How Predictive Analytics Is Transforming the Marketing Industry

by Frankie Wallace, Guest Contributor

As a marketer, imagine being able to analyze a complex set of data from millions of potential prospects and behaviors and attributes of your current customers. This data could reveal how people will use your website, how many times they’ll visit it or contact you before making a purchase, and information about what types of products they want. With so much data available from devices and online tracking, big data can provide trackable, predictable metrics so you can hone your marketing strategies and create tailored campaigns. Here’s how it works:

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Use Data to Predict Events
Even before the time of Nostradamus, people have searched for a way to predict the future. As it turns out, human behaviors and preferences have patterns. Prediction scientists can use historical data and information about the current state of world affairs to assess the likelihood of certain events such as the outbreak of war, political unrest, and terrorist events.

Human behavior, therefore, is quantifiable and follows patterns. Given that we can predict the possibility of larger events, especially with the aid of computers, smaller events are predictable as well. This includes marketing events based on past buying decisions and preferences, and the technology to work with this data is becoming increasingly affordable and available to private businesses.

Where Does Consumer Data Come From?
As a consumer, when you use platforms like Facebook and browsers such as Google Chrome, you’ve given permission for these applications to collect and store certain amounts of data. Platforms collect:

• Your demographics (age, gender, region, race, level of education)
• Your web searches (things you look up, purchase, and need)
• Your affinities (hobbies, entertainment you like)
• Psychographics (tells about your life goals, mood, attitude, and psychology)
• Identifying choices (such as religious or political beliefs, as you may have listed on your Facebook profile)
• Information on how actively you use various social media platforms

Here’s a really simplified version of how a car insurance company could use prediction analysis to serve an advertisement prior to the prospective customer actually researching car insurance rates:

Certain words or searches, such as queries for various car models, “getting married” or “moving to a new state” might identify a good customer — and through machine learning and predictive analytics, an insurance company with the right data can serve an ad to a customer before the customer even thinks to search for the insurance they will need to acquire or change.

A data analyst could take a sample of your customers who have authorized you to collect their data. The analyst and their computer could find the commonalities between your customers to find commonalities and focus advertising.

Why Are Predictive Analytics Helpful?
Predictive analytics allow you to know more about the customer and design your product (or at least your ads) according to their preferences. Additionally, you can target your ads quite specifically, and save money as you don’t have to target as broad an audience. Instead, consider investing that budget into inbound marketing and educational materials for your customers.

Predictive Analysis: Not Just About Sales
While big data and related analysis can help you sell, it’s not limited to that. Predictive analysis can help businesses streamline in many ways:

• Analyze the productivity, size, and scale of departments
• Minimize safety risks, especially in heavy casualty professions such as oil rig work
• Predict audience responses
• Refine credit and insurance risk formulas in banking
• Improve cybersecurity methods, both in the government and for private corporations and citizens
• Improve civic projects, such as traffic flow in a city or paths in a park
• Assist in medical diagnoses

Predictive analysis is already in the works: Starbucks even uses it to find optimal store locations.

The Dark Side of Predictive Analytics: Unethically Sourced Data
Think about the ethics of the products we consume in the real world. Did corporations pay workers fairly to obtain it? Do the workers have rights where the product or service is produced? Ethical sourcing applies to digital products and services, too. From social media swaying by planted “trolls” in comment factories in Russia and China to the revelation of how Cambridge Analytica helped the Trump campaign used unethically gathered Facebook data, predictive analytics requires a sizeable amount of information about your audience.

Predictive analytics are so valuable in marketing that corporate and political entities will apparently go to great risks to obtain it. Big data isn’t cheap—whether it’s acquired ethically or not.

The Future of Big Data
The Wall Street Journal predicts that in the future, big data will more effectively combine research points from multiple medias and collection sources to form a more complete picture of who might buy and when. As time moves on, analytics are especially essential to the successful marketing.

Whether you hope to improve your marketing skills, save money for your business or get ahead of the trend, you can’t go wrong by studying predictive analysis or hiring an expert to analyze user behaviors for you.
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