Data Analysis -Descriptive Analytics

In today's fast-paced business world, the power of data analysis cannot be overstated. According to a study by McKinsey Global Institute, companies embracing data-driven strategies are seeing remarkable gains – 23x more likely to acquire customers, 6x in retaining them, and 19x more likely to be profitable.

Posted by Judith Winkler MBA on January 18th, 2024

Data analysis is becoming increasingly important in the business world; according to McKinsey Global Institute, data-driven organizations are 23 times more likely to increase customers, 6 times more likely to retain them, and 19 times more likely to be profitable than businesses that don’t use data analysis. This study shows how important implementing BI (Business Intelligence) tools such as Power BI, Tableau, and Machine Learning is in today's world.

Only 3 in 5 organizations are using data analytics to drive business innovation according to (NewVantage Partners). 59.5% of business leaders say their companies are using data analytics to drive business innovation.

Data analysis provides business owners, executives, managers, etc., in-depth knowledge to help them make informed decisions. Data analysis types are descriptive, predictive, and prescriptive analysis. Business owners and stakeholders should not only understand them but also understand how they differ.

Descriptive Analytics

Descriptive analytics will answer the question “What has happened in our business?”. This analysis will use current and historical data to identify patterns, trends, and relationships. It will be organized and presented in a manner where business owners and stakeholders can understand them. Data analysis professionals will use statistical software like Microsoft Excel, Tableau, and Power BI, among others to identify trends, patterns, and relationships between variables. In addition, business owners will be able to visualize and easily understand the results to make informed decisions through interactive dashboards that can display line graphs, pie, bar charts, etc.

Descriptive Analysis communicates how the company changed over time and it’s the basis for further data analysis to drive decision-making.

Descriptive Analytics Examples

  • Traffic and Engagement Reports: Social media analytics or web traffic engagement reports are a form of descriptive analytics, they are created by tracking the data generated when users interact with the company website, social media, and/or advertising. Descriptive analytics will help businesses analyze media pages to understand the number of users coming from each source, and if the results are compared with historical data businesses can make informed decisions to optimize their marketing campaigns.
  • Financial Statement Analysis: Companies have different financial statements such as Balance Sheets, Income Statement, and Cash flow Statements, with specific information for a specific audience. These reports contain detailed business financial information and give an overall view of the organization's financial health.
  • Demand Trends: Streaming providers such as Netflix use descriptive analytics to identify customer preferences and make assumptions about customer demand for different products and services. The data gathered by streaming companies like Netflix can give the company information about when a product or service, in this case, a movie, is trending at a specific time, which can drive decision-making about original content, future product development, and marketing strategies.
  • Aggregated Survey Results: Descriptive analytics can help to identify relationships between variables and trends. When a company analyzes a survey, the results can give information about the relationship between different variables such as age, location, income, and the likelihood of buying a product. If the company has historical data, it can compare it with the current data and can infer if the variable correlation has always existed or if it is a new pattern.
  • Progress to Goals: Descriptive analytics can help companies realize if they are working towards reaching their goals. For example, if a company goal is to reach X number of sales and makes less than X sales, the company can communicate this to the sales department via a report and the sales department would understand that it is underperforming and could make the corresponding corrections to achieve their goals.

I have a small favor to ask, if you find this information useful, I ask that you share this blog with other business owners that might find this content useful as well. I will be setting a lot of effort towards posting regular content to help share knowledge about all things related to business and how data analytics can be used to improve companies. Thank you!