What is predictive marketing? Definition and examples

Everyone wants to know what customers want and what can be done to increase their engagement. While this information is not easy to obtain, some strategies can help predict future consumer behavior. One of them is predictive marketing. What is it and is it profitable?

What is predictive marketing?

Although the concept seems rather abstract, most of us have come across predictive marketing and it is quite common. The concept relies on specific historical data, statistics, and analysis to predict future consumer behavior. As a result, new marketing campaigns are not based solely on gut feelings, but on real data that allows for a more accurate assessment of the success of a given project.

For this purpose, specialized tools and artificial intelligence are most often used, which can efficiently and quickly analyze huge sets of numerical data. Without this support, analysis on this scale would be virtually impossible. Predictive marketing helps you see which direction is worth pursuing and whether your actions are having the right impact, but the final decision is always yours. Analyzing your actions will help you understand which of them are producing the expected results and which are not, but what you do about it is entirely up to you.

How does predictive marketing work?

The foundation of predictive marketing is data. This can come directly from the company’s resources or from external companies that specialize in providing data on consumer behavior. Brands can glean many valuable clues from their own websites or online stores thanks to cookies that collect relevant information about consumer activity. What’s more, predictive marketing helps companies identify sales opportunities.

Such in-depth analysis helps create personalized offers that can increase customer engagement and, in turn, revenue. Another benefit of such customization is improved customer satisfaction.

Examples of predictive marketing

Perhaps, after reading the theory above, you may not fully understand how predictive marketing works. If this is the case, we’ve got some useful examples for you.

1. Product recommendations

If you are an Internet user, you have probably encountered such a situation more than once. You’ve read about a product, let’s say a particular model of oven. You read reviews and check prices at various online stores, but you still haven’t made a purchase. Suddenly, an ad for that exact product appears almost everywhere: on your social networks, in banners on sites you visit that have nothing to do with the topic at all. That’s the clever use of predictive marketing in advertising.

2. Cross-selling

Companies are using predictive marketing not only to generate sales but sometimes to increase it. What does that mean? You put an item in your shopping cart, let’s say a phone. Before you pay for it, you are presented with products you might want to buy, such as headphones, a case, or a glass screen protector. This is what it is all about. The company gives you a suggestion of what you might theoretically need.

3. Social media tools

Social media sites like Facebook have sophisticated ad-targeting tools that analyze user behavior. This ensures that ads reach only the potentially interested people. It’s a win-win situation: users get what they want, and businesses pay less for advertising.

What are the benefits of predictive marketing?

Looking at the question directly, the first answer that comes to mind is an increase in sales and therefore profits. This is certainly an important benefit that a company can reap when it starts using predictive marketing, but it is not the only one. There are many other ways that analytics can help your business, from improving customer engagement to boosting your bottom line.

1. Setting priorities

By analyzing customer behavior, you can see which strategies are working and which should be abandoned. It’s also possible to segment customers into groups, set priorities, or even spot trends faster. This allows the marketing or sales team to better manage their activities.

2. Reaching potential customers

Reaching potential customers is quite easy. However, finding those who are ready to become your true customers can be quite a challenge. Predictive marketing makes it much easier. It ensures that ads or mailings only reach the people who are most likely to become customers.

3. Product customization

Customers love to be spoiled and feel that the company understands their needs. It allows companies to target offers and messages based on customer needs and expectations. This way, they don’t waste resources and customers are more engaged.

Threats of predictive marketing

Reading the above description and examples of predictive marketing, you may get the impression that it is an ideal tool. It certainly has many advantages, and if used correctly, it can not only increase your company’s profits but also influence customer loyalty. However, this does not mean that this strategy is completely free of drawbacks.

Keep in mind that while the analysis conducted by specialized tools and the algorithms they use are accurate, they will not always prove to be correct. Marketing strategies are a rather specific matter in which the necessary ingredient for success is the involvement of people. And while it may seem that the study of consumer behavior gives clear results, it may turn out that the results will not coincide with predictions.

A key element of predictive marketing is data. Collecting and analyzing it can be expensive and quite problematic, especially for small businesses. That’s why it is not always a good solution for every problem, sometimes it’s just not cost-effective.

Predictive marketing – summary

Every marketer dreams of a crystal ball that could predict the future. And while such tricks must remain in the dream zone, it is the strategy that comes closest to this dream. In-depth analysis and advanced programs help to predict and understand customer behavior, and thus to choose the company’s future strategies. Keep in mind, however, that interpreting this data and ultimately taking action is still up to you.

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