to analyze and manage this data. But with an increased focus being on automation this year, we will begin to see retailers deploy cutting-edge retail analytics software’s to bring all that information together to get a holistic view of their brand’s overall performance.

Product Assortment Analytics Is Enabling Sales Growth

When we look at the impact of in-store conversions and sales — product assortment plays the primary role. We can all agree to say that retailers who fail to plan their product placement have faced devastating results on their sales in the past. Reviewing shopping patterns to understand correlated products that are purchased together have enabled retailers to optimize their product assortment to maximize sales. Through in-store analytics, retailers can integrate in-store customer behavioral data linked to purchase history from POS to uncover shopping patterns. Looking to the future trends, it is foreseeable that data analytics will enable retailers to become more aware and proactive with product assortment.

Loyalty Programs Will Be Revived Through Data Analytics

None-the-less, we can see that e-commerce profits are gaining momentum, market research shows that 96 percent of retail sales are still happening in bricks-and-mortar. This goes to prove that a high volume of consumers still prefers retail stores over e-commerce. Have you seen the hidden message? No — well, let me explain. The main driver for customer loyalty is not price discounts — its customer experience.

Consumers who are loyal to their brands are seeking privileged treatment and retailers are able to deliver as such through in-store analytics platforms. Brands are beginning to turn their focus on personalizing experiences through collecting in-store customer behavior data to drive customer loyalty. This goes to prove that data analytics will the engine to drive most of the loyalty marketing campaigns in 2018.

Retailers and Suppliers Connected Through Data Sharing

Although data sharing was not able to get traction in the past due to lack of adequate technology — making the communication between retailer and supplier difficult. In 2018, we are seeing that with access to various cloud tools and big data technologies, data sharing is becoming streamlined. With the ability to forecast demands and shopping patterns, retailers and suppliers will be able to improve efficiency and reduce costs for managing, purchasing and deliveries.

Retailers Implement Vibrant Pricing Through Data Analytics

Amazon’s leading advantage over physical stores has been the brilliant Dynamic Pricing structure. Now, through prescriptive analytics and comprehending the customers’ personas and purchasing patterns, bricks-and-mortar can now implement the same. We can expect this trend to hit the ground running mid to late quarter of 2018 with the availability of lower-priced electronic shelf labels and NFC tags enabling stores to immediately update product pricing based on shopping trends and behavioral data.

So, let’s face it — retail is no longer art, but rather a science. Which only means one thing for businesses owners, either you get serious about Big Data Analytics or you and your brand get left behind. There’s a good reason why the retail industry in putting data first. There are several profound benefits to using data in a retail environment. With heightened expectations from the consumers and competition growth in the market, prioritizing customer experience is more imperative than ever before. This means only one thing — retailers must create and deliver a smarter, more unique shopping experience to retain and attract new customers.

Because data analytics ensures that in-demand items will be in stock, prices are adjusted in real time and deliver relevant and timely promotions — consumers will benefit from a smarter, more pleasant shopping experience. Retail data analytics is not just a competitive edge anymore, rather a necessary tool to compete with other retailers.