The datasine team
What is ‘creative data’? And how can you harness its power?
We’ve spoken about the importance of personalisation in marketing, and how the right kind of data can help you to build relationships with your clients. Relationship building is, as all marketers know and, the key to successful marketing.
Content is the main tool that brands use both to express their voices and personalities, and to build relationships with their audiences. Developing a ‘voice’ and a ‘tone’ specific to particular audiences, and expressing that tone through your content is crucial to relationship building.
However, it’s surprisingly rare for marketers to break down the content that’s working for them and analyse it creatively. We in the industry have put an incredible amount of work into developing audience-specific tones but, when those tones work, we rarely go back and analyse precisely what it is about them that’s so appealing for particular audiences.
You may think that understanding this kind of thing is a matter of human intuition, and it is. But there is a way to enhance and inform this intuition. By breaking your content down into ‘creative data’ you can remove the guesswork and glean some surprising insights into not only what your audiences like – but why they like it.
Turning creative content into data
Despite having a ton of tools at our disposal to gather, process, and gain incredible insights from data, we still have a huge and overlooked data gap: the data embedded within our creative content.
At a very basic level, we don’t know why our stuff works the way it does.
Given that content is so key to our relationships with our customers, it’s perplexing that we don’t analyse it in a way which leads to actionable insights.
To close this gap in our knowledge, we at datasine turn creative content into data using a process called ‘Content Atomisation’. Here’s how it works:
Content atomisation – what it is and how it works
Content atomisation involves breaking creative content down into its individual facets, and viewing each of those facets as important, standalone aspects.
Think of image tagging. A photograph of a smiling face might be tagged #smile #selfie etc. Algorithms like those used by Instagram notice when you frequently ‘like’ images with a particular tag, and they show you more images with that tag.
Content atomisation works a bit like that – but it takes it a lot further. Our platform doesn’t just ‘tag’ images – it breaks them down into many, many facets, including ‘taggable’ things (like smiles, facial features etc), but also including aspects like lighting, mood, logo placement and so on.
Why is this important? Well, this is where psychology comes in.
Why do we like what we like?
Ask a group of people ‘what makes good art?’ and you’ll come back with lots of very different answers. Some would say it’s the talent of the artist. Others would say it’s the message of the piece, or the feeling it gives the viewer.
The truth is that we often don’t know why we like what we like. Art is subjective – what one audience adores, another won’t see the fuss about. Different people like different things, and that’s usually because of a gut reaction that the person themselves often can’t explain.
But, by turning a piece of art into data, we can get a bit closer to that all important ‘why do I like this?’ answer.
The second part of our content atomisation process involves taking your atomised content and comparing it to both the other pieces in your creative archives, and your engagement stats. This is where the patterns start to form.
For example, you may be wondering why a set of apparently unrelated images are performing well with certain audiences. Through content atomisation and cross-comparison, you may discover that the pieces with the highest engagement stats do, in fact, have various things in common.
It may be the placement of your logo, the lighting, the mood evoked or something even less obvious. But the pattern is there, and it enables us to draw actionable insights not only about the kind of content that people engage with – but what it is about that content that encourages engagement.
Turning insights into action
By getting as deep and as detailed as an analysis based on content atomisation, content creators can take the risky guesswork element out of producing new marketing material.
Far from reducing creativity to a ‘numbers’ game, granular data insights like these enable creative marketers to be more innovative than ever with their content – without having to worry that their efforts won’t be appreciated by the audience.
Our platform will tell you what elements to include in your creative content in order to resonate with a particular audience. The nature of the process makes it fully scalable, and takes away many of the problematic elements of campaign creation.
It lets you pre-optimise your creative content, meaning that you don’t have to go through risky and expensive A/B testing, and that you don’t have to be cautious when creating new content.
All in all, by harnessing the power of creative data, datasine can give you the kind of actionable creative insights which enable data to power creativity, and vice versa.
To crack open that data gap, we need to start conducting in-depth semantic analysis of our content. Only then can we begin to truly understand why some content resonates and some doesn’t.
The datasine Team
98% of marketers agree that personalisation is of huge benefit when developing customer relationships. But there’s a very fine line between ‘personalised’ and ‘creepy’.