Increasingly, big data is the lifeblood of decisions around targeting and media buying in the advertising and marketing world. Ad tech and marketing tech have had a massive impact on people’s ability to integrate big data insights into decisions around where you should put your ads, what media you should buy, etc. However, until now we really haven’t seen a lot of sophisticated data analysis and big data-led solutions for creatives, marketers and publishers who are looking to answer the question, what content should I create? This point really is the beginning of the decision-making process for brands and content creatives, so getting it right is critical.
Big data is key to understanding your audience. Never before have we been able to access so much data about such a diverse group of people as has been brought together by the social web. This includes Facebook, Twitter and all other social outlets where individuals publicly publish their preferences, likes, dislikes and comments for other people to see. If we go back in history by about a hundred years, the prevailing method of doing customer or market research was collecting demographics data. This data was aggregated around particular metrics like age, gender and ethnicity that you could measure on a location-by-location basis. Then you would make your marketing, branding and publishing decisions based on location.
One of the fascinating things about big data is that it shows you the shapes, trends and topologies of insight without you having to necessarily ask the question. So when you have really small data, for example a thousand responses to a survey, you have to design those questions very specifically to get the right insight, and to be sure that the insight that you are getting is actually statistically relevant. When you have a billion content interactions and you can see that 70% of those are video, there is no kind of ambiguity as to the relevance of that particular insight. Sometimes when you have that much data you don’t even have to ask the questions – the trends present themselves to you. That was the major shift that happened through the social web, allowing brands, publishers and anyone making a creative decision to analyse that data prior to the creation process.
Science and the creative process
When a brand decides to create or plan a new product or campaign, decisions are normally made based on boardroom personas or ideas about the target audience. They might have some market research to back that up, based loosely on surveys with a small number of datapoints or some kind of information from an agency, profiling a group of people and giving a focus-group approach to understanding what the persona of their target audience should be. Big data and artificial intelligence (AI) companies are revolutionising the entire approach by giving marketers access to a huge number of datapoints about the specific content people interact with. This data reveals what different groups of people consume in terms of the content they interact with – what they like, what they share and what they comment on. Consequently, marketers can use these data resources to intelligently and accurately shape the creative decision-making process, which is when they need it most. Content creation is expensive, so being able to make data-informed decisions that are based on fact, and use extremely large data sets to guide the creative process is invaluable. Knowing what type of content your existing and target audiences want to see, and where they want to see it, ahead of the creation process, is vital to help marketers remain competitive.
How AI platforms do this
Content marketing analytics platforms tell brands, publishers and anybody making a creative or strategic decision what content they should have before they actually have to invest in creating it. It’s imperative that brands, publishers and anybody producing content, who are trying to engage with their target audiences, identify what that content should be about and who their target audiences are. Why is this important? Well, the best return on your marketing investment spend comes from creating content that actually engages and resonates with your target audience. AI and the more increasingly sophisticated processing of big data are really key in helping advertisers, publishers and marketers increase the quality of their communication. Objective data, big data and AI are changing the creative process for marketers. Gut instinct and poor decision-making are being removed from the equation when big data and objective insights are added to the mix.
AI can be used to understand how individuals interact with content, and break it down into two different things. First, AI and machine-learning algorithms can be used to understand interactions between individuals with regards to content serving networks that exist within particular tribes or subcultures on the social internet. Then we use different AI implementations to understand the actual content that is being consumed by these individuals. So for instance, we analyse the images using deep neural nets to understand en masse, across millions of images, what it is in these images that really leads individuals to engage with a particular set of images more than a different set? We analyse a huge number of news articles, BuzzFeed articles and anything that has a lot of text. We analyse them to understand which groupings of textual content, themes, topics, interests and affinities a particular group, tribe or subculture on the internet actually has. Using a large variety of different algorithms and AI techniques, a variety of insights can be produced. All these insights are useful for brands, either in a strategic sense in terms of what kind of content pillar to choose through to a more tactical application, such as what kind of image to choose for a particular article to generate the most engagement, or what kind of content format to use.
Driving positive results
Getting the best ROI out of your content and creative decisions is something that should begin when you are planning and strategising around what content you should make. To do that, you need a clear idea of who your target audience is and what kind of content resonates with them, what kind of content they consume and what their particular content consumption habits are. A lot of people only use data and data-driven processes to optimise targeting after making the content, to help target it more efficiently. This isn’t the optimal approach. It would be more efficient to use that data to understand what people want so that the content resonates with them and is relevant to them. This will help marketers grab their attention, hold their attention and allow the brand to become part of that cultural moment for an individual consumer.
