Gender diversity in the creative industry is a topic on everyone’s lips. It hangs in the air on every panel. It sits in on every job interview.

Yet it remains a pervading problem.

A 2018 study by the Department for Digital, Culture, Media & Sport found that the percentage of women working in the creative industry still sits at around 37%. And, according to data gathered by Campaign, just 15% of Creative Directors today are female. 

These figures are quite staggering, and, for women, pretty devastating.

They also call into question how this bias is affecting the kinds of creative content we absorb. What the lack of diversity means for campaigns. How all this impacts what kind of visuals we see or language we read.

Well, the figures right now paint a brutal picture. Women make 85% of purchasing decisions, yet 91% feel advertisers don’t understand them. Evidently this gender bias is felt by both women in the industry and those it’s trying to speak to.

Many approaches have been put forward to solve this problem. And ultimately the solution comes down to hiring more women and encouraging them into leadership positions.

Unfortunately, unavoidably, this will take some time; a whopping 99 years, according to the World Economic Forum.

But I’m a tech writer. And I believe that tech will be the great equaliser in this new decade and, in particular, data-driven technologies.

Here’s how data could be used to tackle the creative industry’s gender bias and ensure campaigns better reflect the way society really looks, thinks and feels. 

Campaigns driven by data insights

The problem with drawing rooms full of men is that they often get what women want from products completely wrong. If you’ve ever stumbled upon the hilarious Bic ‘For Her’ campaign, then you’ll know exactly what I’m talking about.

This is why it’s so crucial to gather and utilise data on your female audience before creating campaigns based on guesswork. Without data to provide objective insights, at best, you’ll be taking a shot in the dark and, at worst, you could alienate and offend your intended audience.

And today it’s not just enough to gather data; you need to ensure the datasets you’re using aren’t biased either. But we’ll touch on that in a moment.

Utilising creative data

Gathering data in order to build personas is one strong approach to creating more diverse campaigns. But there is another kind of data that’s also incredibly powerful: creative data.

Creative data is all the individual creative features that make up a campaign, from the colour present in images to the specific words used. Creative teams can utilise this data by taking note of all these features and seeing if there is a correlation with those features and campaign performance. This gives them powerful insights into what features engage most with an audience, a process we at Datasine call Content Atomisation.

Utilising creative data gives deeper insights into what people want from creative content compared to other methods such as surveys. Using this form of data, creative teams can understand exactly what women want to see from campaigns.

AI could level the playing field, if it’s developed by diverse teams…

In 2016, McCann made history when they unveiled the world’s first artificial intelligence (AI) creative director, a bot called AI-CD β.

While AI-driven creativity is still in its early stages, and considered ‘debatable’ by many, the technology is slowly being adopted by creative teams to automate repetitive tasks, sift through data and even, as in McCann’s case, for ideation.

While it shows huge potential to revolutionise the creative industry and level the gender playing field, there is a risk of bias if developers are not cautious of bias in themselves.

...and trained on-biased datasets

Further to the point, AI needs to be trained on datasets which are not biased.

This need became horribly apparent when an AI created by a team at the University of Virginia began to associate images of shopping and washing with women, and images of shooting with men. Because the machine learning software had been trained on a biased dataset of images, it amplified certain prejudices.

Incidences like these highlight just how, when put in the wrong hands, AI could make gender bias in campaigns even worse. But they also go to show how, if developed by a diverse team who are aware of what could go wrong and work to develop an AI free of bias, the technology could make all the difference in creating diverse campaigns that speak to the wider population.

And, while we’re at it, listening to women

OK so this one’s not strictly data-related, but it’s mission critical. In order for creativity to flourish in the decades to come, we need to work towards having more diverse teams. This means not only hiring more women and BAME individuals but making sure they are listened to as well.

When it comes to creating campaigns that truly move people and hit the right notes, giving the women and minorities on your team a loud voice will be the most important thing you do.