Since the beginning of time, men have been asking themselves what women want. Despite their best efforts, it’s often been a frustrating series of fumble-in-the-dark tries and mind-reading exercises, none of which lead to the elusive answer.

Big questions arise from this one question. How do you find out what women want? Where can this information be had? And once you know what women want – what do you do about it?

Big questions like these are starting to lead to one place – Big Data.

It might seem, looking at glossy ads targeted at women, that advertisers have all the answers and reside inside women’s heads. But the truth is: Ad men, too, are at the mercy of Big Data. The “Mad Men ad men” actually have to turn to the “Math Men,” who have the tools to capture what women want.

Yes, scoff all you like – but the math men with their tech tools and sophisticated algorithms have figured it out.

How has this shift taken place? Women, like most of the world, have gone online to do virtually everything – to shop, communicate, keep up on news, conduct research, learn.

The online realm is the tech guru’s playground, giving math men all the data they needed to get the upper hand – both in terms of knowing what women want and in the ability to teach everyone else how to give women what they want.

The techies have Big Data and aren’t afraid to use it.

Finding out what women want means gathering raw data about their online activities, analysing that behaviour to gain insight to better predict their wants, and then targeting them accordingly.

This is what Big Data enables – and where the age-old questions start to get answered.

It’s a generalisation to say “tech gurus” have this information at their fingertips. Until recently only a few big industry players, such as Google and Amazon, took advantage of the power of Big Data for their own ends, leaving most others in the dark. 

The competitive advantage of being able to use audience data in this way is obvious; these companies have dominated online advertising and e-commerce as a result, serving targeted ads and content/product recommendations to users by tapping into the collected data at their disposal.

Given the same power to leverage user data, though, other companies — like publishers — would be able to gain ground in online advertising, recapture much of the audience lost in the shift to digital media and find new ways to build meaningful connections with their audience(s). 

The big players, though, have hit only the tip of the iceberg in terms of what’s possible. Why? There is a big difference between ads and content targeted only by demographics and relevant, contextual ads and recommendations that take into account user interest and intent.

The way the big players have done it, there are too many intermediaries between the publisher and advertiser. So the user data has not been examined at a level granular enough to create robust individual profiles and, perhaps most importantly, context has not been considered.

Without these keys to relevance, ads and recommendations are little more than assumptions. No rational person should assume that all women, by virtue of being female, are the right target audience for weight-loss programmes or new age beauty treatments.

Context and control of content are the next big steps in Big Data analytics – and in delivering what women, or anyone for that matter, really want. Big Data is unique in that it allows for 360-degree consumer insight when the right solutions are in place.  

An example of this is a leading Spanish news publisher that wanted to target individual users and drive them to paid content promotions. We recently partnered with them in a pilot with staggering results: 100% increase in monthly clicks on paid content promotions.

Every publisher has the tools to discover not just what women want but what each woman wants. Not every woman is the same, and Big Data allows for the individualised, customised approach.

So what do women want? Women want you to know what they want, without having to tell you.