The business world is abuzz with the emergence of user-friendly Artificial Intelligence (AI) tools like ChatGPT and Dall-E 2. Capitalizing on this trend, many companies are now touting their products’ new AI features and functions. Some are truly remarkable, and some are just false advertising of our old friend Machine Learning (ML). But how can you tell the two apart?
First, understand that ML focuses on developing algorithms and models that enable computers to learn and make predictions or decisions. ML algorithms learn from data, recognize patterns, and make predictions or take actions based on the patterns identified. Furthermore, ML algorithms can improve their performance over time by learning from new data.
A classic example in the MarTech space is send time optimization for your outbound marketing communications – a feature that has been in ESP playbooks for years (article from 2009).
Based on a consumer’s email reading habits (AM vs PM, Monday vs Thursday, etc.) ML can predict the best day of the week and time, per individual, to send an email so that it has the highest probability of being read.
You can also find ML enabling MarTech with the creation of “Look alike” social audience segmentations, dynamic pricing based demand and inventory, and fraud detection.
AI, on the other hand, is a bit more sophisticated. It involves creating systems or algorithms that possess the ability to perform tasks or exhibit behavior that typically require human intelligence. AI encompasses a range of techniques, approaches, and technologies aimed at enabling machines to understand, reason, learn, and adapt in order to achieve specific goals. From a MarTech perspective, this involves leveraging data-driven insights, enhancing customer experiences, streamlining processes, and optimizing marketing campaigns for better results and ROI.
One familiar example of AI in marketing is the use of AI-powered chatbots and virtual assistants. These intelligent systems provide real-time customer support, answer queries, and assist with purchasing decisions. Chatbots engage in personalized conversations, handle repetitive tasks, and deliver round-the-clock customer service, resulting in improved satisfaction and cost reduction.
Furthermore, you’ll find AI facilitating personalized content creation based on user behaviors and their intent, identify relevant audience segments and selecting the best ad placements while adjusting bids in real-time, and the ability to fulfill marketer requests using natural language processing (create subject lines, audience groups, new reports, etc.).
As we wrap up, we hope you now see that while AI may leverage ML techniques in its decision-making process, ML alone does not constitute AI. And comparing the two is akin to comparing a thesaurus to The Great Gatsby!
Feel free to send to a friend or tell us we’re wrong…or better yet, check with ChatGPT first!