Let’s talk about Artificial Intelligence, the biggest buzz in the world right now. Don’t worry, you don’t need to be an engineer to understand these concepts. This blog aims to clarify these big terms in simple words, in order to equip marketers with all the tools to conquer the digital marketing world (minus the technical overload).
So Let’s Break It Down - What is Artificial Intelligence?
Starting off with the term that gets thrown around a lot, Artificial Intelligence (AI).
It stands for machines that perform thinking-like actions or imitate the behavior of a living being, basic tasks we consider “smart”. Although this word has become popular more recently, it has been around for a very long time.
As old as calculators are, even they are classified as Artificially Intelligent.
A commonly known application of AI is known as Machine Learning. It can be easily understood as computer programs that get better with use. This is where the learning bit comes into play, these machines modify themselves as exposed to more data without any human intervention.
Machine Learning is implemented with Deep Learning. This is a new technique of programming which is based on the neurological model of a brain. You might immediately think of a human brain, but since this technology is so preliminary, we have only managed to make it work like an ant’s or a fly’s brain, as of yet. For this model to work, the machine has to be fed with large amounts of data to enable a deep neural network synthesize.
This may sound complicated, but all you need to know is that the learning takes place in the machine when they analyze layers of information. So more the information, more the layers means better the understanding and learning of the machine. This picture rightly sums up how Deep Learning is put to work for Machine Learning.
Image source: Mapr, "Demystifying AI, ML, DL"
Where Should You Start?
Firstly, before starting off with the AI integration, it would be helpful to streamline the existing time and money consuming mundane chores, involving large amounts of data. This can be done by automating basic repetitive reports. By doing this, you can focus more on solving complex problems. In Merkle-Sokrati, we took up the stance to automate as much as possible. We have managed to automate plenty of reports, from daily and weekly reports to pulling updated prices of products directly from the website.
Secondly, it’s important to prepare your data for AI. This not only includes standardizing the collection of data but also having a knowledgeable team on board to back it up. Building a centralized information architecture is a step towards standardizing data. The difference seen between decentralized and centralized information systems, displayed below, makes the improvement in the flow of information apparent. This can be a synthesis of data from different departments as seen in the picture or consumer data from different touch point, and so on. However, if your company does not have such data and expertise, digital marketing agencies can come in very handy. Not only do they have access to a plethora of information but also experience in using a similar type of data in more meaningful ways.
Lastly, the amalgamation of AI into the standardly structured analytics can open up a world of opportunities. Some recent implementations include understanding, explaining and predicting consumer behavior. This is exemplified by Amazon’s product recommendations algorithm which uses machine learning to layer new unstructured data to its centralized collection of structured data like purchase history, consumer’s location, payment details and so on. The opportunities of AI application in marketing are endless but to uncover its true potential, it is important to indulge in experiments to discover new uses of the technology. Just make sure you do it with a smaller budget or remarketing audiences to avoid wastage of the budget.
Image source: Software Advice, "Your IT Organisational Structure"
To Sum It Up – Play the game or get played
AI, Machine Learning, and Deep Learning are technological advances that take away strenuous work from the marketers’ ends. By employing AI, you would not only be saving time and money but also make more comprehensive marketing decisions. Collecting, standardizing and assimilating data are initial steps towards creating a centralized information system for Machine Learning, which in turn makes sense of new data. There are numerous applications of this technology, but in the end, it comes down to exploring and experimenting with it to find out new ways of making it work for you. By getting overwhelmed with the technical nature of AI and not playing the game in such a highly competitive market, you are risking getting played.