Unless you’re a reactionary, as a marketer you probably understand that automation is creating more jobs than it makes redundant.

Automation, for all the scale it enables, requires human mastery of technology, process flows and customer lifecycles.

Increasingly personal communications also entail the creation of more content, to suit each segment and event you identify.

But as much as marketing continues to be a balance of science and art, it seems that automated copywriting software could be about to polarise the world of content.

Read on to find out more, but if you want to improve your own skills (and make sure a robot doesn’t take your job) then book yourself onto our Online Copywriting Course.

Wordsmith

I wrote an article about automation and the need for a human touch. In it, I mentioned Wordsmith, an automated copywriting product developed by Automated Insights.

My assertion was that for all automated copywriting can achieve (sports summaries, financial reports etc), it will never master analogy, inference or humour.

Well, Automated Insights picked up on the article and challenged me to a duel (actually, a conference call).

What their head of comms had to say was interesting. Wordsmith is, in effect, a complex and multi-branched version of mail merge.

So, much like the pathways set up for email automation, a copywriter begins by filling in a large and (potentially) complex template (with as many branches/as much variation as the marketer wants to add).

This template dictates what the content will say dependent on values drawn from a CSV file of structured data.

Raw data is transformed into automated narratives.

Content at scale

The technology is currently in beta, but is due to be available on demand in early 2016.

It’s use is, of course, for writing content at scale, where employing people to do the work is simply too pricey or too slow.

For example:

  • Creating thousands of persuasive product descriptions from standard manufacturer descriptions.
  • Turning workout or lifestyle data into a narrative that’s more enjoyable for users to consume.
  • Creating internal business or performance reports from sales data.
  • Writing press-release style articles about financial results or sports that would previously fall outside of resource.

One interesting example was from healthcare. A company called GreatCall has a family tracking services that allows people to keep track of the location of their elderly parents.

Rather than serving this information to users in a formalised and insensitive manner (GPS, frequency of movement, timings etc), GreatCall uses Wordsmith to create a narrative from the detail.

So raw data becomes ‘X left the house to go to Y, they visited Z and their movement was below average for the week’ (or similar – this is my text). 

wordsmith example

Generative writing 

Before you start to think this is an advert for one piece of technology, let me get to the two most interesting points.

Firstly, at a time when we talk about the changing skillset of marketers, it’s clear that broad functional skills and an ability to quickly adapt to new tech are important.

The idea that generative writing will become an important skill changes the concept of copywriting skills.

The skill in what Wordsmith likes to call ‘data-driven copywriting’ is about being able to add nuance and complexity to the original template. This is more about logic than it is copywriting.

Of course, words are still important, but without that balance between science and art, writers will not be able to get the most out of the platform.

Automated copywriting needs an understanding of spreadsheets and structured data, as much as it needs lyrical verve. 

Quality matters more than ever

So, where does this leave real-life wordsmiths?

Well, there’s no doubt you’re safe in most areas. Crafting long-form content, campaign copy, content marketing, none of this will ever be automated.

But where your role borders the functional, such as writing reports or covering news, you’d better be sure you’re adding value beyond simply structuring data.

Using analytics it’s hopefully fairly easy to prove the relationship between time/effort spent writing (or devising) content and the success of that content (however defined). It won’t always be the case, but hopefully there’ll be a regression – we certainly see this for Econsultancy articles.

If you’re just churning out copy in a perfunctory manner, there’s a robot with a pen waiting to stab you in the back.