7 Types of POS Analytics Every Business Needs

Point-of-sale (POS) data is essential for every type of business, from manufacturers to retailers, to adequately track transactions, marketing campaigns, and customer experiences. Without access to these insights, organizations may not understand how to improve their strategies.

POS analytics evaluates past and real-time data to generate detailed reports on various operations, from inventory turnover to customer retention. This information enables management to optimize systems to promote efficiency and profitability.

What is Point-of-Sale Data?

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POS data is sales, customer, inventory, and employee information collected and analyzed by a POS system. Most businesses, including online and traditional retailers and restaurants, utilize POS software to streamline transactions and gather insights.

Advanced POS solutions analyze data from each customer interaction and transaction to detect trends and find anomalies. This enables businesses to see what items consumers are buying on each sales channel, the average order value (AOV), and generated revenue.

By understanding the consumers' preferences, needs, and shopping habits, retailers can improve their marketing strategies and customer outreach.

These solutions also store inventory data, including product variances, stock levels, location, profit margins, and descriptions. With real-time access to inventory details, employees can quickly answer customers' questions and enhance their experience.

POS analytics enables businesses to improve their inventory, business, employee, and customer management across all platforms. With access to past and real-time analytics, companies can prepare their internal processes to promote operational efficiency and profitability.

By integrating POS analytics software with a forecasting solution, companies can also anticipate market fluctuations such as demand, sales, and staffing needs.

7 Types of Point-of-Sale Analytics

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POS systems are highly functional machines, allowing businesses to extract several datasets from various operations. The seven primary types of POS analytics include-

1. Inventory Valuation

Many businesses struggle with maintaining positive cash flow throughout each department. Even if a company is consistently yielding a profit, it may not have enough cash on hand to execute daily operations if too much capital is invested in products sitting in storage.

An inventory valuation report shows how much capital is invested in unsold stock in each department. This enables businesses to optimize their stock levels and reorder points to decrease slow-moving stock. By freeing up storage space, management can order more fast-moving products to improve turnover rates.

2. Employee Ranking

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A significant determinant of a business's success is their ability to manage their employees properly. Small and medium-sized companies simply cannot afford logistical errors when it comes to staffing. While overstaffing can significantly increase labor costs, understaffing can result in lost sales and frustrated customers.

With an employee ranking system, organizations can determine their top-performers and workers that aren't meeting performance targets. With POS analytics, managers can see the sales, revenue, and conversions generated by each employee.

This enables management to see which employees contribute the most profits and which are costing the company excess labor wages. Employee ranking also gives supervisors the chance to offer underperforming members extra training sessions to improve productivity.

3. Customer Report

Many businesses do not recognize that it is more time-consuming and expensive to acquire new customers than to maintain loyal shoppers. While it is important to expand the business, management should also prioritize the satisfaction of existing customers.

With a customer report, retailers can pinpoint which shoppers spend the most money, as well as their visits and purchase histories. With these POS analytics, businesses can send valuable consumers exclusive discounts and promotions to show their appreciation.

4. Cost of Goods Sold

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The cost of goods sold (COGS) is the amount of revenue a business pulls in from the amount of inventory sold within a specific timeframe. POS analytics shows the initial cost of goods as well as the profit each item generated.

However, a company may have limited cash flow even if a COGS report shows positive revenue. Therefore, businesses should cross-examine other sets of POS data with their COGS to determine their overall financial health.

5. Dead Stock

Products that are not selling and just taking up storage space limit the bottom line. Not only do companies eat the expense of purchasing deadstock, but they also have to supply the funds to house the inventory.

With a POS system, retailers can pinpoint dead stock to halt all reorders and determine new pricing strategies to promote turnover. Depending on the type of product, businesses can offer discounts to encourage purchases or may need to discard the inventory.

POS analytics helps companies determine why products converted to dead stock so they can avoid future occurrences.

6. Top Selling Items

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POS analytics identifies top-selling inventory by tracking every transaction, customer interaction, and online query. They also calculate how much income each product line yields, as a top-selling item doesn't always generate as much revenue as high-profit inventory.

Knowing the top-selling products enables businesses to optimize their inventory ordering strategies to maintain healthy stock levels and promote sales. Depending on each item's turnover rate, companies may need to update their reorder points to prevent stockouts and backorders.

7. Purchase Orders

Defining reorder points is challenging, as every company experiences fluctuating demand on different schedules depending on slow and busy seasons.

POS analytics considers past sales and demand trends to suggest reorders based on upcoming events, such as holidays and seasonal changes. Advanced POS systems will even alert users when inventory dips below healthy stock levels.

By integrating existing software with ordering solutions, companies can automate reorders to prevent stockouts.