Your Billing Software Is a Goldmine: Simple Data Analysis Tips for Apparel Retailers

Most small and medium retail businesses already use billing software or ERP systems. Every sale, purchase bill, stock movement, customer detail, and return is already recorded and safely stored.

And then… nothing happens.

That data just sits there like an unused fabric roll in a warehouse, quietly losing value with time.

In current days, data is gold, and you are literally sitting on a goldmine without even realizing it.

When business owners hear the words “data” or “data analysis,” they usually imagine AI, machine learning, data science, big dashboards, advanced Excel, or consultants who charge more than a seasonal inventory budget.

And to be fair, they are not completely wrong.

Advanced data analysis is complex. It requires specialized skills, tools, and resources.

But notice the keyword there: advanced.

Basic data analysis is something you are probably already doing over the years.

If you look at your sales totals for the past five years and see numbers like 2 crore, 3 crore, 2.8 crore, 4 crore, and 5 crore, that is data analysis too. You are spotting patterns, understanding growth, and recognizing ups and downs in your business.

That is the simplest form of data analysis.

And the good news is, there is much more you can do using the same data you already have, without any technical background, AI tools, or complicated software.

In this blog, you will learn simple and practical ways to analyze your billing or ERP data using basic Excel sheets, charts, and the right business questions, so you can make better decisions for your fashion retail business.

Let’s get started.

What Data You Already Have in Your Billing or ERP Software

If you run a fashion retail or apparel business and use any kind of billing or ERP system, you are already sitting on years of valuable business data.

You may not realize it, but your daily operations automatically generate information that can help you understand sales trends, customer behavior, and inventory performance.

Below are some of the most common types of data that almost every billing or ERP system stores.

Sales Invoices

Every sales bill contains more information than just the final amount.

It usually includes:

• Date and time of sale
• Customer details such as name, contact number, or location
• Items sold including SKU, size, color, quantity, and price
• Payment method like cash, card, or digital wallet
• Discounts or promotional offers applied
• Total bill amount
• Total quantity sold

This data helps you identify your best-selling products, peak sales periods, and high-value customers.

Purchase Bills

Your purchase entries tell a clear story about how and where you spend money.

They typically record:

• Date of purchase
• Supplier details such as name and location
• Items purchased with SKU, size, color, quantity, and price
• Total purchase amount
• Total quantity purchased

Analyzing this data helps you control costs, compare suppliers, and plan smarter purchases.

Inventory Data

Inventory data is where most fashion businesses either gain control or lose money.

Your system already tracks:

• Purchase quantity
• Sales quantity
• Items sold and items added
• Stock adjustments due to damage, loss, or manual corrections
• Returned items added back to stock

This data shows which products move fast, which ones stay stuck, and where your working capital is blocked.

Goods Returns (Sales or Purchase)

Returns are often ignored, but they reveal important problems.

Return data usually includes:

• Date of return
• Customer or supplier details
• Items returned with SKU, size, color, quantity, and price
• Total return amount

Returns can highlight quality issues, sizing problems, pricing mistakes, or wrong buying decisions.

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All of this data already exists inside your billing or ERP software.

You don’t need to collect anything new. You just need to look at it differently.

By the way, we don’t need all those details for now, as for this blog, I will focus only on the sales, stock and customer data that is most relevant to fashion retail businesses to understand following patterns: - Sales pattern - Stock pattern - Customer pattern

What we will be needing is only one thing, Item-wise sales report, that’s it, what I call that is stock out report, don’t ask me why, it’s just a name I use cause it’s easier to remember (you know, stock that are going out simple as that).

This report should contain following details: - Date and time - Item Name - Category - Size - Color - Customer name - Quantity - Purchase rate - Sales Rate - Discount - Total Amount

If you are using our billing software, you can easily get this report by going to Reports > Stock Out Report.

If you are not using our billing software, don’t worry, most billing or ERP software have similar reports, just look for item-wise sales report or stock out report in your software, if you can’t find it, contact your software support team, they will help you get it.

Just export the report into CSV format, and you are ready to start your data analysis journey.

In the next section, we will focus on the most important part of data analysis: asking the right business questions before opening Excel.

The 5 Business Questions You Should Ask Before Touching Excel

Before opening Excel, creating charts, or exporting data from your billing or ERP software, pause for a moment.

Data analysis does not start with tools.

It starts with questions.

Without clear questions, Excel quickly turns into a mess of numbers that look impressive but change nothing in your business.

Here are five simple but powerful questions every fashion retail or apparel business owner should ask first.

1. Which products are actually making me money?

This seems like an obvious question, but most retailers confuse “top-selling” with “most profitable.”

