Artificial Intelligence and Machine Learning are increasingly becoming an essential aspect of many industries, and Marketing is no exception. Innovation in AI-driven Marketing Technology promises a better end-user experience – with chatbots, sentiment analysis and product pricing algorithms ultimately providing a smoother customer journey.
Meanwhile, for marketers, AI has gone from offering tools that automate aspects of their jobs, to those which can help advise and augment day-to-day Marketing decisions. And as AI gets smarter, it can begin to address some of the most common pain points facing marketers today – enabling them to make more informed decisions to drive customer retention and acquisition for their campaigns.
A Picture Really Is Worth a Thousand Words
Images, graphics and photography have always been a crucial component of Visual Marketing – and this has only increased with the rise of social media and the consequent abundance of imagery available online. In fact, between 65 and 85 per cent of people now describe themselves as ‘visual learners’, meaning they extract more information from what they see rather than what they read.
A business that is consistently utilizing the best visual assets for their core audience is likely to see increased engagement, click-throughs and sales, ultimately driving customer retention and acquisition. But this can be a daunting prospect – after all, humans are subjective. How confident can you be that the image you like is one that will resonate well with your audience?
Your company’s imagery not only needs to be high-quality and relevant, but it must also stand out amongst the glut of photographs shared by users online. Furthermore, it’s becoming increasingly difficult for a single human mind – or even teams – to track campaign engagement and learnings across the multiple channels utilised for Marketing today. And what happens when team members leave, taking all their knowledge with them?
The result is that marketers often have a very limited understanding of how engaging their visual assets will be once they begin their campaign. This is where AI can come in and remove the guesswork.
Explainability and Collaborative AI
Crucially, it is important that marketers aren’t simply told which visual assets will work best for their Marketing campaign, but why they work and don’t work. This way, they can gain an understanding of how to improve images – whether this is by selecting a more symmetrical picture, or one where the sun is shining.
By using AI to make more informed decisions, engagement insights also can be shared across the whole Marketing team, meaning that each marketer is capable of tapping into a centralized repository of AI-driven knowledge, instead of relying on their own experience or memory of what content works for which channels.
This collaborative approach to AI equips businesses with marketing teams that combine the analytical power of computers with the unrivalled creative mind of humans. The result is a new generation of ‘super marketers’ who can be confident in the appeal of their visual assets even before they hit ‘send’.
Training Computers to “See”
Recent developments in Computer Vision – the same technology that is used to identify which of your friends are in your Facebook photos – mean that machines are now capable of identifying all kinds of elements of an image, including animals and pets. This technology has now become so precise that doctors have begun to utilise computer vision for diagnosing diabetic retinopathy and malignant skin tumours.
It’s important to remember that these applications for Computer Vision are dealing with an objective task, e.g. whether a patient should be referred for a CT scan, whereas Marketing presents a different issue because machines have to take into consideration a number of factors in order to predict what visual assets will be appreciated by your audience.
Nonetheless, modern AI is capable of determining whether an image is aesthetically pleasing, what emotion or mood the image conveys, and whether it contains typography, complementary colours, or even specific animals or other elements of nature. With all this in mind, the machine can assess a series of images and anticipate which one will perform best.
Understanding Your Customers
With computer vision AI tools that are capable of providing explainable insights, marketers are able to build more successful Marketing campaigns, particularly in reference to visual assets. Furthermore, by combining these tools with algorithms trained on your own customer engagement data, you can begin to understand your customers as individuals – catering to their specific interests and personal preferences.
The ultimate result is more efficient marketing teams, more engaging campaigns, and happier customers that trust and value your business.