More and more, the various forms of artificial intelligence are finding a home in the marketing department of all kinds of companies. AI has proven itself capable of understanding customer needs and matching them to products or services. In this article, Christopher Lee, Marketing Manager at WNY Holdings LLC, offers insight into how AI is helping marketers be more effective.
Because the term artificial intelligence, commonly referred to as AI, has become somewhat of an overused buzzword, it is often helpful to begin any discussion of AI with a quick high-level definition of the relevant terms. It is readily apparent from reading popular media accounts detailing the nearly miraculous abilities of AI that some explanation is needed.
AI is, generally speaking, any intelligence demonstrated by a machine rather than a human or animal. Or, more precisely, a system that perceives its environment and takes actions that maximize its chance of achieving its goals.
Given this broad definition of AI, the telephone answering the machine, invented during the first half of the last century, has the characteristics of artificial intelligence. It can perceive an incoming call and take action to achieve its goal of recording the caller’s voice.
More germane to how AI can help marketers become more efficient is IBM’s more recent definition of AI, “Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.”
Two types of AI that find valuable applications in marketing are task automation and machine learning.
Task Automation
AI task automation applications perform repetitive tasks that require low levels of intelligence. They follow a clearly defined set of rules and execute a predetermined sequence of operations. Commonly these applications are used to enhance the capabilities of human workers.
For example, suppose a marketing department wants to send a welcome email to each new customer. In that case, an AI task automation application could efficiently perform that task and free up humans for more complex jobs.
Rudimentary chatbots found on many websites can also be task automation applications. They monitor a customer’s text inputs watching for certain words such as the name of a product, service, or other terms from a predetermined list. When the customer types in one of those words, the chatbot responds with a prewritten “canned” response directing the user to a specific page on the site, for example.
More sophisticated chatbots use machine learning to understand the customer’s needs.
Machine Learning
Modern marketing departments use AI for much more than simple task automation, such as digesting and processing large quantities of data. These intelligent systems learn to predict a customer’s behavior and respond with tailor-made promotions or purchasing suggestions.
These advanced applications can, over time, predict what marketing content will yield the best results, create the most relevant social media posts, and drive programmatic buying of online advertising.
Natural language processing (NLP) technologies arm sophisticated chatbots with the ability to carry on a conversation with customers that is nearly indiscernible from that of human-to-human communication.
A chatbot can escort a customer around a website, acting as a personal shopping assistant. Asking questions as they go, the AI system can gather information to make relevant suggestions. NLP will recognize when the customer is distracted, frustrated, or not interested in the tips offered.
A Diet of More Data
Just as human workers need the sustenance of food to thrive and grow, AI systems require more and more data. The more data your machine learning application has access to, the better it will perform. It needs data about each individual customer and access to big data about customers generally.
In a world where data is the new currency of business, AI’s dependence on data can be problematic. Customers are increasingly wary of applications that ask too many questions or seem overly eager to consume their personal information. More regulations restrict and govern how much and what information marketers can collect and share.
Conclusion
Artificial intelligence is particularly well suited for work in the marketing department. AI has been described as approximating the ability for marketers to assign each website visitor a shopping assistant with nothing to do but help only that person. The digital guide will then forever remember what it has learned about the customer, what they like and dislike, and then follow them around the internet, learning even more.
Even with restrictions placed on personally identifiable information (PII), big data aggregators find innovative ways to make enormous amounts of data available to AI applications.
The future of marketing will undeniably belong to those that build systems around AI capabilities.
About Christopher Lee
Christopher Lee is the Marketing Manager at WNY Holdings LLC, a customer-focused digital marketing company that started in 2018 to provide tailored marketing strategies for small businesses. Christopher Lee assists clients with all their digital marketing needs, from content marketing, web, and graphic design, media creation, SEO, all the way to Facebook advertising.
