Sales Force Automation for FMCG Industries

How to Use AI in Marketing: 3 Ways to Improve Your Customer Journeys

The marketing landscape is changing, and artificial intelligence is at the forefront of this change. Customer expectations are growing and the demand for a one-to-one personalized experience has taken center stage. As these changes are happening, many marketers are turning to artificial intelligence to supplement and enhance their marketing strategies.

If you’re just getting started with AI marketing or looking to enhance the strategies you already have in place, this ultimate guide to AI marketing will help you dive further into the intricacies of using artificial intelligence in marketing.

Three ways that AI can truly revolutionize the online buying and e-commerce experience for YOUR end consumer.

1. Personalized Product Recommendations

AI systems can’t yet build your website from scratch, but machine learning applications are able to improve your website visitors’ experience in a multitude of personalized ways. Algorithms are able to digest complex customer data and provide relevant content to individuals at the right time. With AI, you can improve:

  • The browsing experience. AI scales the processing of every piece of customer data (location, demographics, device, pages viewed, products browsed, items clicked, time spent on a page, etc.) to offer content (products) that are most likely to interest and entice each user
  • Entry/exit intent. Instead of prompting users with run-of-the-mill exit intent overlays, you can personalize your pop-ups to be incredibly relevant per the individual. You can also ensure content within specific web widgets matches what contacts see elsewhere, like in an email.

2. Use AI to connect with your customers on their terms

More detailed audience segmentation is a great start, but as a marketer, you also need to deliver the right message, on the right channel, at the ideal time — whether that’s mobile, email, desktop or laptop, or social media. AI can help you identify the perfect messages, volume, and channels to keep your customers engaged. 

By analyzing the number of messages you send to your customers against relative engagement rates, you can begin to paint a picture of how your audience prefers to interact with your content. For instance, some audiences just won’t engage with certain channels at all. AI can help you predict this, so someone who is unlikely to open an email can be reached with a social ad or mobile push message instead. The same can be done with send-time optimization to reach your customers when they’re most likely to pay attention.

 

3. Automating the gathering and analysis of customer data

How much time and resources are you currently taking to collect, organize, analyze, and draw actionable insights from all your customer data? You probably cringe at the thought of answering that.

Most retail and consumer brands with hundreds of thousands of customer records have at least a person or two if not entire teams dedicated to data management. Unfortunately, these tasks too often fall in the lap of the creators, the copywriters, the artists — the marketers.

Instead, what if you could leverage (and by leverage, I mean trust and rely upon) machine learning systems to read and recognize behavioral patterns to draw marketing insights with the snap of a finger?

With both time and quality data, this kind of automated analysis is possible. You can begin to take a hands-off approach to data analysis, segmentation, and campaign execution, and let the machine devise specific communication plans for individuals based on what it knows about them.

Advanced AI systems can even build customer personas (e.g. “look-alike” audience targeting) based on multiple data points like location, website interaction, referral source, purchase history, and more.

Author

Harshul Aggarwal