How to use AI to optimise your marketing content
AI can drive marketing success by optimising audience targeting and reach but, more importantly, AI optimise your creative content through Content Atomisation.
This article was originally published on Tide.
So, you’re a small business owner with a brilliant product or service that’s going to make waves in the market. You’ve done all the work of building the business so far, now you just need customers and traction, and you’ve been using online ads to get your product out there.
Except that, when it comes to ads, you’re finding yourself a bit lost, because how do you know what works and what doesn’t?
Since your team is still small, resources and manpower are inevitably limited, so how can you create killer marketing content that competes with the big industry players?
Traditionally, a marketing team has several ways of discovering what makes their ads successful: experimentation, extensive A/B testing, market research – to name just a few.
“Your marketing department is probably quite small meaning all these traditional approaches take up A. Time you don’t have and B. Money you don’t have.”
As a small business, your marketing department is probably quite small. You may even have just one person working on the marketing side of things, which means all these traditional approaches take up A. Time you don’t have and B. Money you don’t have. Most importantly, even after you run these tests, how do you actually learn from them?
But without a dedicated marketing team that’s able to conduct and learn from these tests, how do you figure out what works in your marketing?
“Without a dedicated marketing team that’s able to conduct and learn from these tests, how do you figure out what works in your marketing?”
Well, this is exactly where data and artificial intelligence (AI) will turn out to be your best friend. Let’s look at why investing in AI tools that optimise your marketing content is key, and will ensure your product is a best seller.
Data and AI tools
AI is able to use past data to simulate human intelligence processes to perform tasks, especially repetitive tasks, with much more speed than a human marketer can. It’s also able to identify patterns and make predictions based on the data it’s trained on, making it a powerful marketing tool for enterprises.
“AI is able to use past data to simulate human intelligence processes to perform tasks, especially repetitive tasks, with much more speed than a human marketer can”
Most significantly, over the last decade audience targeting has been made much easier with AI algorithms that are able to digest customer data and reveal their habits. The real-time matching of adverts to viewers is another area that’s being facilitated by machine intelligence at some innovative companies, dynamically predicting CTRs and optimising ad selections on the fly.
Yet AI tools tend to focus on targeting and delivery, which is helpful for stretching marketers’ resources further, but fail to see the bigger picture. What these tools miss is the importance of content data: Of understanding what specific features perform best in your creatives and engage your audience.
An AI tool that uses its prediction abilities to demonstrate what creative is going to perform better is equally, if not more important than a focus on delivery. Let me explain why.
Content data and Content Atomisation
To understand the relationship content data plays with AI, it’s important to understand how content data can be used by brands and organisations.
To understand and make use of your content data – and what’s working in your marketing and what’s not – it’s simply a matter of breaking it down into elements and checking to see if there are any patterns which relate those choices to your ad performance. This is a process we call Content Atomisation.
You can do this with all sorts of content, but let’s take a look at the images we use in ads.
If you were to conduct an analysis of your marketing images, you’d first have to take all of your previous image assets and note down any features present in the image. A very simple example of this is that you might identify that many of the images you’ve used in ads feature the colour red.
You can also go much deeper than this and identify less concrete features that we nonetheless perceive in images. For example, we might feel an image was more ‘staged’ if the people or items in it are positioned in a way that registers to us as unnatural, and vice versa.
There’s countless different features to look out for, from what objects are in the image to the emotions the image evokes.
“Once you’ve identified the different elements, you can see which types of images are receiving the most engagement and understand the features that are resonating most with your audience”
This is a process that can also easily be used to identify text features. For example, you might notice that your ad copies tend to use certain words and this certainly would be a feature of the copy. You might also notice when the language you’ve used tends to be more formal, or more friendly. Again, there’s many, many potential different features in each element of an ad.
Once you’ve identified the different elements, you can see which types of images are receiving the most engagement and understand the features that are resonating most with your audience. Taking the time to conduct this sort of analysis has a real impact on your understanding of your audience’s content preferences and allows you to create ads that work.
Content Atomisation with AI
Of course, content analysis is easier if you have just a few campaigns on the go. Scaling Content Atomisation is more tricky.
“With AI, even a single marketer can automate the process of semantically analysing hundreds of past campaigns in mere minutes”
It stops being practical to expect humans to spend days, weeks, even months labelling what goes into each piece of content when we’re looking at hundreds and hundreds of past campaigns. Here’s where AI becomes a complete lifesaver, because it can conduct this analysis of all your content data in moments.
With an AI tool, like our tool Datasine Connect, that’s been trained on past engagement data to conduct Content Atomisation, even a team of just a single marketer can automate the process of semantically analysing hundreds of past campaigns in mere minutes to understand the exact features that are the most impactful, making the absolute most of a modest marketing budget.
Want to be among the early adopters of Content Atomisation? Book a demo now:
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