Predictive Versus Prescriptive Analytics: Why You Need Both

More and more every day, analytics play a critical role in making better-informed business decisions, especially in the area of marketing. To deliver value, analytics must transform data into actionable insights.

Predictive and prescriptive are the two primary types of analytics. Both use data, and typically machine learning, to inform the decisions businesses make. The key differences between them:

• Predictive analytics anticipates what might happen in the future based on historical business data and economic and consumer trends.
• Prescriptive analytics goes a step further by laying out specific actions to achieve the best outcomes.

This guide explores predictive and prescriptive analytics, their benefits, and why you need both.

Predictive Analytics: What You Need to Know

Predictive analytics explain what might happen in the future. Predictive models analyze historical data to identify patterns and predict future trends, behaviors, and outcomes. ‍

‍Examples of predictive analytics in action

An example of the use of predictive analytics in marketing is when businesses leverage data to recommend products and services to a website visitor based on past purchases or online activity. It can also power content marketing programs by offering up material in emails or social media that visitors are more likely to engage with based on past activity.

Marketing-adjacent uses of predictive analytics include a retailer leveraging it to forecast seasonal sales demand and then adjusting promotional activity based on the information. The retailer can predict which products will likely sell out by analyzing sales data and adjusting inventory levels accordingly. Marketers can then pull back on — or increase —promotion.

Beyond marketing-related uses, predictive analytics can improve pricing, inventory forecasting, and credit scoring.

The power of predictive analytics is – as its name suggests – predicting the likelihood of marketing success, consumer demand, market movements, and possible risks. This allows businesses to make better-informed decisions and take steps to prepare for the future.

Benefits of predictive analytics

Leveraging predictive analytics can provide businesses with considerable benefits, including:

• Improved decision-making. Companies with a clearer picture of the future can better prepare for it.
• More personalized marketing. Personalized promotional efforts tend to be more effective at generating sales. Predictive analytics can help determine what customers want to purchase or engage with next.
• Optimized operations. Leveraging predictive analytics can help anticipate inventory and warehousing needs, prevent equipment failures, streamline supply chains, and price items more competitively, even during changing times like today. All these things will help keep consumers happy.
• Enhanced customer experience. A better understanding of the future allows you to personalize marketing, reduce customer churn, and boost engagement with your brand.

Clearly, introducing predictive analytics into your business could improve decision-making, marketing, and other aspects of your operation.

Prescriptive Analytics: What You Must Know

Prescriptive analytics goes beyond predictive by helping you understand what to do next. It uses advanced artificial intelligence (AI) and machine learning (ML) to suggest specific actions based on predicted outcomes. It helps you find the best ways to achieve your marketing and other business objectives.

Examples of prescriptive analytics in action

Are you under pressure to improve your marketing and other aspects of your business? Here’s how prescriptive analytics can help:

• Media selection. Are you unsure what the best media option is to promote your business? Predictive analytics can analyze data to identify the ideal ones for your target audience.
• Pricing. AI and machine learning can help you identify competitive dynamic pricing structures even in these rapidly changing times.
• Customer retention. Prescriptive analytics can leverage predictive information about the reasons for customer churn and suggest strategies to prevent it.

Prescriptive analytics can be used in marketing and other business functions, and the possibilities are only limited by your imagination and the quality of your data.

Prescriptive Analytics Versus Predictive Analytics: The Differences

While both provide value to businesses, prescriptive analytics goes beyond predictive. Predictive leverages a forecast about the future and actually recommends actions to take to reach the best outcome based on that forecast. Predictive analytics uses machine learning, regression, and time series models to generate insights. It is backed by optimization algorithms and scenario analysis.

Let’s go back to the example of a business wanting to understand its customer retention level better and develop new strategies to retain more customers. The company could start by inputting data into a predictive analytics model. It will then report on retention trends and causes of customer loss. After learning this, the business could use prescriptive analytics to come up with the best retention strategies based on its situation. The solutions could include things like offering discounts on additional purchases, personalizing marketing tactics, or improving customer service.

Optimizing Use of Predictive and Prescriptive Analytics at Your Company

Here’s what to consider to make the most of your analytics program.

Focus on business goals

When deciding whether to use predictive or prescriptive analytics within your business — or both — begin by considering your organization’s objectives.

• Do you want to better understand tomorrow’s trends or prepare your business for possible future events? Predictive analytics is a way to do both.
• Maybe you want to go beyond this and get specific recommendations about how to best deal with what could happen in the future. If that’s the case, prescriptive analytics is more appropriate. 

Maximize the value you get from your data and analytics program

The next thing you want to think about is the value you want to gain from your analytics efforts. Typically, combining both types of analytics maximizes the value of your data. By better understanding future outcomes and then implementing AI-based recommendations, you can improve marketing and business results by making better, data-backed decisions.

Understand the complexity of your needs

Effectively using predictive and prescriptive analytics depends on the complexity of your business requirements and your comfort with data, analytics, and AI-backed analysis systems. Start slow if your needs and comfort level are limited. Begin with some fundamental predictive analysis, then build up from there.

Companies that effectively implement both strategies gain a competitive edge by being able to anticipate and shape the future by making informed business decisions rather than just reacting to events.

Predictive Versus Prescriptive Analytics: The Final Word

Both predictive and prescriptive analytics are valuable for helping companies make better data-driven decisions about their marketing programs and other aspects of their operations. Predictive analytics enables you to understand what could happen in the future. Prescriptive analytics leverages that information to deliver actionable insights that make your marketing and other business efforts more likely to succeed.

When you leverage these two powerful strategies in tandem, you transform raw data into highly valuable, actionable insights that will ensure your marketing efforts are as relevant and successful as possible now and in the future.

Need help with your data analytics? The experts at Jarrah can answer your questions and set you on the proper path to the future.

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