The Turing Test is the ultimate test of machine intelligence. Developed by Alan Turing long before the nascent AI we see today, the test involves how well a machine can mimic human responsiveness as measured by another human. In other words, if you’re talking to a machine, can you tell it apart from a human being by its answers?
MARKETING AI® isn’t quite ready to pass the Turing test on its own with a sophisticated conversation, but it’s gotten highly skilled at making the initial introductions, especially with chat-bots. Chat-bots let leads type or speak questions and will then route users’ communications to the appropriate person or spread a social media message. They’re far more than just an answering service, though; they’re intelligent enough to pick up social media followers, anticipate leads’ next questions, send them useful information, and even winnow out unrelated chat from your lead gen process.
The Person at the Other Side of the Screen
Some chat-bots channel prospects to needed information without routing them to a person, and that’s good; if your lead can get answers from a FAQ, article, or white paper, you’ve saved them and your team some time. Eventually, though, all chat-bots should offer access to a person. As good as MARKETING AI has become at communicating, some prospects need a little guidance from you directly. You’ve seen this in action if you’ve ever gone through a customer service phone call by pressing “0” or saying “operator.”
Neural Networks Learn Indiscriminately
Chat-bots on social media are getting smarter all the time, and some of them can sound remarkably human over the short span of a tweet. AI-powered chat-bots on social media are quick learners – and that can be a little scary for the people operating them. A chat-bot readily learns how to sound like the people talking to it, which means it may have trouble at first sorting out what’s relevant. By setting simple linear models as rules for what your chat-bot should address is a good way of keeping it from going on a tangent. Remember, the ultimate goal is to contribute to lead gen with a chat-bot that stays on topic, not one that likes to talk about the weather.
Making Your AI Smarter
Chat-bots should sound personable and intelligent enough to encourage leads to respond, and a simple, mechanical parroting of their actions lacks sufficient engagement to keep them interested. A simple decision tree might be all you need for a chat-bot designed to connect leads to the appropriate department to answer their questions, but if you’re looking for deeper engagement, AI tools that use machine learning to “understand” questions and respond with relevant answers are the right choice.
Today’s chat-bots are useful tools for introducing you and your leads to one another. Tomorrow’s versions may well pass the Turing test on their own. Getting in on the ground floor of chat-bot technology with a MARKETING AI that gives you room to grow is a smart choice.
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