Starbucks announced on Monday Echo owners can now enable the "Starbucks Reorder" skill and, with a voice command, tell Alexa to reorder food and beverages for pickup at a preferred store. SEE ALSO: Starbucks CEO's powerful open letter on Trump's Muslim ban As with Alexa's Domino's Pizza skill, placing an order with Alexa voice commands is simple, but limited. Sure, you could already place orders for pickup using the mobile Starbucks app, but now you don't even need to open your phone. You can also check your Starbucks balance by saying: "Alexa, tell Starbucks to check my balance."
Nearly six in 10 (59%) have or would be willing to communicate with chatbots to either receive offers and coupons, receive recommendations or advice (37%), and/or conduct online banking (14%). Affluent households with income over $100K are more likely than less affluent Americans whose total household income is under $50K to find it invasive that chatbots can remember past interactions and store a customer's previous purchase history and personal preferences (28% vs. 20%). That said, people are most willing to engage with chatbots to receive product recommendations from retail stores (22%), hotels/accommodations (20%), travel destinations (18%), product recommendations from a pharmacy (12%) and fashion/style (9%). DigitasLBi conducted two online surveys within the U.S. by Harris Poll from November 4-8, 2016 among 2,040 U.S. adults ages 18 and older and from November 18-22, 2016 among 2,049 U.S. adults ages 18 and older.
With the overall number of transactions rising hugely, and developments such as real-time payments helping make settlements faster, the solutions banks have in place for fraud detection are coming under more pressure than ever. As more people turn to digital solutions for all their everyday activities, including banking and making payments, they will generate huge amounts of data that forward-thinking banks can use to identify trends and highlight suspicious behavior. It was recently noted by CIO.com.au that PayPal, for instance, uses machine learning technology that studies users' purchase history. For example, if a system is put in place to flag up any payments over a certain amount for a more in-depth review, criminals will quickly learn to place transactions that come in just under this limit.