What is content atomisation?

August 19, 2020

When it comes to science, smaller is often better. For example, despite being indescribably tiny, atoms give huge insights into the world around us. And by making them even smaller (splitting them), we can produce the world’s most powerful source of energy.

It’s the same with data science. By breaking campaigns down into granular metrics, we can draw deeper and more accurate insights about everything from audiences to performance.

Until now, data science has looked at traditional metrics. Clicks, engagement rates – that kind of thing. Because it’s traditionally seen as ‘unmeasurable’, creativity has stayed apart. 

Many people feel that marketing (which is a very creative profession at heart!) has suffered from this.

Well, we’re here to change all that. We want to empower marketers by putting creativity back at the core of marketing. 

But we don’t want to do this by taking marketing back to the pre-data era. No. Rather than turning the clock back to a time before the data boom, we want to bring creativity forward. We’re aiming for a future in which creativity and data work together, empower one another, and bring out the best in each other for the benefit of all.

To do this, we’re returning to that ‘smaller is better’ principle. We’re extracting what we call ‘creative data’, through a process we call ‘content atomisation’.

How does it work? Let us explain:

Creative data

When you get right down to it, everything is atoms.

It’s the same with data. Everything is data. The trick is to find a way to measure it.

Creative content is chock full of data. The colours in an image? Data. The figures, objects, and shapes in an image? Data. The ‘mood’ of an image? Data. The tone of creative text? Data. All of it is data. But how can we extract this ‘creative data’? And, more to the point, how can we measure this data in a way that brings actionable insights?

Step 1: Atomise your creative data

To extract every facet of creative data – from colours to figures to tone, expressions, mood and much much more – would take a human marketer forever. But for an AI, it’s easy.

Our platform uses a highly trained AI to break your creative content down into hundreds of individual facets (or ‘atoms’). This turns your creative content into creative data, each ‘atom’ of which is marked with its specific quality or qualities.

If you’ve been using tags to measure things which aren’t aligned to traditional metrics (for example, tagging influencer-led content with the influencers’ names in order to track and compare engagement rates ), this will sound familiar to you. 

So, what’s the difference between content atomisation and tagging?

Well, the major difference is that content atomisation goes far deeper than tagging ever could. By atomising content, our AI effectively applies thousands of ‘tags’ to your creative content, accounting for absolutely everything from solid graphical features to more abstract and ephemeral things (like the tone and mood of the piece).

Crucially, our AI also does this automatically. Atomising content by manual tagging would take huge chunks of time which human marketers simply don’t have.

Once your content has been atomised and turned into data, the next step is to analyse it.

Step 2: Find correlations between creative data and performance

Creative data on its own isn’t much use. In order to properly quantify and measure creative data, you need to have something to measure it against.

Our platform measures either against your past campaigns, or against the engagement metrics of an AI-generated audience. 

So, having turned your creative content into atomised data, our AI will then run that data against performance and engagement metrics, and extract patterns relevant to your KPIs.

For example, do ads featuring creative content with smiles and blue skies get more clicks than ads which don’t? Does the presence of a graphic effect like a sparkle enhance or detract from this? 

Our AI can not only extract information like this, it also goes much, much deeper. 

It can tell you the kind of mood your customers will respond to best, and the graphical features which will evoke that mood. It can show you how even subtle alterations in colour can make a difference to your engagement metrics – and tell you exactly which colours to use.

Our AI is able to analyse enormous quantities of data in seconds. It will know almost immediately what’s worked for you in the past, and what will give the best results in the future. 

It can help you to make lightning-fast adjustments on the fly as tastes change and new patterns form. And it ensures that you can always give your customers what they want.

Step 3: Empower your creatives and your audience

Creativity has always been a risky business. All too often, creative marketers have put their heart and soul into a piece, only for it to fall flat when it hits the market.

Our content atomisation process ensures that this won’t happen. It empowers creatives by giving them the right notes from the get-go. They’re free to innovate and create, knowing all the while that audiences will love what they’re doing.

It also empowers audiences by giving them content that’s precisely tailored to their own needs. We all know how important personalisation is for both marketers and audiences – Datasine’s content atomisation technique takes personalisation to the next level.