WHAT IS DESCRIPTIVE ANALYTICS

DESCRIPTIVE ANALYTICS

The process of identifying trends and correlations in real-time and historical data is known as descriptive analytics. Because it highlights patterns and associations but does not drill down, it is often referred to as the most basic type of data analysis. 

Descriptive analytics is inexpensive and presumably used on a regular basis in your firm. Data visualization tools, such as Google Charts and Excel, may assist in analyzing data, detecting patterns and correlations between variables, and visually showing information.

Descriptive analytics is particularly useful for describing change over time and for using patterns as a springboard for more research to help inform decision-making.

Here are five examples of descriptive analytics in action that you may use in your company: 

1. Reports on Traffic and Engagement

Reporting is an example of descriptive analytics. If your company measures interaction through social media analytics or online traffic, you’re already using descriptive analytics. These reports are made by comparing current metrics to historical metrics and visualizing trends using raw data collected from people who interact with your website, advertisements, or social media content.

2. Financial Statement Examination

Another type of descriptive analytics you might be familiar with is financial statement analysis. Financial statements are quarterly reports that contain financial data about a company and, when analyzed together, provide a comprehensive picture of its financial health.

The balance sheet, income statement, cash flow statement, and statement of shareholders’ equity are all examples of financial statements. Each caters to a certain audience and offers various financial facts about a firm.

There are three major approaches to financial statement analysis: vertical, horizontal, and ratio.

Vertical analysis is the process of reading a statement from top to bottom and comparing each component to those above and below it. This aids in determining the links between variables. For example, if each line item represents a percentage of the total, comparing them might reveal which are greater and smaller percentages of the whole.

The horizontal analysis involves reading a statement from left to right and comparing each item to a previous era. This type of research examines how things change over time.

Finally, ratio analysis compares one section of a report to another based on their relationship to the whole. This examines trends over time as well as your company’s industry ratios to see if you’re outperforming or underperforming.

Because it provides information about trends and correlations between variables based on current and historical data, each of these approaches to financial statement analysis is an example of descriptive analytics. 

3. Demand Patterns

Descriptive analytics may also be used to uncover trends in client preferences and behavior, as well as establish assumptions about demand for certain items or services.

Netflix’s trend detection service is an outstanding use case for descriptive analytics. Netflix’s crew, which has a history of being very data-driven, collects information on users’ in-platform activities.

4. Survey Results as a Whole

Descriptive analytics may also be used for market research. When analyzing survey and focus group data, descriptive analytics can help identify patterns and links between variables.

For example, you may run a poll and discover that as respondents’ ages grow, so does their probability of buying your goods.

5. Make Progress Towards Goals

Finally, descriptive analytics may be used to monitor progress toward targets. Reporting on progress toward key performance indicators (KPIs) can help your team figure out if their initiatives are on track or if they need to be tweaked.

What Is the Process of Descriptive Analytics?

Before converting raw data from multiple sources into a standard format for analysis, businesses must first gather and combine it. They’re then ready to analyze the information. Many companies use data intelligence, which is a set of methodologies and technologies for gathering and analyzing data prior to making decisions. conclusions and developing action plans based on the results. Others use spreadsheet formulae to perform basic descriptive analytics on aggregated data, producing metrics and other statistics that are later included in reports.

Descriptive analytics is an important tool for businesses to use when dealing with large amounts of historical data. By measuring key performance indicators (KPIs) and other variables, it aids you in monitoring performance and trends. By integrating descriptive analytics with diagnostic, predictive, and prescriptive analysis, companies may get deeper insights into the causes and expected future consequences of events, as well as potential actions they can take to enhance company performance.