Ins and Outs of Point of Sale Analytics and Data Analysis
There’s an innocuous machine (a chain of several, maybe) that is quietly collecting data about
your customers; data that customers are willingly giving up. Over time this data becomes a
treasure trove of information, and if analyzed, can speak volumes about your business, its
customers, the inventory, its staff, and much more. That machine is your point of sale (POS)
When customers dine out, or purchase services, online or offline, they pay in either cash, credit or debit cards at such a POS system. There are two types of POS: software and hardware- based systems that are integrated with cash registers, and web-based services that are integrated into e-commerce sites for online buying. Every time they do that, customers leave behind information about themselves, their payment mode, the commodity or service purchased, the frequency, the time, the month….it’s a long list.
Table Of Contents
- What Is Point Of Sale Analytics?
- What Is POS Data Specifically?
- How Can POS Analytics Help Your Business?
- What is POS Data Analysis Used For?
- Benefits Of POS Analytics
- Advantages And Disadvantages of This Form Of Analytics
Many merchants continue to look at the POS as merely a machine used to charge a customer at the time of checkout, and are not aware even today that this data is pure gold; and that it can be analyzed to get the granular picture of the business they are in.
What Is POS Analytics?
Analytics is critical for business in any industry. It’s the scientific way of helping business
owners understand what’s working and what isn’t, so they can make better informed decisions to grow their business.
Point of sale analytics is the process of using data from sales transactions to improve your
business. This data can be used to track trends, understand customer behavior, and make more informed decisions about marketing, product development, and operations.
The advantage here is that POS data is real-time information: it gives you information on how
customers shop and process transactions with your business.
Analyze Customer Data With Point Of Sale Analytics
The astute merchants amongst us have already started using their POS data to make dramatic, positive changes in their business strategies in order to increase sales and create loyal customers.
What Is POS Data Specifically?
Sales data is information that is collected from a point of sale system. This data can include
information on what was sold, when it was sold, and how much was sold. POS system data
includes information on product sales, customer purchases and staff interactions with the
Point of sale systems have data about customers and their purchases. This data can include the customer’s name, contact information, and purchase history. POS systems can also track inventory levels and sales data. This type of data is collected from a POS system’s scanners, or bar code readers. This technology lets a POS system know what inventory to keep on hand and what products to stock in order to meet the sales goals. POS systems are capable of tracking this information based on the customer’s purchase.
By understanding the different types of POS data, businesses can learn how to better grow their operations.
How Can POS Analytics Help My Business?
Analytics of the data collected at the point of sale helps a business by showing the path to the most profitable strategies, including fast-selling products. For example, point of sale analysis (POS data analysis) can show that a product’s sale volume has increased but its profitability has decreased. If a product is underperforming, POS data can show which stores are responsible for it.
POS analytics can also show a sales trend. If store profitability has been decreasing and the
number of hours that are spent per customer is increasing, then it’s likely that there is some
factor that is causing the decrease in profitability.
A business can use POS analytics to make smart decisions regarding its operations. For example, by knowing which products have decreased profitability and which have increased it can make adjustments to its operations.
Analytics of POS data can give insights into:
- Sales Volume
- Product Profitability
- Product Ranking
- Store Sales Trend
- Best Day of the Week
- Coupon and Promotion Frequency
- Product Selling Seasonality (e.g., peak/low sales)
In fact, POS companies like Lightspeed POS have started to sell fully integrated retail POS
systems for restaurants, ecommerce and so on, positioning it as “the technology for the future” So you don’t buy just a sales machine but an entire omnichannel ecosystem complete with analytics for the next era of commerce.
Others such as Toast POS offer systems and analytics specifically for the hospitality
business. Its “restaurant-first” suite of tools and services include not only the POS but also
integration for online ordering, self-ordering kiosks and take-outs.
What Is Point of Sale (POS) Data Analysis For?
A POS (point of sale) data analysis is a type of analysis that looks at the point of sale data for a business. This data can include things like the number of sales, the average sale amount, and the types of products that are being sold. If you can use this data to help make business decisions, it can really improve the health of your business. For example, you might use the POS data to figure out which types of products are most profitable for your business and which ones are not. Using the POS data can also help you figure out the best pricing strategies for your business. That way, you can maximize revenue and minimize loss.
