This post is part of a series focused the future development of AI services and how we can harness its positive impacts, capabilities and potential to further optimize our creative practises.
Last week on the blog, we discussed how to combat common workplace fears of artificial intelligence. We touched on how AI technology could be used in the marketing industry as a whole, but not how it would help marketers elevate the creative processes specifically.
At first glance, creativity and AI don't appear to go hand-in-hand, the negative impact still being that, one day, ai systems will be able to do whatever we human beings can and render us obsolete, even our creativity.
However, that is not the case for the marketing industry, as we'll demonstrate that in this blog post.
Artificial intelligence and creativity
Content, customer engagement, customer experience, customer behavior, etc. are all examples of domains that benefit from the inclusion of AI technology.
Businesses that integrate AI methods enjoy deeper insights and more opportunities for growth, this promotes innovation like assessing gains and losses on the micro scale in order to augment the larger picture.
But these are not the only areas of customer focus that benefit from the inclusion of artificial intelligence. Marketing AI systems can help too, specifically when it comes to delivering cut through creative ideas.
Using AI to support the creative process is becoming an increasingly more relevant practice as the boundaries of what constitutes as creative blur. How do we define creativity? Can only humans be creative? If AI depends on data it has to "create" something, does that count as creativity?
Including AI tools in the creative process is going to be key when it comes to battling modern creative problems. In fact, you'd be surprised to see how seamlessly artificial general intelligence fits in...
Artificial intelligence and the human brain
Like AI, the human body and brain seems to work in mysterious ways to many of us.
However, the parallels between the two are striking, especially when viewed from a psychological angle.
System 1 vs. System 2
System 1 and System 2 are alternative terms to what has been called "slow thinking" and "fast thinking" in the past. They were coined by psychologists Keith Stanovich and Richard West in order to describe how the human brain processes stimuli and completes tasks. However, it was Daniel Kahneman who popularized the terms and the theory.
System 1 is the fast-acting, reactive system that controls instinctive actions, like recognizing objects and directing focus due to sensory cues (e.g. turning towards a sound). It requires very little to no conscious thought or voluntary control. Basically, you don't really realise you're doing it until you're doing it.
System 2 is the slower, analytical system. It helps us solve puzzles, assess situations, and make subjective choices. Unlike System 1, this system requires conscious thought, and if that attention is interrupted, then so are any actions being taken.
Do you see the similarity here between these two systems and the relationship between artificial intelligence technology and the human brain?
System 1 - AI
AI is the technological equivalent of System 1. Artificial intelligence technology can only do what it has been programmed to do with no additional power being directed to other non-programmed tasks, just as System 1 is able to recognise facial expressions and direct basic tasks without conscious attention.
System 2 - the human brain
In this metaphor, the human brain is System 2. While AI tools work "in the background" on the tedious, mundane routine tasks, all the 'human capital' can be focused on the creative process and generating strategies and content.
The thing to note about Systems 1 and 2, and therefore about the relationship between AI algorithms and the human brain, is that the brain doesn't switch between systems - they work in tandem.
As AI becomes commonplace, this concept is how we can view the future of creative marketing - a balance between fast thinking tasks completed by AI and deep thinking (creative) tasks completed by humans.
The "modern creative process"
Modern marketing efforts require modern solutions, like using machine learning algorithms to improve customer experience or to deliver personalized user journeys. Many companies, like Amazon, are already way ahead, analyzing customer data and digital behavior in order to tailor product purchase suggestions on their sites and social platforms.
In marketing, creativity is key. In other words, if you want people to be interested, you must be interesting. Being seen is no longer the problem given the incredible targeting marketers have have access to.
It's all about getting heard. Delivering insightful, original ideas that cut through all the other noise to create real engagement, joining the dots in new ways to deliver messages that inspire - this is a human superpower and something AI is not capable for the foreseeable future, so the future for creative thinkers is very bright.
Your AI-proof and your skills will become increasingly more desirable, but if you can leverage AI to your advantage and amplify ideas, you and your own business models will be on another level.
The "modern creative process", as we at Loops like to call it, is all about embracing technological advancements across the world in order to elevate and augment creative processes, and find new solutions to persistent problems. Having amazing ideas is one thing, but proving they're amazing and getting buy-in? That's another.
Creative work is subjective - fine for purely creative pursuits, but if you work in marketing, you must find ways to prove objectively that it will deliver the right message and inspire action.
This is where you can use AI, to quickly prove that audiences understand the idea and that it has impact. Previously, you may have used a focus group, but today you can use tools like Loops instead with 10x the speed, scale, and rigour.
Why do we need AI in creative marketing?
Applying AI to data insight
Customer data is crucial to the marketing process. Machine learning technologies that can process and analyze customer data in real time offers companies not only deep insights into current consumer behavior and UX, but also into the future.
Predictive analytics is overlooked in many marketing strategies, with marketing teams focusing only the now and near future, rather than where marketing campaigns could go. Data driven campaigns and decisions have a higher rate of overall success and client satisfaction, data analytics can also offer insights into previous unconsidered audiences and creative paths.
Tools like Pulsar Platform offer this capability.
At Loops, the qualitative data we collect from our 110m+ expert pool is analysed by several forms of AI to deliver outputs like sentiment analysis ("Do people like it?"), theme analysis ("What are the keywords and related topics?") and summaries of general comprehension ("Do they get it?").
This not only helps move the design process forward with real time data, but also supports and validates creative choices once we've converted it into easily digestible quantitative data.
Applying AI to content marketing
For companies with strong content marketing strategies, using AI in the content creation process can be a great way of shifting some aspects of the workload and creating content more efficiently.
Natural language generation (NLG) AI that can generate tweets and blog posts could become important tools to a marketing team, expediting the creative process if their attention is needed elsewhere.
Natural language processing (NLP) is a rising star in the artificial intelligence sphere, and AI marketing tools like Surfer SEO and Conversion AI have become helpful to the content creation process due to their brain-jogging and contextually sound capabilities.
Loops uses a form of deep learning and branch of NLP called natural language understanding (NLU) to identify themes, patterns, keywords, and sentiments in the feedback received on ideas, concepts and designs. It does the heavy lifting that a qualitative researcher might do in a click.
AI tools give you back time and preserve your energy
Like with the System 1 vs System 2 metaphor we made earlier, using AI in marketing to take care of the repetitive number crunching and time-consuming data analysis means marketers free up precious time so that efforts that can be better spent elsewhere.
Rather than simply creating content because you think it would be a great fit for your company, or you think it would simply make sense, let the data lead you to what your customers are looking at most and want to see more of. By doing this, you don't waste time creating content that won't serve a purpose or your brand.
AI can help you measure marketing effectiveness
Because the digital age of marketing is technology-based, using artificial intelligence algorithms to easily analyze any marketing strategy is a given.
The big data collected can show companies which channels customers are using the most or least, which ones are collecting the most customer data, how long customers are staying on each channel, etc.
All this big data can then inform companies of which traction channels are actually working, and therefore where they should direct their attention. Tools like Automated Creative turns impressions into intelligence.
Loops enables a modern creative process
Data, design thinking, and iteration sit at the heart of Loops, and power our mission to deliver a modern creative process. It's not rocket science - it's simply working in an agile way based on consumer insight.
This gives you better access to the most valid, supportive, and in depth research to inform creative marketing choices. The AI we use in the mix simply does the heavy lifting of your analysis - it's not a replacement for your imagination and intuition.
