In the war for human attention, Artificial Intelligence is the new sniper. The future of digital marketing is all about personalization and seamless user experiences.
AI offers marketers a golden opportunity to cut through the noise and attract customers at a much more personal level.
To accelerate the adoption of AI in marketing, we’ve identified five key trends that will drastically change how marketers leverage AI to connect with customers in new and innovative ways.
Read on to learn more about these emerging best practices for marketers looking to take full advantage of AI in their day-to-day operations.
Real-Time Consumer Behavior Tracking
The goal of AI-based customer tracking is to help marketers identify high-value prospects and create dynamic customer experiences. AI customer tracking, if executed properly, can identify every action a customer takes and then map that data against the customer’s past behavior.
The point is to track customer activity in real time and create customer profiles that give marketers an in-depth look into each customer’s journey. This can include everything from what content the customer is consuming to where he or she is in the purchase funnel and what emotional and psychological triggers are being appealed to.
This data gives marketers a clear picture of what customers are interested in at any given time and how those customers change over time. This can help marketers create more personalized and dynamic experiences that appeal to customers based on their current moods and desires.
AI-Based Lead Identification and Scoring
Marketers can also use AI to identify potential customers and create dynamic lead-scoring algorithms.
This is a similar concept to what happens behind the scenes at call centers and contact centers, where staff members are routing calls to different departments based on the customer’s needs.
These lead identification and scoring algorithms work in a similar fashion and allow marketers to understand the types of customers who are visiting their sites or reading their content. For example, if someone has been reading about travel destinations, an AI-based scoring algorithm could flag this person as a potential lead for an outdoor adventure excursion.
To create these dynamic scoring algorithms, marketers will feed machine learning algorithms with pre-existing data from their customer bases. This can include things like purchase history, demographic data, and even location data (if the customer has provided it).
Evergreen Content Creation
A lot of marketers have already started to leverage AI’s ability to create evergreen content. With the help of AI, marketers can create a library of content such as blogs and videos that scales well and stays relevant over time.
More importantly, this content can be easily repurposed and tailored to resonate with a wide range of audiences. This is because AI-generated content leverages machine learning algorithms to collect real-time data about the people who are consuming the content.
This data helps AI-generated content continuously evolve and stay relevant to a wide range of people.
Rise of Virtual Assistants
Marketers can leverage AI-powered virtual assistants to help streamline their daily tasks. This includes everything from managing social media marketing campaigns to creating and distributing content.
By integrating AI into existing virtual assistant platforms, marketers can take advantage of more robust AI assistants that are trained to handle more complex activities. This can include things like natural language processing and machine learning.
These assistants can use NLP to understand human language and machine learning to apply that language to specific rules and algorithms. This gives marketers a way to streamline their work while keeping their hands involved in the process.
AI can give marketers the ability to leverage more robust knowledge-based marketing strategies. This can include things like targeted surveys that allow marketers to collect more detailed data from customers. It can also include the use of machine learning algorithms to collect data from social media posts, online reviews, and more.
All of this data can be used to create more robust customer profiles and deliver more personalized experiences. This can be especially helpful for marketers who work in regulated industries or have strict compliance policies in place.
Machine learning algorithms are designed to understand human language and, by extension, the language of compliance policies. This gives marketers a way to collect data about customers without violating compliance policies.
Integration of Mixed Reality and AI
AI is already being used to create virtual experiences for customers. This includes everything from product tours to virtual store walkthroughs and more.
Now, as virtual and augmented reality become more commonplace, marketers can use AI to distribute more robust and immersive experiences. This can include things like personalized product tours or guides that walk customers through insurance policies or financial terms and conditions.
It can also include more robust virtual store walkthroughs that allow customers to interact with products and view them from different angles. This is being done by a number of different companies, including retailers like IKEA and clothing retailers like Thread.
By leveraging AI to create these more robust and immersive experiences, marketers can create more personalized experiences for customers.
While AI-based automation can be helpful, especially in regulated industries, it is not yet commonplace. The technology is still in its early stages and marketers are still figuring out how to leverage it effectively.
However, as AI continues to advance and become more robust, it will become the norm for marketers to use AI-based automation. This can include things like content creation and distribution, social media campaigns, and more.
Generally, Artificial Intelligence will make marketers’ lives easier and free up time for more strategic tasks that require human insight.