Predicting the Future Thanks to Predictive Marketing

Although this marketing technique might sound futuristic, it dates back to 1930. Back then, predictive analytics enabled mathematicians and computers to calculate and analyse the possible successes, failures and results of multiple scenarios (e.g. weather conditions). At the start of the 21st century, companies and brands started to leverage predictive analytics and marketing technology to predict their customer’s future behaviour. They started by carefully analysing their historical customer data to predict which marketing actions were more likely to succeed and which were more likely to fail.

In short, predictive marketing specialists gather data about your business from several sources, which they then analyse alongside the company’s marketing data. Then, they inject this large pool of data into a predictive model that matches your business and predicts the success of your marketing activities. To optimise predictive marketing, companies and brands must combine existing customer data with third-party data that will allow them to understand evolving customer habits.

Predictive Product Suggestions 

A widely used predictive marketing tactic in the e-commerce industry is predictive product suggestions. In short, it’s suggesting products to consumers based on product interests and purchase history to significantly boost revenues, CTRs, conversions, and other KPI’s.

Special algorithms on e-commerce sites continuously collect data about prospects’ product interests based on what they viewed or purchased from them. Then, the data is used to predict which products are most likely to be bought next. Finally, this data is collected and put into the e-commerce ad or promotion the prospect sees. So, instead of presenting the same ad or product to every prospect, predictive marketing tools help to direct customers to products they desire.

Predictive SEO Tactics 

As marketers, a (big or small) part of our job involves creating online content aimed to attract and convert audiences. Since search engines provide significant traffic wins and brand awareness, producing valuable content on page one is vital.

However, getting to the top is one thing but staying there is another. Landing your high search result page position and the accompanying organic traffic will allow you to use predictive data to prevent the future loss of your ranking and all the traffic that comes with it. 

This tactic, also known as predictive SEO, is applied by content strategists who use traffic and search ranking analytics to determine if a web page is at risk of losing its traffic momentum.

Customer Churn Prevention 

It’s hard to tell when customers need new content or when they’re likely to churn. But, thanks to predictive analytics and well-crafted marketing strategies, companies can now identify and re-engage customers that are close to churning.

• While your business might not implement complex customer churn prediction tools, data can be used in different ways to predict and prevent lost audiences. For instance, by tracking email engagement data and identifying contacts that are less likely to open or click on emails, you can create a segment of contacts that are at-risk of unsubscribing. That segment can then be triggered by sending re-engagement emails.

Implementing a predictive marketing strategy requires time, effort and money. However, if done correctly, the desired results follow quickly. Here’s an overview of the pitfalls and benefits.

Pros

• Allows for a better understanding of customer behaviour.
• Can help companies make decisions in marketing budget management, planning of marketing campaigns, lead generation, and conversion strategies.
• Paves the way for more personalized responses to an audience, which leads to far better retention.

Cons

• It’s not always accurate: the fact that marketing strategies rely on human engagement to succeed can cause a prediction to be wrong.
• It can be pricey: predictive tools and predictive marketing projects that require analysing large amounts of data can get costly.
• It requires data: collecting, cleaning, and organizing data properly so that predictive tools or algorithms can leverage it is time consuming and should be built into your predictive strategy.

Predictive marketing can prove to be very useful regardless of the industry. By combining business and consumer data sets with predictive models, you can identify emerging opportunities. In addition, with expanded data assets, predictive marketing can help deliver personalised customer experiences. In a nutshell, a marketing technique worth taking a look at.

4P square has the right talent to help you set up, optimize and manage your marketing assets. Don’t hesitate to reach out and see what we can do for you!

Emmanuel Liebaert is a quinti-lingual (NL, FR, ENG, SPA, POR) marketing consultant with a rich international background. His adventurous spirit and love for marketing has taken him all around the world. During his early 20’s he lived and worked in Spain, Portugal, and Colombia. His areas of expertise are brand management, content marketing, and strategic marketing. He approaches every marketing project the same way he approaches his day-to-day life: with passion and commitment.