Can AI Replace Our Content Marketeers?

Sven Verleun
> 5 min
|
May 9, 2019
Content marketing is becoming a more crucial marketing strategy by the day. Its revenues are projected to grow at a 14.4 percent compound annual growth rate, so here at Dashmote we started wondering: can we become more effective in our content production?

Could we, for example, replace our content marketeers with a machine? It turns out the short answer is yes, and it lies on the acronym NLG.

NLG stands for Natural Language Generation. It’s a software process that automatically transforms data into written text. Feed the algorithm with data, and it will put out a story like the one in the GIF below - it comes from a 2019 release by OpenAI.




How does NLG work?

The functioning of NLG is fairly simple in its intricacy. It could be compared to the process humans use when they turn ideas into writing or speech. An algorithm extracts data from a variety of sources to produce naturally worded prose that can be used for the most different purposes.

Commercial uses of this technology date back to the early nineties, when it started being used for weather forecasts. The earliest of such systems to be deployed was FoG, used by Environment Canada to generate weather forecasts in French and English.

Over time then, NLG has been extensively implemented and experimented. Outlets such as The New York Times, Associated Press, Reuters, and The Washington Post have already utilized AI to generate content. Forbes mentioned that the Press Association alone is currently producing 30,000 local news stories generated by AI.

What are the potentialities of AI-generated content?

It’s easy to imagine a bright future might lie ahead, for a content marketing that will rely more and more on NLG and similar technologies.

First of all, they are scalable. As NLG improves in quality, its quantity can increase exponentially. Once a machine is taught to help efficiently with content marketing operations, and once a good algorithm is developed, we can fully open the proverbial Pandora’s box.

At this very moment, NLG is used for things like worldwide: customer service, crafting equity research report (which is what the German bank Commerzbank does), being implemented in data-driven decision making workflows, and, as exemplified by the example above, being used by newspapers - especially for fact-checking and sports reports. The list of examples could go on and on an on.

Where the limit of AI for content marketing lies

Let’s play a game! Take this New York Times quiz that will challenge you to tell the differences between computer-generated stories and those that were written by NYT journalists. Do the test and come back here!

If you did the test, you will know your skills are far from being replaced. It might sound corny, but although the AI-generated content is impressive, it lacks creativity and sensitivity, which are two essential skills necessary for putting together an enticing story.

Some steps have been taken, that’s true. For example, a Japanese team competed for a national literary prize with an AI-written novel. And yet, decisions regarding the plot were made by the human part of the team. In addition, the team also prepared some sentences from which the machine was able to take off.

It’s perhaps too soon for NLG in content marketing

So, wrapping it up, if the short answer to our question is yes, the long answer is “yes, but…”. Yes, we could replace our content marketeers with a machine, but we would be deprived of their amazing creative qualities.

Content marketing is a profitable marketing strategy, and it will profit from NLG - that goes without saying. It’s important for marketeers to take that into account, but creative campaigns still rely on a high level of personal knowledge and creativity to be implemented.

So, if you’re thinking of joining our crew, check our job openings because we’ll still be searching for talented people in the times to come!

About Dashmote

Dashmote is an AI technology scale-up headquartered in Amsterdam, The Netherlands. With the goal of bridging the gap between images and data, we are working to bring AI-based solutions to marketers for clients like Heineken, Unilever, Philips, L’Oreal, and Coca-Cola. We add value in areas such as Location Analysis, Trends Analysis, and Marketing Intelligence. Doing so on a global level, our company today has offices in Amsterdam, Shanghai, Vienna, and New York.

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