Descriptive Analytics Meaning Examples

Descriptive Analytics Meaning Examples. The goal of business analytics is to identify patterns and trends in large amounts of data to help organizations make better decisions and improve performance. Analyzing data descriptively is the most basic and widely used type of analytics; it produces the KPIs and metrics used in business reports.

A descriptive analytics report summarizes and highlights patterns in current and historical data to help companies understand what has happened. Although it attempts to predict what might happen in the future, it does not attempt to analyze why something happened. Combining descriptive analytics with other methods of analysis is necessary to explore those questions.

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Meaning of Descriptive Analytics

A descriptive analytics study is the most common and fundamental form of analytics used by companies. To monitor trends and keep tabs on operational performance, descriptive analytics can be used in every part of the business.

KPIs such as revenue per customer, sales growth year over year, and the average time it takes for customers to pay their bills are examples of descriptive analytics. Presentations, dashboards, and financial statements are products of descriptive analytics.

This type of analysis is particularly useful for communicating changes over time, as well as assisting in the development of decisions by utilizing trends as a basis for further analysis.

Examples: Descriptive Analytics Meaning Examples

To help you implement descriptive analytics in your organization, here are five examples.

Traffic and Engagement Reports

Among the examples of descriptive analytics is reporting. You’re already using descriptive analytics if you track engagement on social media or through web traffic.

By comparing current metrics to historical metrics and visualizing trends, these reports are created by analyzing raw data from your website, advertisements, or social media channels.

If your company’s product page receives the most traffic from certain media channels, you may need to report on them. The number of users from each source can be determined using descriptive analytics on the page’s traffic data.

If you decide to go one step further, you may want to compare traffic source data to historical traffic data. As an example, you might highlight that paid advertisement traffic increased 20 percent over the past year to update your team.

You can use the three other analytics types to figure out why traffic from each source has increased or decreased over time if trends are likely to persist, and what your team should do next.

Financial Statement Analysis

You may be familiar with financial statement analysis as another example of descriptive analytics. Combined, financial statements provide a holistic picture of a company’s financial health by detailing financial information about the business.

Statements of shareholders’ equity, income statements, cash flow statements, and balance sheets are all types of financial statements. The different reports target different audiences and convey different information about a company’s finances.

An analysis of a financial statement can be done in three ways: vertically, horizontally, or by using ratios.

In vertical analysis, each item in a statement is compared to those above and below it from top to bottom. Using this method, you can determine how variables relate to each other. Comparing line items, for example, can provide insight into which are taking up the largest and smallest percentages of the total.

In horizontal analysis, a statement is read from left to right and each item is compared to itself from a previous period. Analyzing change over time is the purpose of this type of analysis.

In addition, ratio analysis compares one section of a report to another according to their relationship to the whole. By comparing items across periods and your company’s ratios with the industry’s, you can determine whether yours is overperforming or underperforming.

These methods of financial statement analysis are examples of descriptive analytics, since they provide information based on current and historical data about trends and relationships between variables.

Demand Trends

In addition, descriptive analytics can be used to identify trends in customer preferences and behavior so that assumptions can be made about a specific product or service’s demand.

This descriptive analytics application is a perfect example of a streaming provider using descriptive analytics to identify trends. The Netflix team, which is incredibly data-driven, gathers data on users’ behavior on the platform. On the platform’s home screen, trending titles are listed in a section that analyzes this data to determine which television shows and movies are popular.

Not only does this data show Netflix users what’s popular and what they might enjoy watching-but it also lets Netflix know what types of media, themes, and actors are popular at certain times. Marketing, retargeting campaigns, and contracts with existing production companies can all be informed by this data.

Aggregated Survey Results

Market research can also benefit from descriptive analytics. The use of descriptive analytics can be helpful in identifying relationships between variables and trends from survey and focus group data.

If you conduct a survey, you might find that customers are more likely to buy your product as their age increases. Descriptive analytics can tell you if this age-purchase correlation has always existed or if it is something that only happened this year if you have conducted this survey multiple times.

The use of diagnostic analytics can explain why certain factors are correlated based on insights like this. By analyzing those trends, you can use predictive and prescriptive analytics to improve your products or plan marketing campaigns for the future.

Progress to Goals

To track progress toward goals, descriptive analytics can be applied. Tracking progress toward key performance indicators (KPIs) can help your team determine if efforts are on track or if adjustments are needed.

Traffic data can help you communicate your progress towards your organization’s goal of 500,000 unique page views per month, for example. By the middle of the month, you may have 200,000 unique page views.

Having 250,000 unique page views at that point would be underperforming because you should be halfway to your goal. Analyzing your team’s progress descriptively can allow further analysis to examine how to improve traffic numbers and achieve your KPIs by improving your strategies.

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