Constilation

Using Retail Analytics to Benefit Business Operations

Author
Ross Malpass
September 1, 2021

To thrive in today’s competitive retail market, companies have been forced to implement new methods for maximizing growth. Businesses have turned to retail analytics to help improve efficiency and returns. 

What is Retail Analytics?

Retail analytics is “the process of providing analytical data on inventory levels, supply chain movement, consumer demand, and sales … Retail Analytics provides in-depth customer and business insights into the scope of and need for improvement.” The collection of data allows companies to identify patterns and trends to improve operations. 

However, as SPScommerce points out, “it’s not just about the raw data. An effective retail analytics software cleans inconsistent data sets and presents them in a single intuitive retail dashboard. Businesses get a bird’s-eye view of performance, informed sales, marketing decisions, and increased profit.”

Types of Retail Analytics Software

Depending on a business’s operations, the best software to use varies. Companies must identify the optimal solution to help them meet their business goals and objectives. Here are some of the most common types of retail analytics software used today.

Point-of-Sale Systems

Point-of-sale (POS) systems are used to streamline retailer operations via an automated transaction process. They are used to ring up customers, accept payments, execute refunds, etc. Historically, these systems have been relied upon to expedite the customer’s experience. However, today’s POS systems offer in-depth analytics to help retailers improve their business models. Effective systems offer the following features:

  • Inventory management
  • POS reports
  • Customer loyalty programs
  • Employee management
  • Customer relationship management (CRM)
  • Tipping support

POS systems offer an in-depth review of how a company is operating. Details can provide insight into important metrics, including profit margins, sales trends, peak checkout times, etc. As a result, businesses can understand which products or suppliers are driving revenue and which times are critical for increasing staff to meet consumer demand. The data can be leveraged to enhance the customer experience, thereby increasing revenue. 

In “How to Use Big Data to Improve Your Retail Store Sales,” Riva Lesonsky states, “You can use information from your POS system and sales receipts to staff your store appropriately or make adjustments to your store hours. For example, if you find that customers rarely come in after 6:30 p.m., consider closing earlier or reducing the number of sales associates on the floor at that time. You can also use this data to plan for seasonal fluctuations in sales, helping you manage cash flow better.”

People Counters

People counters, such as the Ombori People Counter, use cameras to count individuals entering and leaving a building without any human intervention. This software can track customers as they move through multiple entries or exit ways and automatically provide data to help businesses understand occupancy patterns within a specific location.  Common types of people-counting systems used across industries today include:

  • CCTV & Stereo Vision: Optical People Counters: Uses video to record individuals entering and exiting the store; the vision technology leverages facial recognition and object deduction to count people. 
  • Thermal People Counters: Tracks the movement of the human body by measuring how the body heat of entering customers raises the temperature of the environment and entryways.
  • Mono People Counter: Consists of a single lens system that tracks traffic.
  • WiFi People Counters - Signal Tracking: Uses a customer’s connection to WiFi to track their location and identifies how many users are within the store.
  • IR (Infrared) People Counters: IR counters work by placing a barrier between two spaces; when a customer walks between the IR counters and interrupts the signal, they are counted. 

During the COVID-19 pandemic, people counting has become critical to helping businesses align with ordinances that restrict occupancy. For example, during the peak of the pandemic, grocery stores in California were limited to 50% capacity. 

Traditional methods for counting people who go in and out of a store include using an employee to physically track those customers. However, people counting technology has introduced a new avenue for ensuring public safety. These systems offer additional analytics that human employees do not. 

People counters offer real-time data to retailers, and by gathering and analyzing customer traffic data, companies can create value in terms of revenue and business efficiency and generate crucial insights that drive sales, improve conversion rates, and help to make informed marketing and spending decisions.

For example, foot traffic data can help management identify staffing needs at a particular time. During peak hours, businesses can increase the number of staff available to control crowds.

Unlike POS systems, people counters track those who go in and out, even customers who do not purchase an item. And by linking the two systems, businesses can benefit from an in-depth understanding of conversion rates.

Queue Management Software

Multiple industries, including retail businesses, use queue management software to help control customer flow, manage wait times, and enhance the overall shopping experience. An effective queue management system, such as Ombori Queue Management, examines the following elements:

  • Customer population
  • Method of arrival (e.g., in groups or individually), timing, and customer distribution
  • Service mechanisms (including whether separate queues exist for each service)
  • Customer behavior while in the queue
  • Interaction with customers (this is a key component for creating an effective queue management system)

Examining data derived from queue management solutions allows businesses to better understand customer demand and implement a system that works well for all given situations. 

Most recently, retailers have started relying on virtual queues, a function of queue management solutions, to improve the customer experience. Virtual queues offer customers the ability to check-in online and wait for their turn outside of a traditional standing queue. Instead, they are offered the ability to browse the store until they are notified of their turn. This function collects data from customers related to waiting times and provides insight into reducing wait time. 

Benefits of Using Retail Analytics 

There is no limit to how data can help a company improve its operations, and each software application offers unique insights into retail analytics. This information can provide businesses with the following benefits:

  • Fewer customer complaints: Any way a business can improve the retail experience can have a positive effect on customer feedback. Improving operations to reduce wait times and improve processes will likely contribute to an influx of visitors to a specific location. 
  • Improved staffing needs: High traffic hours require more staffing, both at checkout and within the store. Companies can assess how many customers are shopping and leaving and then ensure they have the correct customer-employee ratio at all times. 
  • Expanded business success: By understanding the number of visitors to a store and comparing this data to checkout statistics, businesses can gain insight into conversion rates. When these rates are lower than expected, businesses can make adjustments to increase the numbers. For example, they may notice lower conversion rates when specific items are low in stock, and then they can increase inventory to help manage losses. 
  • Eliminated wait times: Twenty-five percent of customers report that they will walk out of a store if a line appears to be too long. For businesses, these walk-outs result in economic losses and can be avoided if appropriate checkout options are available, thereby reducing or even eliminating queues altogether. Understanding demand depends on the data collected from a queue management software. 
  • Improved store layout: Understanding foot traffic can help businesses reconfigure their stores to maximize occupancy while offering the feeling of spaciousness to customers. Businesses can see which products and services are most commonly visited and separate them accordingly. 
  • Measured and improved marketing efforts: Retail analytics can help companies measure the effectiveness of marketing campaigns. For example, they can determine if foot traffic and sales increase after launching a new campaign; they can then modify the campaign accordingly, taking customer feedback into consideration. 
  • Analysis of product demand: POS systems are commonly used to analyze product demand. They help businesses understand the value and number of products sold in an average order; recognize which products sell the most often, the least often, and everything in-between; discover demand and past lost sales; determine optimal suggested order quantities and recommend purchases and allocations; and establish the optimal price point for a specific product at any specific location.
  • Understand customer demands: Most importantly, retail analytics helps businesses understand their customers. After all, customer experience matters and retailers can appreciate consumer wants and needs by following the data. Then they can make the buyer’s journey as seamless as possible and improve customer loyalty.

With the rise of online shopping, many retailers are facing fierce competition and changing consumer behavior. People can now buy a vast number of products from different stores with the simple click of a button. So, it is more important than ever for businesses to leverage retail analytics to maintain a competitive edge.

 

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