Artificial intelligence, especially machine learning, is an integral part of marketing nowadays. Read on for part one of three of our complete primer for AI in our industry right now.
Related content and recommendations
Predictive analytics allows platforms like Netflix to surface and finesse related content. Clustering algorithms make better recommendations. So the longer users stay, the more likely they are to enjoy their subscriptions.
Under Armour is one of the many companies to have worked with IBM’s Watson. The sports apparel company combines user data from its Record app with third-party data and research on fitness and nutrition.
The result is the ability for the brand to offer personalised training and lifestyle advice based on aggregated wisdom. You can find out more about the collaboration on TechInsider.
Search engines
In late October 2015, Google admitted it was using RankBrain, an AI system, to interpret a significant number of search queries.
RankBrain has proven useful in natural language processing (NLP). It can find relevance in content and queries, as well as interpret voice search and user context (e.g. Google Now).
Machine learning is nothing new at Google. It is already used in search, advertising and YouTube recommendations.
Preventing fraud and data breaches
Card issuers have used AI to analyse credit and debit card usage patterns and device access. This allows security specialists to identify points of compromise.
Retailers would also find AI useful because they have been subject to high profile data breaches. This is a result of outdated systems based on usernames and passwords without any strong authentication process.
This area of security analytics has been around for years but is becoming more sophisticated. Solutions have to react swiftly to new fraudster tactics and analyse unstructured data, too.
Natural language processing (NLP) can examine text within transactions and transform it into structured data. Newer AI implementations can also identify anomalies in behaviour, even on the first instance.
Social semantics
Microsoft’s AI chatbot ‘Tay’ (and its embarassing tweets), was an unforgettable experiment between AI and social media.
Yet, deep learning has plenty to offer within social media. Deep learning refers to machine learning on large datasets – a neural network that recognises abstract patterns.
Areas where AI has the potential to allow social networks to improve at scale are sentiment analysis, product recommendations, image and voice recognition.
Have a look at Facebook’s AI research to see the many possibilities. Wired magazine also covered a particularly novel use – using AI to analyse overhead images of topography to find evidence of human life. Facebook could use this to target its internet-providing drones at communities that need them.
Website design
The Grid is a website design platform which uses AI to build websites and automate web design. It uses a new style of CSS called GSS (Grid Style Sheets). Functionality includes intelligent image recognition and cropping, algorithmic pallette and typography selection. It has been on beta for a long while and their ‘pioneer’ batch are getting restless! The jury is out as to whether AI will be replacing web designers anytime soon, but we think this is an empowering step for business owners of the future.
On that note, we end the first part of our series of articles covering developments in AI marketing. Leave your thoughts and comments below – what does the future hold for AI?