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How to Start Using AI for Predictive Marketing

Article • August 18, 2021 • Written by: Diane Keng

Consumers are operating in an increasingly digital world, meaning their behaviors and habits are shifting faster than ever before. With more options at their fingertips, consumers are more likely to shop around for the brands that provide good products and great consumer experiences. That means brands need to curate highly personalized digital consumer experiences to maintain their competitive edge.

What is AI Personalization?

Brands are learning how to use AI in digital marketing to improve ROI and help them achieve their business objectives.

Successful execution of predictive personalization in digital marketing is built on a foundation of data science. That said, most companies aren’t eager to build a full-fledged data science department to help their marketing teams turn raw consumer data into actionable insights – that’s where AI solutions can help. 

AI personalization for digital marketing takes the heavy lifting off of marketers by streamlining the data collection and analysis processes – leaving them free to focus on the bigger picture. This technology isn’t going to completely automate marketing roles, but it’s great for:

  • Recognizing trends and patterns on a massive scale
  • Enabling real-time dynamic content with algorithms
  • Driving consumer behaviors tied to business outcomes, like sales and CRM registrations

How to Get Started With AI-Driven Predictive Personalization

That said, getting started with AI personalization solutions can seem daunting at first. Here’s how to jump right in:

  • Define measurable business goals.

It’s one thing to set a goal of “digital transformation” or “implement predictive personalization.” While those are good high-level goals, it’s really important to have quantifiable, measurable objectives to work towards. AI isn’t a silver bullet – you have to figure out what you want the solution to help you achieve. If your goal is “increase CRM registrations,” the AI algorithms that produce those outcomes are different from the ones that will “improve e-commerce conversion rates'' or “improve engagement with content.” 

Simply put: AI solutions are really good at recognizing patterns in consumer behavior. If someone makes a purchase, for example, AI personalization tools can understand what led the consumer to that purchase and use that information to improve the consumer experience in the future. If you haven’t defined a specific goal, however, you’re likely not going to see the results you’re looking for. 

  • Set benchmarks for progress.

In order to make progress towards those measurable goals, you need to be able to see exactly where you are along the way. When you think of implementing AI and personalization as one singular action, it’s tough to know exactly where you stand. It helps to think of personalization in three separate stages: 

1. Data collection and consumer insights
2. Customer journey optimization
3. Predictive and dynamic personalization

For example, if your data collection practices are in order and you’ve got some actionable insights, you can see that the logical next step is to optimize the consumer journey through simple personalization. If you’re still struggling to figure out how to collect and use your data, though, you know that you need to spend some more time on the first stage of personalization to build a foundation that allows you to move forward.

  • Find a vendor that understands your business.

A vendor can make or break your marketing efforts, especially when it comes to AI and personalization in digital marketing. You need a partner that understands your specific business needs and is aligned with your goals. For example, if you’re ready to move on to enabling simple AI personalization on your website, a vendor that specializes in analytics and A/B testing isn't going to be the best use of your marketing budget. If a vendor can’t produce personalized experiences at scale, they might end up holding your business back in the long run.

Some AI solutions are easy to implement and can start showing results quickly, while others can take six months to integrate and up to a year to start producing ROI. When assessing your vendor, take into consideration the time-to-value as well as how much effort is required to fully integrate their product – the length of the process might surprise you.

Figuring out how to use AI in digital marketing can seem intimidating, but the reality is that you don’t have to have everything figured out from the start. If you want to keep up with consumer behaviors and maintain your competitive edge, it’s time to start using AI to create personalized digital consumer experiences. 

If you’re ready to see what Breinify has to offer, contact us to learn more or get started!

Ready to transform your digital personalization with incredible speed?

Diane Keng

CEO & Co-Founder @ Breinify
Forbes 30 Under 30 for Enterprise Technology