# What is Quantitative Analysis?

By Indeed Editorial Team

Updated November 23, 2022 | Published May 17, 2021

Updated November 23, 2022

Published May 17, 2021

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

When measuring the success of a business, quantitative analysis can be useful. Quantitative analysis explores facts, measurements, numbers and percentages to gauge the behaviour of something. In this case, how well a business is behaving. In this article, we'll discuss what quantitative analysis is, how it's different from qualitative analysis and how you can apply it in business.

## Definition of quantitative analysis

Quantitative analysis uses research, measurement and mathematical and statistical modelling to better understand the behaviour of past, current and future events. You can use it to gauge the behaviour of large-scale quantifiable matters like predicting changes in a country's GDP, determining the value of a stock or creating successful marketing strategies. Essentially, quantitative analysis is used to predict outcomes, identify trends or patterns and examine behaviour and events.

Most industries use quantitative analysis but it's most popular among financial analysts and government officials. Financial analysts that rely strictly on quantitative analytics to determine economic trends are known as Quants or Quant Jockeys.

Related:

• Analytical Skills Defined and Explained

• How To Become a Big Data Analyst (With Salary Expectations)

## How is quantitative analysis different from qualitative analysis?

Another method of data collection and processing is qualitative analysis. You can use qualitative analysis and quantitative analysis together to make the most informed decision. Here are the main differences between the two:

• Quantitative analysis: focuses on answering the question, “what happened?” by looking at hard data, such as statistics, measurements or numbers.

• Qualitative analysis: focuses on answering the question, “why did that happen?” with less tangible, subjective results, such as customer surveys, focus group discussions or interviews.

Related: Examples of Qualitative Data (Definition and Advantages)

The key distinctions between quantitative analysis and qualitative analysis can be either conceptual differences or functional differences, such as the following:

### Conceptual differences

Conceptual differences consist of what a specific type of analysis is designed for. Here are the conceptual differences between quantitative and qualitative analysis:

• quantitative analysis deals with facts

• quantitative analysis assumes reality is measurable

• qualitative analysis analyzes the reason for a behaviour

• qualitative analysis assumes reality is always changing

• qualitative analysis includes variables that are hard to measure numerically

Related: What Are Conceptual Skills: Definition and Examples

### Functional differences

Functional differences consist of differences in methodology. Here are the functional differences between quantitative and qualitative analysis:

• quantitative research collects data through measurements

• quantitative analysis uses values and statistics to predict outcomes

• quantitative analysis reports data in statistical values

• qualitative research collects data through observation and interview techniques

• qualitative analysis uses information collected in interviews and surveys to predict outcomes

• qualitative analysis conveys information using language and description

## When to use quantitative analysis or qualitative analysis

Although you can use quantitative and qualitative analysis together, different situations may call for one without the other. If you want to confirm or test something, use quantitative analysis. If you want to understand something, you should use qualitative analysis.

For example, if you want to determine whether people are happy with a specific product, you could survey 100 past customers and ask them, “On a scale of one to five, how happy are you with XYZ Product?” This allows you to collect and analyze statistics from the data to draw conclusions, such as, “75% of customers are extremely happy with this product.”

With a qualitative analysis approach, you could ask customers open-ended questions instead, such as, “What do you like about this product?” or “How can we improve this product?” You can then analyze their answers to find commonalities or patterns to improve your product.

If you wanted to use both types of analyses, you could provide customers with a survey containing quantitative and qualitative questions. This gives you in-depth insight, as you are collecting answers in several forms.

Quantitative analysis is a great way to collect important information about how your business is doing. Here are two types of statistics you can use to analyze results from sales, interviews, tracking inventory and more.

### 1. Descriptive statistics

As the name suggests, descriptive statistics describe your data set to help you understand the sample details. Descriptive statistic techniques include the following:

• mean: the average of your range of numbers

• median: the middle point of your range of numbers arranged from low to high

• mode: the most frequent number

• percentage: expresses how a value within the data relates to a larger value

• frequency: the number of times a number appears

• range: the highest and lowest numbers in your set of values

Using these techniques helps you see both the bigger picture and finer details of your statistics to properly analyze them. Use these descriptive statistics in business by looking at monthly sales trends, tracking inventory and keeping track of delivery times.

### 2. Inferential statistics

Inferential statistics help you draw conclusions about the population you're analyzing and make predictions about the total population. Inferential statistic techniques include the following:

• t-tests: compare the average of two groups of data to see how different they are

• ANOVAs: similar to T-tests but they analyze multiple groups

• correlations: assess the relationship between two variables

• regressions: look at the cause and effect between variables

These inferential statistic techniques are great for forecasting future trends in business, such as predicting whether a certain product or service will do well before you release it.

Related: Inferential Statistics: Definition and Pros and Cons

## How you can apply quantitative analysis in business

You can use quantitative analysis for business in a variety of ways, like the following:

Marketing includes a wide range of things, such as advertising, public relations and promotions. But one of the best ways to evaluate your marketing strategies is to examine them using quantitative analysis, which you can do in a variety of ways. One way is to look at your website statistics to see how much traffic you have, where it's coming from and what parts of your website are most popular.

You can also monitor your engagement on social media to see what type of posts garner the most attention, or review response rates to promotions by seeing how many customers use a certain promo code. Ultimately, using quantitative analysis helps you hone your marketing techniques so you can determine what's working, what's not and adjust accordingly to improve.

Related: What Are Quantitative Research Methods? (With Benefits)

### Decide whether an advertising campaign is worth it

A big part of marketing is creating advertising campaigns, which are expensive. However, you can use quantitative analysis techniques to assess the value of marketing costs. Quantitative data points and projections compare the anticipated return on investment of the campaign against the cost. If you decide the campaign is worth it, you can use quantitative analysis to track its results and success.

Related: What Are Success Metrics? (With Tips for Using Them)

You can also use quantitative analysis to track your finances. One way is to divide your expenses into production and overhead costs. This allows you to create a quantifiable analysis of how different sales, times of the year, and more affect your profit margins and gross profit. If you have long-term financial records, you can create quantifiable analyses of your debt, taxes, profits and much more. Using quantitative analysis for your finances helps you monitor growth. You can then determine exactly where you're spending money and make any necessary changes to improve profits.

### Sales analysis

If your business relies on sales, creating quantitative analyses that track them is important, as you can't solely review gross sales to calculate your earnings. You can use quantitative analysis to determine if you need to raise or lower prices, spend more money on advertising a specific product or service, drop a product in your store, change distributors or wholesalers and much more. Quantitative analysis tracks your sales to see where you're earning the most money and shows how you can earn more.

### Budget variance analysis

Many businesses create budgets to guide and limit spending. However, even if you have a budget in place, you may not always be able to stick to it. Budget variance analysis demonstrates whether you've stayed within your projected budget. You can then use quantitative analysis techniques to analyze monthly, quarterly or annual budgets and see where your money is going. You can then determine whether you're spending too much or too little on things like expenses, overhead costs, debt, production costs, hiring new employees and more. It will also help you create a more accurate budget in the future.

Related: How to Write a Project Budget (Importance and Steps)