You Ask, I Answer: Machines Marketing to Machines?

In today's episode, Annika asks, will humans drop out of the loop with marketing? Will be machines marketing to machines in the future. You know, this is happening to some degree already. In fact, we have been marketing to machines for decades. When you look at the professions, for example, of search engine optimization, you are optimizing not for a human, you are optimizing for a search engine to crawl your page.

Now, thanks to things like deep learning and stuff, uh what appeals to a human and what appeals to a machine have converged much more closely. But in the early days uh of SEO, it was all keyword matching. We used to have uh terrible jokes like uh an SEO expert walked into a bar, tavern pub, uh, stuff like that. So we've been marketing to machines for a while. And no surprise, um, anybody who's been doing any kind of work in machine learning in marketing for the last five years has been using machines to do some of that marketing to machines.

For example, in SEO, using topic modeling to reverse engineer uh the top search results that Google spits out so that you can understand what content needs to be on your pages to potentially rank just as well. That's machines marketing to machines. When you look at social media, social media marketing is humans marketing to humans, but it is also humans marketing to machines. It is also humans trying to understand how the algorithms work. And again, no surprise, using sophisticated data analysis tools, a number of vendors have figured out that uh stuff like time series forecasting and other predictive analytics are an important part of understanding how to market to these algorithms to increase the chances of your posts being seen in the Facebook news feed, for example, or Twitter or Instagram.

So again, machines marketing to machines. Where this is going, no surprise, is with lots of content generation. SEO will see this first, social media will see this probably secondarily. But as we were talking in a recent episode about new advances in pre-trained models like GPT-2778 and um Melnet, humans are really good at creating content in general. I mean, obviously, if you have the intern create all your content, you're gonna get intern-level content.

But for the sake of argument, you know, a mid-career professional is going to create presumably pretty good content. But we scale poorly. Machines are today spitting out mediocre quality content at blistering paces. And as these models, these pre-trained models get better and better and better, we will see that quality of content generated by machines inching up. So going from mediocre to not bad to actually pretty good.

To wow, that's really good. I like that. As we make that evolution, no surprise, at least for SEO purposes, we will be 100% machines marketing to machines where the human will be in the loop insofar as they are quality checking. They are providing some training for an active learning system, saying, like, yes, that was good, no, that was good, spot checking stuff, but the heavy lifting will be done by machines. We are already seeing this to some degree.

Um, for example, in press releases. Press releases are the most templated forms of content there are, right? What's the standard format of a press release? It's it is uh, you know, an introduction of the industry leading company, a quote, uh a key announcement uh where you're proudly uh introducing your you're pleased to announce your your product, right? Uh and then you follow that up with a a random quote by the CEO that the CEO never said, you just have copy and paste something in there.

Um you have information about your product's innovative turnkey solution, you have a quote or testimonial, which again is probably made up, and then you have some contact information, right? That's the template of a press release. Machines already write those. Machines write minor league baseball reports, machines write financial press releases and financial statements because it's so templated that you don't even need AI for that. Um more creative stuff like blog posts, video scripts, and things like that.

Those will become machine generated for the most part, and then humans will be responsible for the quality checking. Will humans ever exit the loop? Probably for low-risk stuff. Again, humans have already exited the loop for things like financial press releases, right? That's low-hanging fruit.

There's no risk. And if your content all sounds the same, it's fine because humans really aren't supposed to be reading it. I mean, I guess they should be, but um, nobody does. Those are released to satisfy uh regulation FD by the SEC, which says that you must publish certain things as public announcements to meet regulatory compliance requirements. As long as you publish the thing, it doesn't matter if another human ever lays eyes on it.

Um, you have done your due diligence to meet that regulatory requirement. So a machine can 100% publish that, and as long as the data is factually accurate, it doesn't even really matter if it's word salad. Um humans will not exit the loop on creative endeavors for quite some time because again, we want to make sure that our models are generating appropriate content. We have seen from past experience, Microsoft Tay comes to mind, uh, that the machines can uh the algorithms and the models can be spiked pretty easily, uh, poisoned. So we will be continually quality checking those, making sure they stay on the rails.

Um. And we can track things like model drift with tools like IBM OpenScale, for example. For the most part, we will stay within the loop on our creative endeavors with machines. On other things like, for example, advanced topic modeling or social media algorithm analysis, you will have the machine the human in the loop far less because again, those are pretty standard statistical operations. Those are not things that require deep inspection.

Humans will look at the outputs, but beyond checking for model drift, humans won't be needed to really dig in there. So machines marketing machines is the present day already, and it will become much more in the of the future as the future rolls around. So good question. Interesting question. If you have follow-up comments, leave them below.

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