How AI-Based Marketing Personalization Can Improve Customer Experience

Today’s clients demand that you anticipate their needs and solve their issues. How can marketers accomplish this? By utilizing AI and machine learning marketing platforms. AI and machine learning marketing platforms can predict user behavior in real-time and provide access to a wealth of data that will allow you to delve deeply into your target audience’s motivations.

Brands can use this data to create personalized images, content, promotions, and product recommendations for customers across various channels to increase customer engagement, loyalty, and sales.

Why Is Marketing Personalization Important?

Consumer preferences and behaviors are constantly changing, making the process of individual personalization labor- and time-intensive. However, AI can learn which content is most effective for each customer more quickly and can even deliver it automatically.

AI also opens new avenues for data experimentation, testing, and learning. Businesses can use AI to effectively determine which messages are likely to be well received by their target audience and instantly create hundreds of iterations to test various messages to uncover which ones perform the best for each customer type.

Using artificial intelligence to guide your marketing personalization efforts allows you to provide a great customer experience by showing that you are paying attention to what your customers need. As a result, you’ll be able to build relationships with each customer, increasing satisfaction and promoting brand loyalty. In fact, 97% of marketers witnessed a rise in business outcomes as a result of personalization.

How to Use AI-Based Marketing Personalization

Here are a few examples of how businesses can use AI and machine learning to provide a more personalized user experience.

• Emails: AI and machine learning can assist marketers in predicting the kind of email content that will engage specific individuals under various circumstances by analyzing performance of previous emails tougher and data regarding customer preferences. It can also use automation rules based on historical and real-time data to ensure that emails are sent at the most appropriate time of day for each customer.
• Personal recommendations: AI can analyze user behaviors and site traffic data to make personalized recommendations. For example, AI can recommend displaying a list of products to a customer on the chatbot they open that is based on the customer’s search history. The chatbot can also use the user’s previous queries to display conversational keywords.
• Dynamic websites: AI now makes it possible to create dynamic websites that adapt to individual users, showing them a customized version of your website by using current behavioral signals and previous browsing or purchasing history. You can even use information like popular searches, trending topics, and user location to help you customize the content.

Best Practices for Marketing Personalization

• Don’t rely exclusively on AI: Although AI has made creating personalized content and recommendations easier, marketers must still use their experience to determine how that information can be used to optimize marketing campaigns.
• Follow data compliance guidelines: You must adhere to data protection laws like the GDPR when using customer data. Inform users about the information you’re gathering and why it’s important. Many users will gladly provide you with their information if it means receiving personalized recommendations.

With so many options available to customers, AI-based marketing personalization is becoming more and more essential. AI and a data-driven strategy can help you deliver highly targeted marketing content to your users, keep them interested in your brand, and forecast their future behavior.