Unlocking Retail Success with Powerful Analytics
Every business needs analytics to measure growth. The same applies to retail stores, where analytics contribute to improving sales, inventory, marketing, and other aspects of the business. Retail analytics have existed before the digital age through means like customer surveys and receipt reviews.
However, digitization has revolutionized retail analytics with the provision of better insights. Retailers need this revolution to meet the increasing customer demands, who ask for more convenience and consistency than before. In modern times, retail analytics have become indispensable in decision-making.
Read on to understand more about retail analytics and how it contributes to your business’ success. Our guide on retail digital signage is also important.
What Is Retail Analytics?
Here is a working definition of retail analytics: Retail analytics involves acquiring and examining data related to different aspects of the retail business. Analytics help retailers understand current trends, observe customer behavior, check inventory levels, and cross-check the number of sales. Overall, it informs decision-making and drives progress.
Retail analytics have benefited from the rise of digital technology, which opens new opportunities for gaining data, surpassing traditional tools. The data surplus allows for better strategies and positive changes in approach.
Retail analytics, partnering with digital tools, gives the company a competitive edge over others, especially with the Key Performance Indicators (KPI). KPI measures the performance of retail stores, making it a core aspect of retail analytics. Digital signage content automation also provides that competitive edge, as well as the right content for signage.
Furthermore, retail analytics can identify lagging areas in the retail store. Are customers dissatisfied? Did sales drop since the previous year? Retail analytics can pick up these setbacks, opening the road for solutions.
Why Is Retail Analytics Important?
Although we defined retail analytics in terms of data collection, its value extends beyond gathering and examining data. The ever-changing customer expectations make analytics a necessary tool to detect customers’ needs and behaviors, especially with digitized data.
Customers’ information, combined with personalized strategies, entails better customer satisfaction. Modern analytics employs many technologies, such as facial recognition and video analytics, which result in accuracy.
In addition, retail analytics influence other aspects of the retail business. The obvious influence is sales, as happier customers buy more. Retail analytics also increases the store’s efficiency, which the staff benefits from.
To understand more about the importance of retail analytics, read our guide on digital signage analytics. Also, explore our guide on digital signage tools for window devices to engage your customers with more than analytics.
How Does Retail Analytics Work?
As the name suggests, retail analytics involves many analyses, including past data and the target audience. It also relies on human suggestions as much as technology. Let’s explore further:
1. Analyzing the audience
A retail business would collapse without customers. Ergo, audience analysis is crucial. Using modern technology and the expertise of Artificial Intelligence, retail analytics examine different audience factors that influence purchases. Examples are age, gender, income level, career, and emotions at certain hours of the day. Retailers use the data from this analysis to understand their audience. Together with digital signage, your store can exceed expectations.
2. Analyzing the past
A store’s history offers incredible resources that can influence future strategies. Through analyzing the past, retailers gauge the store’s performance, noting successes and areas of improvement. The past data also unveils strategies worth repeating, how customers spent, and products that sold more. Want to improve your marketing? Check out our Creating a TV Menu Board.
3. Analyzing Customer Feedback
Retail analytics needs direct customer feedback alongside technology. People’s suggestions are also important. After all, retail analytics seeks to enhance their experience. Actual feedback offers more personal data than digital analysis. Furthermore, feedback nurtures the relationship between retailers and their customers. Learn ways to manage customer interactions, and get tips on Digital Signage Content Managers.
Examples of Retail Analytics
Retail analytics has grown over the years, offering more practical techniques than sales analysis and trends. Newer examples have sprung forth, some of which are listed below:
Gaze analysis
Yes, you read right. This technique involves monitoring how long a customer gazes at a product or an advertisement. Your best tools for this analysis are static cameras, which capture the eye movement and how long the individual stares at what is presented. If four customers gazed more at product A over product B, why is it so? Does a particular advertising content hold the gaze of a particular audience demographic? Gaze analysis raises and responds to these questions.
Demographic Analysis
A more common form of analysis, demographic analysis involves examining the characteristics of a particular population, such as age, income, gender, and education. Demographics helps to better understand customers, their needs, and how they can be segmented.
People Counting
People counting is also quite common, perhaps as much as demographic analysis. It involves keeping track of the number of people who enter and leave the store. The purpose of this analytic example is to determine the number of visitors and those who make a purchase.
Hot Zone and Dwell Time
The hot zone and dwell time track people’s movement within the store. Areas wiith the highest amount of attention is called the store heatmap, and the time spent is the dwell time. This analysis determines where products will be placed to gain the most attention.
Customer Behavior Analysis
Finally, the customer behavior analysis reveals how customers interact with products and advertisements. Retail analytics is incomplete without customer behavior analysis, which is instrumental in enhancing the customer’s overall experience.
Retail Analytics Best Practices
Alongside the knowledge of how retail analytics work and the examples, retailers should employ the best practices for more insight:
- Run pilot tests: Running a pilot test is similar to test driving a new car. It enables retailers to try out marketing strategies on a smaller scale before implementing them.
- Observe customer behavior: Note how customers make decisions, what they prefer, and what attracts them more. Analyzing customer behavior helps in making decisions that focus on the customer's needs.
- Adapt in-store displays: Alongside the first two practices, ensure your product displays align with all you know about customer behavior. Recommend products you know customers would likely buy, and tailor your advertisement to their interests.
Conclusion
Retail analytics contribute to progress and customer satisfaction, making it a core tool for every store. Ensure you implement all the insights gained from the analytics, and take advantage of the evolving technology for better measurements. When done effectively, retail analytics will transform your business.