What is Discrete Data

Discrete data is a subset of quantitative data. It comprises whole numbers and is expressed in distinct values. There’s no room for fractions or decimals.

Let’s say you own a clothes shop. You want to see how many people buy certain items of clothing, so you take a look at the sales records and see that the number of people who’ve bought a dress is 356, the number of people who’ve bought shoes is 233, and pants is 300. This is an example of discrete data.

In marketing, discrete data can manifest in different ways such as the number of purchases made, the number of clicks on links, of sign ups to newsletters, etc. It’s easy to compute and analyze so it plays a key role in measuring performance metrics.

Data is the foundation of marketing. It lets marketers know which tactics are working and which are underperforming. Discrete data with its binaries is some of the best data companies can study in order to see which marketing strategies and products are producing the best results.

In this article, we’ll go over how it’s used, differences with continous data and how to implement it.

Discrete Data and Continous Data — What’s the Difference?

Quantitative data consists of another category called continuous data. Continuous data deals with everything that is in between discrete data. Unlike the latter which deals with whole numbers and where there’s a distinct space between each value, continuous data is exact and includes decimals. It’s great for getting nitty-gritty data because it’s far more granular than discrete data. It can measure the entire range of values that is possible.

Continuous data is used when measuring something, which gives more insight than counting it. Measuring how long a visitor stays on your website or what percentage of an article they’ve read are examples where continuous data proves more useful than discrete data.

This table outlines the key differences between discrete and continuous data

Discrete Data	Continuous Data
Consists of individual, separate numbers	Represents any calculated value within a range
Values are represented by whole numbers	Values can be represented by fractions or decimals
Used for counting	Used for measuring
There are spaces between each value	Can express the minutest variable

What Can I Use Discrete Data For?

As we’ve mentioned, discrete data is used when you need to count something. So, any of these situations where the data is whole can be collected using discrete data:

Counting the number of items in stock.

The number of employees or teams in your company

Obviously, there can’t be half or a quarter of an employee, so the number of persons or divisions that are working in your organization is a form of discrete data.

Sales Metrics

Discrete data is often used to calculate the number of sales made at any given period of time – whether it’s the last quarter or the past month. It gives the management a clear idea of how successful the product is and if sales are climbing or falling.

New Clients Gained

Similarly, the number of customers your business has earned over time is a form of discrete data.

Calculating the Number of Website Visitors

Every user that visits the website forms a value of discrete data because they are one whole person.

Social Media Engagements

Social media engagements like comments, the number of viewers or subscribers, likes, dislikes and shares are all tracked through discrete data.

Link Click Tracking

The number of clicks on any links such as those in an ad leading to your website or any links shared on a webpage or other communication form a type of discrete data. There’s no such thing as half a click, they either click on it or they don’t, so it’s a good way to measure the efficacy of your advertising.

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What About Continous Data?

Continuous data is the way to go when you need more accurate measurements of interactions or engagements. It’s easy to break down into bite-sized pieces, enabling marketers to conduct more thorough, in-depth analyses where the tiniest percentage matters.

Use continuous data when measuring the following situations:

User Time on Web Pages

The amount of time every user spends on a webpage can be accurately measured by continuous data. It can measure it down to the millisecond, which is useful to see how user’s attention is being engaged. It could be from 1 minute, 20 seconds to 1 minute 50 seconds — continuous data really gets down to the granular level.

How Long An Ad Is Being Watched

Similar to how long a visitor spends on a web page, continuous data can tell advertisers the amount of time a user watches a video ad. Here the milliseconds count because we can pinpoint the exact time the user’s concentration or patience breaks and make improvements using this data to deliver the message effectively.

Scroll Depth

Scroll depth is the amount of an entire article that a user reads (how low that scroll bar goes). This data is represented as a percentage and reveals to the writer how engaging their article was and where most readers stop reading.

How Discrete Data Can Be Represented

The raw numbers of discrete data can be put into a visual format, which can help marketers better analyse the information collected. Some popular graphical representations include:

Bar Charts

Probably the most popular way to represent discrete data. Here, the values are represented on the Y axis, and the rectangular bars represent the number of people, products or engagements. Take, for example, a bar chart depicting the most bought ice cream flavours.

Pie Charts

Pie charts are a great way to represent the proportion of the different categories of the discrete data in connectin with the greater whole. A pie chart can be used to represent the share of engagements on each social media platform.

Histograms

A histogram represents the share of a numeric variable’s values as a series of bars corresponding to an interval. For instance, you can use it to illustrate how website traffic varies according to the days of the week.

Bullet Chart

A bullet represents a metric compared to two other metrics in order to measure performance and progress. For example, a small business has a set goal to sell 500 products in a month and they were able to sell 300, then this will be represented by two bars with the smaller bar superimposed on the larger one.

Dot Plots

Dot plots or dot charts are a type of visual representation of data where the data points are depicted as dots representing a number and the Y axis represents the frequency. It’s pretty similar to a bar chart and is a fun way to represent data. You can make a dot chart to represent the number of clicks on an ad, for example.

Conclusion

Data in all its forms, whether quantitative or qualitative, structured or unstructured, is the lifeblood of marketing.

It enables marketers to see which tactics are working and the tools most effective for their purposes, as well as to stay on top of trends. Data charts out the success and performance of the company and allows us to spot the gaps in all aspects of business, from advertising to product popularity. It also helps to find out the audience who are using your products and services. If a company wants to stay afloat, it has to listen to what the customers are saying, doing, and clicking.

Discrete data is a rather simplistic method of data collection. It represents every finite interaction and purchase that’s happened, so it’s easy to track and learn from. The strong suit of discrete data is when it comes to counting variables. It may not be able to be as granular as continuous data, but that doesn’t mean it’s any less important. A blend of discrete and continuous data will allow your company to chart their methods and finetune weaknesses here and there, allowing you to stay on top and edge out competitors.