INTRODUCTION TO PREDICTIVE MARKETING ANALYTICS

Predictive Marketing is the process, tools, and rules for applying predictive analytics to making marketing and sales decisions. The objective of Predictive Marketing is to anticipate which marketing and sales actions will most likely lead to the desired customer behaviour and to carry out those actions.

Predictive Marketing is not a replacement for more traditional marketing approaches. Marketing and sales decisions will continue to be based mostly on product releases, inspirational ideas, what competitors and peers are doing, and what has worked well in the past. What Predictive Marketing will do is supplement traditional marketing with a new, more analytical method of sorting and prioritising marketing and sales actions.

One of the key aspects of Predictive Marketing is Predictive Marketing Analytics (PMA), which involves using historical customer data to predict future outcomes and trends. For example, PMA can tell you which accounts to target for churn prevention and which leads are most likely to become customers and are, thus, most worth pursuing. PMA is typically and predominantly done using computer algorithms (e.g., Machine Learning).

pma enGraphic 1: Predictive Marketing Analytics Process

During the last five years, the majority of B2C companies have started utilising Predictive Marketing Analytics. But PMA is really nothing new. The individual methods and formulas have been around for almost fifty years. So what is behind its recent growth in popularity? The explanation is that three critical enablers have simultaneously matured to the point at which PMA has become easily accessible to almost any company.

  1. Marketing Clouds and CRM-centric sales generate a massive amount of behavioural data. These include sales interactions, digital customer engagement, social media, loyalty (e.g. Net Promoter System), support, etc.
  2. Data extraction has become easier and cheaper. Just a few years ago, it took weeks or even months to extract, transform, and load data for analytics. Modern martech applications make data extraction simple and easy to automate using data integration tools like Frends.
  3. Computing costs have plummeted. Machine learning requires a massive amount of computing power. This used to be very expensive. With cloud computing more or less following Moore’s law, the cost of storing and processing data has fallen drastically.

Predictive Marketing Analytics isn’t an absolute science. Like traditional marketing, it is some combination of art, intuition, and science. But it does provide companies with the ability to more reliably forecast customer behaviour.

Thanks for the Photo Stefan Steinbauer on Unsplash

Do check out

Learn what ABM is – and why it’s getting so much attention.

Hello!

SUBSCRIBE NOW.

1 email a month, EXCLUSIVE stories, and 10 minutes of your time.

Subscribe now

MORE RELEVANT STORIES ON

Custom Media Shines at Campaign Asia Awards: A Double Win!

We’re thrilled to celebrate Custom Media’s achievements at the Campaign Asia Awards, where they secured Silver for Content Marketing and Bronze for B2B Marketing.

READ MORE

Highly creative ads are four times more profitable than low creative quality ads

WARC's Imaad Ahmed reveals how creativity and long-term brand building can transform B2B marketing success. Explore why emotional advertising, distinctive campaigns, and a customer promise are key to effective marketing.

READ MORE




Innovation Boom: Why B2B Marketing should now focus on architectures instead of actions

In a fast-paced digital world, B2B marketing needs more than short-term actions. Discover how marketing architectures provide the flexibility to adapt and thrive amidst AI innovations and content overload.

READ MORE

BBN International Expands Global Reach with New Partners

BBN expands in Asia Pacific with Brew Interactive and Custom Media joining the partnership, enhancing global B2B marketing services in the region.

READ MORE
Translate
Share via
Copy link