The Fundamentals of Descriptive, Predictive, and Prescriptive Analytics

The Fundamentals of Descriptive, Predictive, and Prescriptive Analytics

The more accurate and insightful data you have, the better decisions you can make. If you work in any field where data is important, then you've probably heard the terms "descriptive analytics," "predictive analytics," and "prescriptive analytics."

In this blog post, we'll look at the basics of these types of analytics. We'll also see how they can help you make better decisions with your data. Read on to have descriptive, predictive, and prescriptive analytics explained.

Descriptive Analytics and Ways to Utilize a Descriptive Analysis

So, what is descriptive analytics? Descriptive analytics is the process of turning data into information that can be used to describe, understand, and visualize what has happened. It's all about describing the past. An example would be looking at historical sales data charts to see which products have been selling well and which ones haven't.

A descriptive analytics process answers questions such as "what happened?" and "how often did it happen?" Its primary focus is on summarizing data, finding patterns, and providing manageable data sets.

There are several ways businesses use descriptive analytics.

Report on Past Revenue and Business Growth

A descriptive analytics process can be used to do business intelligence reporting on past revenue and business growth. This can help you understand where your business has been and where it is going. To be effective, you will need to collect data on your revenue and growth over time.

This data can be collected from various sources, such as financial reports, tax returns, and sales records. Once you have this data, you can begin to analyze it. Look for patterns and trends in your revenue and business growth.

The data will help you understand what has been working well for your business and what needs to be improved. You can then use this information to make decisions and implement an effective business strategy.

Descriptive analytics can also be used to find sales trends in different customer segments. This can help you target your marketing efforts and improve your sales strategy. You'll need to segment your customers by their characteristics (such as age, gender, location, etc.). Then, you can analyze the sales data for each segment to gain knowledge about which segments are growing and which segments are declining.

You can also use descriptive analytics to measure the performance of your sales team. This can help you identify which salespeople are meeting their targets and who is falling short.

Predictive Analytics and How to Apply a Predictive Analysis

Predictive analytics is the branch of advanced analytics used to make predictions about unknown future events. Predictive analytics uses statistical techniques to make predictions about future events. It is based on the assumption that the future can be predicted by understanding the patterns in past data.

It answers questions such as "what will happen?" and "what is the most likely outcome?" Predictive analytics works like descriptive analytics, but it goes one step further. It uses historical trends and patterns from predictive analysis to make predictions about future events.

You can use predictive analytics for various purposes. For example, to predict marketing performance. Other uses include creating accurate financial projections and anticipating inventory demands.

Predict Marketing Performance With New Strategies

One of the uses of predictive analytics is to predict and measure performance of your marketing campaigns. This information can be used to create more effective marketing strategies.

To run predictive analytics, you need to collect data on your marketing campaigns. This data can include the number of impressions, clicks, and conversions for each campaign. You can then use this data to build predictive models. These models will identify patterns and trends in your marketing data, which can in turn be utilized to make predictions about the performance of future campaigns.

You can also use predictive analytics to segment your customers. This is done by identifying the characteristics of your most valuable customers. The segments are used to create targeted marketing campaigns.

Create Accurate Financial Projections and Anticipate Inventory Demands

Another use of predictive analytics is to create accurate financial projections and generate inventory demand estimates. This information can be used to make better decisions about your business finances and stock levels.

You need to collect data on your past financial performance and inventory levels. This data can include revenue, expenses, and profit margins when generating financial projections. When generating a predictive model for inventory demand estimates, you will use data such as the number of units sold, the number of units in stock, and the reorder level. You can then use this data to build predictive models that accurately predict future actions.

These models will identify patterns and trends in your financial or inventory data, and provide insights into your future outlooks. The insights from these models can then be used to make predictions about your future financial performance and future actions.

Prescriptive Analytics and Actionable Insights From a Prescriptive Analysis

Prescriptive analytics is the process of using data and statistical methods to prescribe actions that will produce the desired outcome. It answers questions such as "What should we do next?" or "What is the best way to achieve our goals?"

Actionable insights from prescriptive analysis are useful in many ways in the business analysis process. For example, you can use these insights to:

  • Determine the next product to market
  • Improve sales strategies and processes
  • Optimize pricing models

Determine Next Products To Market

One of the most common uses for prescriptive analytics is to determine the next products to market. This is done through pattern tracking to identify trends in your data. This information will help you create a marketing plan that targets the right customers with the right products.

To carry out this type of analysis, you need access to data that includes information about customer behavior and preferences. Once you have this data, you can begin to build prescriptive models that can determine key decisions. These models use mathematical algorithms to identify the best possible course of action (key decision).

Improve Sales Strategies and Processes and Optimize Price Modeling

Actionable insights from the prescriptive analysis can also be used to improve sales strategies and optimize pricing models. For example, they can be used to create effective sales plans or optimize existing ones.

In order to conduct this type of analysis, you need data about customer behavior and preferences. This data can be collected through surveys, customer interviews, focus groups, or data mining. Once you have this data, you can begin to build prescriptive models. The models will guide you to the right steps to improve sales strategies or optimize your pricing model.

Streamline Your Business Analytics Process With a Data Visualization Dashboard

By understanding the three types of analytics — descriptive, predictive, and prescriptive — you can arm yourself with insights to make better business decisions. However, it can be difficult to know where to start or how to improve your business analysis process. That’s why we offer Canvas, a platform that makes data visualization easy and user-friendly.

With Canvas, you can create custom data visualization dashboards in minutes with just your spreadsheet skills. This will help free up time to focus on strategic work, collaborate in real-time where the data lives, and get feedback on how teams consume data. Sign up today and try Canvas for free. With powerful visuals at your fingertips, you will gain insights into your business performance like never before.