The application of Artificial Intelligence (AI) is a topic that is being vigorously focused on by a multitude of industries. These range from financial services deploying AI based chatbots, to entertainment services like Netflix™, which use AI to predict and suggest what viewers may want to watch next. For marketers, the question arises: How will the rise of AI affect their industry?
As with all new technologies, AI is a topic that has fallen prey to being massively overhyped. That, however, does not make it any less useful or innovative. In fact, often all the hype that accompanies an exciting technology allows for markets to be tested and for the most practical use cases to emerge.
Leadify’s CEO, Grant Fleming unpacks what AI means in terms of marketing your business and explains why it’s not likely that it will ever replace direct marketing.
1. You must firstly ask yourself, is it the real deal?
It is essential to define what AI means in the direct marketing context and separate that from machine learning. In fact, we are nowhere near true AI; we have some automation and machine learning processes. Thus, those who are punting AI in marketing automation don’t know what they are talking about and are just using buzzwords.
Even as true AI, and quantum computers that could solve humanity’s pressing problems in minutes, are still on the horizon, machine learning holds the more immediate promise to truly impact on marketing.
More particularly, according to a recent report by Forrester, all indications are that one of the more viable benefits of machine learning will be enabling marketers to improve on customer experiences and support. Additionally, in the short term, leveraging machine learning will enhance existing products and services, as well as streamline processes.
2. Rise of machine learning
Such applications are available now. Leadify already integrates machine learning to assist with handling Exclusion criteria. This ensures that contacts that have already been marketed to in a previously defined period are not sent campaigns one after another.
Another important aspect is on our delivery failure prevention strategies, where the system works out the probability that a marketing message will be delivered to a particular contact, or not. If the probability is low, based on certain previous delivery criteria, then the message to that contact is not queued. This saves the wasted marketing cost.
Beyond machine learning helping marketers do their jobs more efficiently, the necessity of the human touch should not be diminished, as there are certain functions that are easy for people to perform but difficult for a machine to replicate. A key example is a marketer’s ability to understand customers from an insights perspective. Furthermore, campaign managers and analysts can readily be at coal face of the campaign, in contact with customers, even as all the automation is done via the platform. In short, the value of human interaction can’t be replaced by a machine.
Related: Direct Marketing: Permission is Key
3. Here to stay, but not to rule
Already we are seeing this with chatbots, in which an artificial intelligence program leads customers up to a certain point when buying insurance for example. When the chatbot reaches the limit of what its algorithms can accommodate, customers are handed off to a real salesperson to complete the transaction.
In other words, it looks like machine learning is intended to handle the grunt work, rather than rendering their makers irrelevant. Additionally, people are generally more comfortable interacting with other people.
But what about the future? Should marketers be leery of AI replacing their current practices? I do not believe so. There is a practical consideration that makes it unlikely AI will overshadow direct marketing anytime soon – cost. The initial implementation of AI will likely not be cheap, at least not from the outset. This then will likely compel organisations to balance cost versus utility when considering whether to use AI for mass market direct marketing automation.
Ultimately, the value of AI/machine learning will ultimately be measured against the bottom line. After all, if AI can improve response rates by 50% but also increases costs by 200%, its worth will quickly come into question.
All this bodes well for how AI, even as it becomes more sophisticated, will likely be employed. As marketer’s servants and assistants, not our overlords.