Driving Success: A Guide to POS Analytics for Retail and Restaurant Growth

The Point of Sale (POS) system does more than handle transactions; it acts as a valuable source of insights. Point of Sale Analytics, or POS Analytics, collects, analyzes, and understands the data generated during customer transactions at the point of sale. It involves dissecting information to understand better how a business performs and what customers prefer.

Point of Sale Analytics: Significance in Retail and Restaurant Businesses

The right KPIs for POS Analytics provide real-time visibility into sales patterns, customer preferences, and operational efficiency. By harnessing the power of POS Analytics, businesses can make informed decisions, optimize inventory management, enhance customer experiences, and ultimately drive sustained growth.

Read this blog to know more about the right KPIs to track to tap into the potential for positive transformations.

Sales KPIs for POS Analytics in Retail

Retailers and consumer goods manufacturers have the enormous responsibility— and opportunity—to reinvent themselves and reimagine their next normal. As per the findings in the McKinsey report, numerous companies face a shortage of consumer and retailer point-of-sale data. The available assets, including internal financial, product, and customer master data, are often stored in isolated legacy systems, posing challenges in terms of accessibility and harmonization. Consumer goods companies do not have well-established data governance processes for utilizing, securing, and sharing data across the organization in accordance with privacy regulations.

Some consumer goods companies, recognizing these inadequacies, mistakenly believe that they must change their entire data infrastructure simultaneously. Giving priority to the enablers that offer the highest value is more effective and ensures the consistency of enablers across various domains.

Let’s take a look at three fundamental sales metrics:

Total Sales:

Definition: The cumulative revenue generated from all sales transactions within a specific timeframe.
Example: If your clothing store earned $50,000 monthly, that constitutes the total sales figure for that period.

Average Transaction Value:

Definition: The average amount a customer spends during a single shopping transaction.
Example: If 100 transactions occurred in a day, and the total revenue for that day was $5,000, the average transaction value is $50.

Items per Transaction:

Definition: The average number of items a customer purchases in a single shopping transaction.
Example: If 50 customers made purchases, and 200 items were sold, the items per transaction would be 4.

Sales Reports and Analysis

The right KPIs can help you generate the following reports.

Aging – Managing Shelf Life:

Example: Imagine you manage a grocery store. By analyzing sales data, you notice that certain perishable goods have been on the shelf for an extended period. This prompts you to adjust stocking strategies to minimize waste and ensure the freshness of products.

Careful Stocking Strategies:

Example: A retail electronics store examines its sales reports and recognizes that specific brands or models are consistently popular. This insight guides them to strategically stock more of those items to meet customer demand effectively.

No Stock Reports for Inventory Optimization:

Example: A home goods store monitors instances of items being “out of stock.” This analysis helps them optimize inventory levels, ensuring popular items are consistently available.

Mode of Payment Analysis:

Example: A fashion boutique notices an increase in credit card payments. This insight encourages them to ensure their point-of-sale system supports various payment methods, enhancing customer convenience.

Door Delivery, Pick Up, and Walk-In Orders:

Example: A department store discovers through POS analytics that a significant portion of their orders come through Dunzo for doorstep delivery. This prompts them to optimize delivery partnerships and streamline in-store processes for walk-in customers.

These examples showcase how a nuanced understanding of retail sales metrics and strategic analysis can empower businesses to refine their operations and drive growth.

Sales KPIs for POS Analytics in Restaurants

Boosting the operational efficiency of stores includes various initiatives, including minimizing food wastage, optimizing staff schedules, and increasing the speed and precision of customer order fulfillment. For restaurants, it’s crucial to streamline processes related to digital delivery orders, in-car pickups, and drive-through operations—channels that experienced a surge during the pandemic and are now integral to the industry. These efficiency enhancements cut costs and align with evolving customer preferences.

Let’s take a look at three fundamental sales metrics:

Total Revenue:

Definition: The overall income generated from all sales transactions within a specified period.
Importance: Indicates the overall financial health and performance of the restaurant.
Example: If a restaurant earned $30,000 in a month, that represents the total revenue for that period

Average Order Value:

Definition: The average amount spent by a customer per order.
Importance: Reflects the average customer spending, aiding in menu optimization and upselling strategies.
Example: If a restaurant serves 500 customers weekly, and the total weekly revenue is $15,000, the average order value is $30.

Table Turnover Rate:

Definition: The number of times a restaurant’s tables are occupied and vacated during a specific period.
Importance: Measures the efficiency of service and how quickly tables are utilized, impacting overall revenue.
Example: If a restaurant has 20 tables and serves 100 customers daily, the table turnover rate is 5 (100 customers ÷ 20 tables).

Sales Reports and Analysis

The right KPIs can help you generate the following reports.

Average Per Cover:

Definition: The average revenue earned per customer served.
Example: If a restaurant serves 200 covers daily and generates $4,000 in revenue, the average per cover is $20 ($4,000 ÷ 200).

Number of Covers:

Definition: The total count of customers served within a specified period.
Example: If a restaurant serves 1,000 covers per week, the number of covers for that week is 1,000.

Menu Item Sales Analysis:

Purpose: Identify popular and less-ordered menu items.
Example: Discovering that a specific pasta dish consistently sells out can prompt the chef to feature it more prominently or create variations.

Dining Time Analysis:

Purpose: Evaluate the duration customers spend at tables.
Example: Recognizing that lunch service sees quicker table turnovers than dinner may lead to adjusted staffing schedules for optimal efficiency.

Sales by Daypart Analysis:

Purpose: Understand sales patterns during different times of the day.
Example: Observing a surge in breakfast orders during weekdays may inspire introducing a breakfast promotion to capitalize on demand.

Customer Order Channel Analysis:

Purpose: Differentiate orders from dine-in, online delivery, etc.
Example: Identifying a significant increase in online delivery orders can prompt the restaurant to optimize online platforms or consider exclusive promotions.

Customer Satisfaction and Feedback Analysis:

Purpose: Evaluate customer reviews and satisfaction scores.
Example: Noticing recurring feedback about slow service might lead to staff training initiatives or procedural changes to enhance overall customer satisfaction.

CI Global: Your Partner for POS Analytics

At CI Global, we provide cutting-edge solutions tailored to your unique needs. Our Point of Sale Analytics expertise empowers you to unlock valuable insights, optimize operations and inventory management, and elevate customer experience. Partner with CI Global for a transformative journey towards data-driven excellence in the competitive world of commerce.