A kurta that sells 500 pieces at a thin margin may bring in less profit than a jacket that sells 50 pieces at a healthy margin.

When you ask this question, you are not just looking at sales volume. You are looking at profit per item, profit per category, and whether your best sellers are also your best earners.

This question forces you to calculate margins, not just count quantities.

2. Which sizes and colors are selling well, and which are not?

In fashion, wrong sizes and colors are silent profit killers.

You may be ordering XL in every design, but if your sales data shows XL barely moves while M and L fly off the shelves, you are wasting money on stock that won’t sell.

This question helps you identify:

• Which sizes sell the most across all categories
• Which colors perform well and which struggle
• Size and color combinations that consistently underperform

When you know what sells and what doesn’t, you can order smarter next time and avoid blocking capital in slow-moving variants.

3. Who are my most valuable customers?

Not all customers are equal. Some buy once and disappear. Others keep coming back season after season.

This question helps you identify:

• Repeat customers who bring consistent revenue
• High-value customers who spend more per visit
• Customers who only buy during sales versus those who pay full price

Once you know who your valuable customers are, you can focus on retaining them instead of constantly chasing new ones.

4. When do I sell the most, and when do I sell the least?

Sales are not evenly spread across the year. Fashion retail has clear peaks and valleys.

Understanding your sales pattern by month, week, or even time of day helps you:

• Plan purchases before peak seasons
• Avoid overstocking during slow months
• Schedule promotions when traffic is already high

This question is about timing, which is everything in fashion.

5. Are my discounts helping or hurting my business?

Discounts feel good because they bring in customers. But if you discount too often or too deeply, you train customers to wait for sales.

This question makes you look at:

• How much revenue came from discounted sales
• What was the average discount percentage
• Whether discounts actually increased volume or just reduced margins

It also reveals if certain categories only sell at discounts, which is a sign you may be pricing them wrong from the start.

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These five questions are your compass.

Keep them in front of you before you open any Excel sheet. Every analysis you do should answer one or more of these questions. If it doesn’t, you are probably wasting time on data that looks interesting but changes nothing.

In the next section, we will learn how to use basic Excel functions to answer these questions using your item-wise sales report.

Basic Excel Functions Every Retailer Should Know

You don’t need to be an Excel expert to analyze your data.

In fact, with just five or six simple functions, you can answer all five business questions from the previous section.

These functions are built into every version of Excel and Google Sheets. No add-ons, no macros, no complicated formulas.

Let’s go through them one by one.

SUM: Add Up Your Numbers

The SUM function adds up a range of numbers.

Example: To find total sales from your report:

=SUM(K2:K1000)

This adds all values in the Total Amount column from row 2 to row 1000.

Use it for:

• Total revenue
• Total quantity sold
• Total discount given

SUMIF: Add Numbers Based on a Condition

SUMIF adds numbers only when a condition is met.

Example: To find total sales for “Kurta” category:

=SUMIF(C2:C1000, "Kurta", K2:K1000)

This looks at the Category column, finds all rows where Category is “Kurta”, and adds the corresponding Total Amount values.

Use it for:

• Sales by category
• Sales by customer
• Sales by size or color

COUNTIF: Count How Many Times Something Appears

COUNTIF counts how many times a specific value appears in a range.

Example: To count how many times “XL” size was sold:

=COUNTIF(D2:D1000, "XL")

Use it for:

• Number of transactions per customer
• How many times a product was sold
• Quantity of items in each category

AVERAGE: Find the Middle Point

AVERAGE calculates the mean of a range of numbers.

Example: To find average transaction value:

=AVERAGE(K2:K1000)

Use it for:

• Average bill value
• Average discount percentage
• Average margin per item

UNIQUE and COUNTA: Find Distinct Values

UNIQUE gives you a list of all unique values in a column. COUNTA counts non-empty cells.

Example: To count how many unique customers you have:

=COUNTA(UNIQUE(F2:F1000))

This first creates a list of unique customer names, then counts them.

Use it for:

• Number of unique customers
• Number of unique products sold
• Number of unique categories

Bonus: Calculating Profit and Margin

Your item-wise report has both Purchase Rate and Sales Rate. Use them to calculate profit.

Profit per item:

=(I2-H2)*G2

Where I2 is Sales Rate, H2 is Purchase Rate, and G2 is Quantity.

Margin percentage:

=((I2-H2)/I2)*100

This tells you what percentage of your sales price is actual profit.

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These six concepts are enough to analyze most of your data.

You can combine them, nest them, and use them with filters to get more specific answers.

In the next section, we will apply these functions to answer each of the five business questions step by step.