Like we said earlier in this post, the majority of retailers capture and store a large amount of
business-relevant data, but they don’t know what to do with it. Retailers can use POS data analysis to accurately understand consumer behavior and the impact of sales at every point of sale.
Estimate Online and Physical Retail Store’s Impact Beyond Sales with POS Anayltics
6 Benefits Of POS Sales Analytics
- Sales analytics is the practice of analyzing data to help sales teams improve their performance.
- The benefits of using sales analytics include being able to identify trends, optimize resources, and improve close rates.
- Sales analytics provides insight into customer behavior, which will help sales people make better decisions.
- Sales analytics is not just used by retail sales people and consumer products companies. This tool can be used to improve any sales and marketing team.
- The goal of sales analytics is to help sales people make better decisions. This can be done by having more information about customers, sellers, and products. With more information, the sales team will have better tools to make better decisions and be able to provide personalized service.
- A sales analytics tool allows sales people to get better reports, making it easier for them to track metrics and make changes.
Here’s where it helps:
A POS analytics system makes it easy to keep track of your store’s inventory in real-time, so you can
manage your stock more effectively. With a POS system, when you receive new inventory, you can simply scan the items and enter the quantities. This saves a lot of time compared to manual tracking of your inventory, and reduces the chances of errors. Vendors like Clover POS, for example, offer inventory control as part of their POS offering.
Better customer management
With a sales analytics tool, you will have better customer management and customer support.
Knowing how much each customer spends, their spending pattern, and the products they
purchase will help you track customers more effectively.
By sending your customers promotions, you can encourage them to visit your store more often or build customer loyalty. The system allows you to track each customer and offer targeted promotions based on their behavior.
Better promotion offers
With a POS system, you can use the reports to create better promotions for your customers. At a glance, you can understand what kind of products each customer buys and the cost of each item. This will help you to know what products to include in the promotions and how much to charge for each item. You can even create promotions for “Christmas in July”, or any other holiday, to build brand loyalty and increase sales.
What Data Is Absolutely Necessary?
There are a few key point of sale analytics that are absolutely necessary for any system. The first is sales data. This data is essential for understanding what products are selling, how much they are selling for, and which customers are buying them. This information can be used to make decisions about inventory, pricing, and marketing. Another important point of sale analytics is customer data. Knowing what people are buying can help to figure out what products you should be selling or even which ones you shouldn’t be selling at all. Tracking customer data can help maximize revenue, minimize loss, and increase profitability. In addition to customer data, tracking customer spending habits is essential for understanding who is buying what and how much. Customer spending habits can be used to optimize future marketing and promotional campaigns. There are a few other common point of sale analytics that are critical for maximizing revenue.
What Are The Advantages And Disadvantages Of Such Type Of Analytics?
The advantages of POS analytics include its value in understanding specific product data and
analyzing sales trends. It is able to give you answers to questions like – “Why are we losing
customers?” or “Why aren’t we selling more products?” or “Why do some customers buy more of our products than others?” What’s more, POS analytics can provide a clear picture of the relationship between promotions, price, and product sales.
The disadvantages of POS analytics include the fact that it only allows for continuous
understanding and analysis and not actual sales control. A critical element of POS analytics is
data enrichment, which refers to the process of using additional information to create a more
accurate picture of a specific situation. Using these additional data helps to solve difficult
customer questions, manage marketing plans, and optimize business goals. Sometimes, enriching data could allow mistakes to creep in.
Also, POS requires software and hardware updates which can prove to be costly in the long run. But updates are required to ensure system does not become obsolete. Also, there is also the standard apprehension of bugs creeping in.
In conclusion: A point of sale terminal is not just a simple till machine. Thanks to technology, it is now a powerful device in the hands of a retailer. The data it captures can be analyzed to help retailers improve customer experience, anticipate demand and optimize stock.
How To Link Shoppers’ Digital Footprint To POS Activity
Express Analytics uses a combination of tactics to map the digital footprint of customers to their in-store, in-person activity. The solution schematic is presented in the image below.