Artificial Intelligence Marketing and its Drawbacks
In the past two posts I have gone in depth on what artificial intelligence is and how it is used in marketing. In my very last post I chose a specific example on how it is implemented in real life in the healthcare industry. For this post on artificial intelligence in marketing I will talk about its current drawbacks and areas of needed improvement.
The main umbrella of issues with artificial intelligence is that "Most marketers assume artificial intelligence knows more than it thinks, but it still thinks more than it knows — and marketers know more than they think." This mindset exists because AI is doing so much busy work, tedious tasks, and analyzing so much data at one time.
James O'Connor, Director of Marketing at Go Solar Group, a residential solar company says that learning how to implement AI in marketing and how to use it is completely different than having to actual learn marketing skills. One can theorize that access to AI makes critical thinking to employees less prevalent. There is a balance to thinking critically on your own and finding ways to mastering technology to fully maximize ones fullest potential. In Mr. O'Connors experience their are certain failures with marketing platforms have taught him a few lessons.
AI helps business process data about your audience. It does not understand your business model or the industry you work in. This holds very true in areas of work that have a lot of competition, do not generate repeat customers, and target specific locations. This exists because of the embedded marketing platform in certain types of AI. You can't assume that AI can think critically about your company’s industry and business model. For example you James O'Connor used Facebook to make lookalike audiences on for more than 20 campaigns be he included his installed customers. The algorithm didn't think critically enough to take out the existing customers even though they were already dealt bossiness too. This results in generating leads that may be already installed.
Embedded platforms in AI can interfere with personal work. The embedded ads that are implemented into the platform. Therefore competing interests between marketers and platform profits are escalated. Search engines like google implement paid per click advertising. Without platform knowledge, interfaces such as the ads, make overcoming competing interests between clicks and leads a challenge. Additionally dynamic keyword insertion is a compiles clicks that don't turn to leads, since the platforms aren’t routes to the engines. They don't understand the context of the ads. You must be able to go past competing interests.
Lastly AI makes people lazy. It gives people an excuse. Marketers forgo the creativity that they were taught to implement into the workplace. Relying to much on AI can be dangerous and will continue to get worse once it can generate more context to certain things such as creating images based off of titles and context. Things like creativity can't be forgotten about because creativity is what reminds the consumer that you are thinking about them at targeting them. Algorithms don't do that. People do.