5 Retail Analytics Trends Shaping the Industry in 2022

Analyzing data has become increasingly important to economic models across all industries. This approach has probably had the most significant impact on the retail industry.

Success of pure-play retailers such as Amazon or Alibaba provides evidence of this particularity. In their research, these companies were able to collect a large amount of information from their users: customer types, research history, and average purchase budget.

To ensure successful marketing of their products, pure player retailers learned early on that they needed to understand their users. Hyper-personalization strategies allow them to attract consumers through personalized referral systems or early shipping models.

In order to implement data-driven strategies, here are the top 5 retail analytics trends to follow:

1. Retail analytics increase consumer awareness

Retailers must anticipate and respond to the needs of their customers since they are a customer-focused industry.

With each purchase, a customer gives the store a wealth of information (buying habits, brand preferences, and loyalty points). Utilizing data analysis tools can assist retailers in learning more about customers from these multiple data sources.

In addition to improving operational efficiency, this trend allows traditional retailers to increase customer satisfaction. As an example, Starbucks collects customer preferences to send customers personalized advertisements and offers on specialty beverages.

It is easy to evaluate this type of operation using data narration software. With this information, you can intuitively determine which customer types respond positively to personalized promotions that your marketing team sends.

2. Using retail analytics to increase customer satisfaction

By implementing in-store data tracking technologies, consumer satisfaction increases. Additionally, these tools are proven to significantly increase employee efficiency.

An online retailer, for example, can access stock data to instantly inform a customer if a certain item is available (at the store itself or in another nearby store, for example).

Additionally, customer satisfaction increases by better analyzing the data from the loyalty program. Using this information, your marketing team can offer better discounts or gifts on products that he or she prefers if they go in-store… This will provide the customer with a more personalized experience at your store.

3. Provide buyers’ needs-driven product trend analysis

Traditional retailers can easily identify the most popular and profitable product categories within their stores using a data storytelling solution, and then devise marketing or merchandising strategies to highlight them.

On your dashboard, for example, if you are selling a t-shirt in three colors, you can see which model has had the most success in terms of sales volume. Your teams can update stocks and value products through merchandising.

As of 2018, H&M started using important data from their stores to customize their merchandise assortment. Additionally, according to the company, it will use algorithms to analyze data from store receipts, returns, and loyalty card data to reduce markdowns.

4. Consider omnichannel behavior

More than 80% of consumers who make purchases online conduct online research before they make their purchase, according to retail research. In other words, the journey really begins before the customer sets foot inside the store!

Therefore, retailers must focus their efforts on the Internet as a strategic entry point to convince their customers to visit them in person. How? When you are able to strategically use the data collected from their online purchases, you can ensure they are shown the goods they want and given relevant advice when they are in store.

By utilizing data storytelling solutions, retailers can access homogenized data collated from retail stores, social media channels, and email marketing campaigns. Using that data, you can create special offers, personalized messages, and packages.

In one example, Walmart uses social monitoring to track a product’s reaction and send out targeted messages to consumers, encouraging them to visit the store to collect a discount voucher, a gift, or to participate in an event.

5. Enhance the customer experience in the store

Several studies suggest that Brick and Mortar retailers who utilize digital technologies are outperforming their competition. In fact, gathering and analyzing carefully selected data will give retailers a competitive edge.

Retailers can use data from physical stores, combined with online shopping behaviors, to offer new services in stores. As an example, Uniqlo has developed a click & collect service in several cities (London, Singapore, etc.).

Similarly, many athletic companies, such as Nike or Adidas, are known for regularly launching limited edition collections in a particular store as a way to encourage customers to visit. There is a database of customers invited to the store (regular customers, raffles via social media, etc.): being invited and going to the store are privileged experiences.

Our demonstration has shown that retailers are using data strategies to rethink the physical environment of their stores in order to provide their customers with more personalized experiences. The resulting homogenized and cross-referenced data is used to enable efficient operations.

Furthermore, employee productivity and comfort are increased. By seeing the right figures, store managers are more confident about monitoring their sales objectives. Assistant sales staff can effectively answer customer questions.

You will keep customers coming back to your stores if you ensure customer satisfaction and improve the purchasing experience. That is something pure players cannot deliver.

Wrap-Up

A lot hasn’t changed in the way retailers aspirations over time. A retailer’s top goals include better customer service, better performance against competitors, and more effective supplier relationships. Although new sophisticated strategies to solve the daily challenges and strategic problems are appearing in the retail industry all the time, it doesn’t guarantee that all retailers will reach their goals. Using data analytics to support initiatives can make a difference.