How is Artificial Intelligence Revolutionizing Digital Marketing?
Artificial intelligence marketing 8 Examples
Here are a whole bunch of case studies and use cases, as a complete primer for artificial intelligence in our industry. Predictive analytics allows Netflix to surface and finesse recommendations. This kind of machine learning algorithms is continually improving suggestions, allowing users to make the most of their subscription.
Uniting information from diverse website design is a common use of Artificial Intelligence. Under Armour is one of the many companies to have worked with IBM's Watson. The sports apparel company combines user data from machine learning algorithms with third-party data and research on fitness, nutrition etc.The result is the ability for the brand to offer up relevant (personalized) training and lifecycle advice based on website design
Search engines
In late October 2015, Google admitted it was using Rank Brain, an Artificial Intelligence system, to interpret a 'very large fraction' of search queries. Rank Brain should mean better natural language processing (NLP) to help find relevance in content and queries, and website design as well as better interpretation of voice search and user context (e.g. Google Now).Andrew Howlett, CTO of Rain Agency, told AdWeek: Customers providing reviews use real language and say it in ways that people might also ask a question through Google. For example, in a review, someone might say, 'This place has the best chips and salsa anywhere that doesn't cost a fortune. 'Machine learning algorithms is, of course, nothing new at Google, already used in search, advertising and YouTube recommendations
Preventing fraud and data breaches
Analyzing credit/debit card usage patterns and device access allows security specialists to identify points of compromise. The relevance of artificial intelligence is not just for card issuers, though. Retailers, for example, have been subject to high profile data breaches (e.g. Neiman Marcus) as a result of a system based solely on machine learning algorithms (without any stronger type of authentication).This area of security analytics has been around for years but is becoming more sophisticated. Solutions have to react quickly to new fraudster tactics and website design and analyse unstructured data, too. Natural language processing (NLP) can be used to look at text within transactions, for example, transforming it into structured website design
Social semantics
Looking at Microsoft's artificial intelligence chatbot 'Tay' (and its regrettable tweets), one might not immediately think Twitter and Artificial Intelligence go together like salt and vinegar.However, deep learning (a term used often to refer to machine learning algorithms on large datasets - a neural network recognising abstract patterns) has plenty to get its teeth into on social.Sentiment analysis, product recommendations, image and voice recognition and website design there are many areas where artificial intelligence has the potential to allow social networks to improve at scale.It's worth having a trawl through Facebook's AI research to see the many possibilities, if you've got a head for scientific whitepapers, that is. Wired magazine covers a particularly novel use (outside of Facebook's social network) - the tech giant analysing website design of topography to find evidence of human life
Website design
The Grid is an artificial intelligence website design platform. Intelligent image recognition and cropping, algorithmic pallette and typography selection - The Grid is using AI in certain areas to effectively automate web design
Product pricing
With thousands of products and many factors that impact sales, an estimate of the price to sales ratio or price elasticity is difficult. Dynamic price optimization using machine learning algorithms can help in this regard - correlating pricing trends with sales trends by using an algorithm, then aligning with other factors such as category management and inventory levels
Predictive customer service
Knowing how a customer might get in touch and for what reason is obviously valuable information. Not only does it allow for planning of resource (do we have enough people on the phones?) but also allows personalisation of communications. Another project being tested at USAA uses this technique. It involves an Artificial Intelligence technology built by Saffron, now a division of Intel. Analysing thousands of factors allows the matching of broad patterns of customer behavior to those of individual members. The AI has so far helped USAA improve its guess rate from 50% to 88%, increasingly knowing how users will next contact and for what products
Ad targeting
As Andrew Ng, Chief Scientist at Baidu Research, tells Wired, “Deep learning [is] able to handle more signal for better detection of trends in user behavior. Serving ads is basically running a recommendation engine, which deep machine learning algorithms does well.” Optimising bids for advertisers, algorithms will achieve the best cost per acquisition (CPA) from the available inventory. When it comes to targeting of programmatic ads, machine learning algorithms helps to increase the likelihood a user will click. This might be optimising what product mix to display when retargeting, or what ad copy to use for what demographics
What is AI ?
Artificial intelligence marketing
