If you’re a marketer, you probably aren’t too concerned about what’s “under the hood” of the martech tools you’ve adopted. You want it to be easy to use, and able to drive the results you expect – whether its creating and deploying offers, increasing engagement or improving sales.
Today, though, artificial intelligence (AI) and machine learning (ML) are all the rage, and everyone is touting how these technologies make their solution a game changer.
But do you truly know what AI and ML is? Or are you being caught up in the buzz about what you should have, even if you’re not sure what it is and how it works?
Not sure? We’ve put together this primer to help you gain a basic understanding of AI and ML, how they work together, and why it’s important to distinguish between the two when you’re evaluating new marketing technologies.
AI is sometimes referred to as machine intelligence, since it can be loosely understood as incorporating human intelligence into machines. Machines are considered “intelligent” if they can complete tasks based on a set of problem-solving rules, or algorithms. As a result, artificial intelligence is a very broad concept that can range from “Good Old-Fashioned AI” to futuristic technologies like deep learning.
Many marketing platforms claim to use AI. But in reality, what AI actually is to them can vary greatly – from a simple algorithm, search capability or chatbot to something more sophisticated, complex and powerful.
Machine learning is a subset of, and a technique for realizing, AI. With ML, a computer is empowered with the ability to learn through a method of training algorithms to make decisions. This training requires massive amounts of data, in which the algorithm can keep learning more and more about the information it processes.
ML is an absolute necessity for brands interested in designing highly personalized offerings. ML enables processing of vast amounts of data, from info collected by the data science and IT teams, to sales, customer service and customer loyalty sources. So, instead of programming a specific set of instructions, the software is “trained” as it takes in all this information, and continues to “learn” as more data is added. This is ideal for marketing applications, in which the machine can evaluate customers interactions in real time, and enable marketers gain better insights into each individual so they can tweak offers to get better results.
These unique capabilities make ML essential if you’re trying to go beyond segmentation and microsegmentation marketing to achieve true 1:1 personalization. ML-enabled solutions can help you deliver the right offer to each customer, at just the right moment.
This kind of personalization is often a big challenge for marketers because offer creation has long been a manual process that cannot scale to address hundreds of thousands, or even millions, of customers. ML assists in automating the process so that 1:1 offers can be achieved, even at some of the largest brands.
Integrating ML into your marketing toolbox can help you automate processes, such as identifying relationships between disparate data. Then, as more data is gathered with every customer interaction, ML gets smarter, enabling you to quickly test and analyze alternatives, and fine-tune offers to deliver the most impactful customer journey to each person.
If you’d like to learn more about AI and ML in marketing, and how they can help you deliver effective personalized offers more quickly, download our new white paper, “Bridging the Gap Between Data Science and Marketing: How to Achieve Personalization at Scale with AI and ML.”
Artificial intelligence and machine learning are an absolute must for brands interested in designing highly personalized offerings. AI enables the processing of large amounts of data collected from IT teams, sales, and customer service. AI algorithms are trained as it takes in all this information, and continues to “learn” as more data is added. This way marketers gain better insights into each individual so they can tweak offers to get better results.
10 Artificial Intelligence Marketing Tools Driving the AI Revolution
Marketers can now use AI-based tools to analyze customer data and ultimately design and deploy highly personalized offers that customers find appealing. This article reviews 10 cutting edge AI marketing tools that can improve your results.
Understanding Machine Learning for Marketing
Machine learning enables companies to collect insights on customers’ preferences and determine what they will do next. These insights can help understand if some is likely to leave your website to look for a better deal elsewhere, or if they are a candidate for conversion, then react accordingly.
Read more: Understanding Machine Learning for Marketing
We have authored in-depth guides on several other hyper-personalization topics that can also be useful as you explore the world of AI for marketing.
Learn how one-to-one marketing can impact marketing effectiveness and your bottom line, and how brands are scaling personalization across digital channels.
See top articles in our one-to-one marketing guide:
Today, marketing is not just about customer acquisition but also retaining your biggest fans. And the best way is to increase customer loyalty through a loyalty program.
See top articles in our customer loyalty guide:
Learn about the importance of customer engagement, and get practical advice to build a customer engagement strategy that transforms customers into fans.
See top articles in our customer engagement guide:
Traditional types of customer segmentation fall short on many accounts. Learn how AI and ML can personalize offers with the best combination of incentives.
See top articles in our customer segmentation guide: