3 Ways to Get Started Using AI for Predictive Marketing

The consumer goods industry is experiencing rapid transformation. Consumers have been shopping and engaging with brands more and more online, but the pandemic turned the push for excellent digital experiences into a full-on shove. For brands to gain a competitive advantage with consumers, it's important to deliver highly personalized experiences in a subtle way — without consumers feeling like their privacy has been violated.

Brands are increasingly leveraging data to inform personalization in digital marketing, but they run into challenges. This is because data science capabilities are required, whereby collecting, organizing, and analyzing data is a holistic process instead of just a means to an end. How can you get those valuable, predictive insights?

AI for Personalization in Digital Marketing

Building an internal team of data scientists who turn data into accurate, actionable insights for predictive marketing is one option to overcome difficulties in data collection and management. The problem with this strategy is that most companies don’t have teams dedicated to using data science in digital marketing, and building them takes too much time because professionals trained in data science are in high demand and short supply.

This is where AI marketing tools can fill the gaps. Predictive AI can help you deliver dynamic digital experiences in real-time using data. This allows you to be proactive instead of reactive to changing user behavior and trends. Predictive personalization tools use algorithms to predict user behavior. They allow you to test content, layouts, and other aspects of your channels and campaigns more frequently with larger sample sizes and maximum results with minimal risk.

AI can also identify trends invisible to humans, which is crucial for anticipating consumer demand early and ensuring that you don't miss opportunities. Because of its ROI, AI isn’t just an alternative to data scientists; it could be an improvement.

Using AI for predictive marketing may present some challenges, but here's how you can get started easily:

1. Understand Your Objectives

“Implement AI” can’t be the only objective. You must clearly understand and define the problems you’re trying to solve for your customers and team with AI marketing tools and the business objectives behind your decision.

A common business objective is to increase engagement, but when you dig deeper, you can come up with more specific goals like increasing page views, CRM registrations on loyalty pages, or conversion rates for e-commerce. Strive for quantifiable objectives so you can measure progress and ROI easily.
Also, consider including internal objectives focused on how new AI marketing tools will save time and increase efficiency for your team. For example, reducing the time spent on segmentation or A/B testing are great internal goals. Ultimately, determining why you want to employ AI will help you identify how best to do it.

2. Pinpoint Your Progress

Personalization in digital marketing can be broken down into three stages: data collection and insights, customer journey optimization, and predictive and dynamic personalization. It’s important to identify your brand or company's current stage to know where to focus your efforts.

If your company is already collecting and storing data effectively, then focus on identifying actionable insights and delivering simple personalization for content or dynamic segmentation that optimizes customer journeys.

3. Pick the Right Vendor

There are many aspects to consider when deciding on a vendor, but in general, you want a partner that can integrate quickly, provide the technical support necessary to get the solution up and running, and help you see results fast. Think about how powerful the technology itself is and what it can do for you — does it offer smart segmentation, 1:1 personalization, and scalability? Determine the gaps in your campaigns, and choose a tool to fill them.

It’s important for brands to get started with AI in marketing sooner rather than later to keep pace with consumers. Adopting this technology and embracing predictive marketing can feel like a leap into the unknown. But it’s a necessary step forward — and with the right strategy, it’s a step you should take confidently.

Diane Keng is the CEO and co-founder of Breinify, a plug-and-play AI platform for predicting and acting on customers’ highly dynamic interests.