Looking at Microsoft’s AI chatbot ‘Tay’ (and its regrettable tweets ), one might not immediately think Twitter and AI go together like salt and vinegar. Newer AI implementations, such as that used by the United Services Automobile Association (USAA, which provides financial services for ex-military), will identify anomalies in behavior even on the first instance.Ĭould Neiman Marcus have benefited from AI to prevent a data breach? Natural language processing (NLP) can be used to look at text within transactions, for example, transforming it into structured data. Solutions have to react quickly to new fraudster tactics and analyze unstructured data, too. This area of security analytics has been around for years but is becoming more sophisticated. Neiman Marcus ) as a result of a system based solely on usernames and passwords (without any stronger type of authentication). Retailers, for example, have been subject to high profile data breaches (e.g. The relevance of AI is not just for card issuers, though. Machine learning is, of course, nothing new at Google, already used in search, advertising and YouTube recommendations.Īnalyzing credit/debit card usage patterns and device access allows security specialists to identify points of compromise.
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For example, in a review, someone might say, ‘This place has the best chips and salsa anywhere that doesn’t cost a fortune.” That sentence will help now with someone searching for something like, ‘I’m on a budget, where’s a good restaurant with awesome chips and salsa?” Google Now).Īndrew Howlett, CTO of Rain Agency, told AdWeek:Ĭustomers providing reviews use real language and say it in ways that people might also ask a question through Google. RankBrain should mean better natural language processing (NLP) to help find relevance in content and queries, as well as better interpretation of voice search and user context (e.g. In late October 2015, Google admitted it was using RankBrain, an AI system, to interpret a ‘very large fraction’ of search queries.
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It can watch what she eats and offer suggestions on how to improve her diet to improve performance. The app could map routes near her home/office, taking into account the weather and time of day. IBM explained as follows in a press release :Ī 32-year-old woman who is training for a 5km race could use the app to create a personalized training and meal plan based on her size, goals, lifestyle. The result is the ability for the brand to offer up relevant (personalized) training and lifecycle advice based on aggregated wisdom. The sports apparel company combines user data from its Record app with third-party data and research on fitness, nutrition etc. Under Armour is one of the many companies to have worked with IBM’s Watson. Uniting information from diverse datasets is a common use of AI.
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This kind of clustering algorithm is continually improving suggestions, allowing users to make the most of their subscription. Predictive analytics allows Netflix to surface and finesse recommendations. But AI is poised to change how we communicate with NON-humans! R2-D2 and C3PO are no longer science fiction!īen Davis at Econsultancy has put together a whole bunch of case studies and use cases, as a complete primer for AI in the marketing industry. While technological innovation is exciting and allows us to do things we never imagined possible, it also is a little scary! Social media has changed the very fabric of how we communicate with one another. Some experts in the marketing world are predicting artificial intelligence is set to transform the marketing and communications world even more than social media has.īut what is Artificial Intelligence and how are brands and marketers using this technology?
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