Data is revolutionising many industries. They include transport (self-driving cars), medicine (medical image recognition), finance (algorithmic trading) and retail (online retailers and recommendation systems).

What all these examples have in common is their varied use of ‘machine learning’. Machine learning algorithms take large amounts of raw data, and learn from it more effectively than any human could. Companies that succeed in this new environment know how to use that knowledge to inform business decisions and deliver a commercial return.

There’s a perception that communications and PR are immune to the data revolution because they’re founded on ’softer’ skills such as relationship-building, working with influencers and writing compelling content (all of which are attempting to build advocacy and drive differentiation).

Here are seven reasons why that’s not the case.

1. The majority of communication now happens on one platform: the Internet

Print and, increasingly, TV are peripheral now – at most they are adjuncts to content and news shared online and on social networks. For example, 95% of UK adults have a Facebook profile. More people in the UK now use a mobile phone than a TV, and more use a laptop or PC than a radio, or print newspapers and magazines (Ofcom Adults’ Media Use and Attitudes 2016 survey).

The deep structure of the Internet – the way it divides people into fragmented communities, the way some content spreads while other content doesn’t, the way a vivid lie travels further and faster than the complex truth – affects our culture in ways we’re only just beginning to understand. The rise of Trump is a fascinating case study of how our information landscape is bound up with this new platform, and how little we understand the dynamics behind it.

As communications professionals, we must be at the forefront of understanding this new landscape, mapping and navigating it to manage our clients’ reputations and support how they engage with their audiences or customers.

2. The Internet is ‘machine-readable’

In other words it’s easy to use computers to collect, combine, analyse and generate insight from the Internet. This wasn’t the case for traditional media such as newspapers and TV.

Because of this, our communication – from news articles, to social media comments, to Instagram photos – can become raw material for the machine-learning algorithms.

The most successful communicators will be those who best use data to boost their campaigns, or use the insights it generates to trial new, more effective approaches.

3. Data is encompassing areas previously outside its reach

Areas previously seen as separate from more data-driven analysis – including text , video and imagery – can increasingly be processed and optimised by machine learning algorithms, alongside more numerical content. That means the range of content types where it’s possible to use machine learning to gain an advantage is expanding.

Additionally, machine learning can now analyse content at scale – replacing woolly conclusions gleaned from a tiny sample size of one or two articles, with robust conclusions based on hundreds or even thousands of web pages or social media posts.

Increasingly, PR professionals will be able to improve all aspects of their campaigns using machine learning – not just those which are more obviously numeric or metric-driven.

4. Platforms – and their algorithms – control our access to information

Companies such as Facebook, Google and Apple are now the gatekeepers of the media landscape. Traditional media – mere ‘content generators’ such as the BBC, The New York Times, and The Washington Post – have become subservient to the platforms owned by the gatekeepers.

This is both because traditional media must tailor their content and online presence to the platforms, but also because they’re engaged in a race to the bottom with sites founded to thrive in the new landscape – the Buzzfeeds, Huffington Posts and (unfortunately) Breitbarts, of the world.

Even on their own websites, news organisations are implementing algorithms that control the content available to readers. The Washington Post analyses the performance of each article for the first 30 minutes after it’s put live, then prioritises content it believes will be more successful in terms of clicks, reads and shares.

Everywhere we look – the content we see and the content we create that reaches our target audiences – is mediated and controlled by algorithms.

As agencies and communicators we’ll need to use data to understand how to navigate those algorithms and make sure our content reaches the people we want it to.

5. Mass audiences have become micro-audiences…

…and fame / celebrity has fragmented into ‘micro-fame’. Andy Warhol’s famous quote was only half-right – in the future everyone will be famous not for 15 minutes, but within a small, focussed community related to their hobbies, political persuasion, interests, or friendship circle.

Influencers are those who can transcend the fame of their real-world contacts – friends, family and colleagues – and become known amongst a geographically dispersed community brought together by the Internet.

For communicators, data will increasingly be needed to identify, locate, reach and persuade the specific micro-community you’re targeting – whether they are patients with a specific disease or risk factor, or likely Trump voters in swing states.

6. Everything is much more measurable

It’s increasingly possible – and expected – for PR messages and campaign content to be targeted, tested, iterated and customised.

Clients will no longer be happy with vague promises to ‘raise awareness’. Instead professional communicators will be expected to have the data skills to measure impact in novel ways and demonstrate tangible results. Agencies will differentiate on their ability to use data to robustly demonstrate benefit and to deliver better results.

7. Data *is* the story

So far I’ve focussed on ways in which practitioners can use data to target, optimise and test what they’re doing, but there’s another way in which data is important for PR: it’s increasingly becoming the story itself.

More and more, leads are generated by analysing data rather than through old-school reporting. Stories focus on statistics and numbers – for example the minutiae of election polling data, or the dispute around the size of the crowd at Trump’s inaguration. Finally, journalists increasingly tell stories through techniques such as interactive data visualisation.

Data is nothing without creativity and storytelling, but it’s impossible to look at the work of the NY Times graphics department, or view the data artworks of the designer Nicholas Felton, and deny that they’re often one and the same.

This ability to creatively tell a story with, or about, data is the final new skill that PR practitioners will need to master after the data revolution.

To hear more about Health Unlimited’s data capabilities, contact Andrew Lamb.