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Machine Learning Making Big Moves in Marketing

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This means that ML will be applied to customer interaction data in order to find and exploit patterns in different types of user interactions that occur at different times and locations: purchase histories, emails, call center interactions, social media, website searches, previous marketing campaigns, and even location data and/or "emotion data" from wearable sensors while the customer is shopping. The number one hottest trend (where ML-based marketing is moving) is behavioral analytics, including both predictive and prescriptive analytics modeling. ML is first and foremost a set of algorithms that learn to detect and recognize patterns in data, and to learn from experience when making decisions or taking actions based on those patterns – i.e., the ML process learns (from both successes and failures, including failed models and failed classifications) how to improve over time. ML (including social network analysis and social graph mining) is now helping marketers identify the key influencers within their market domain.


Welcome to the Hotel California of Artificial Intelligence

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After already two decades, the Internet giants – speaking of Amazon, Google, Facebook, Alibaba and Baidu – are still collecting tons of data, filling their databases with information of everyone's knowledge, opinions, recommendations, locations, movements, buying behavior, relation status, lifestyle etc. On the contrary, almost every month, new services or devices are released to provide a better user experience, make our life more convenient and increase our dose of digital addiction. However, this progress of technological developments shows one thing: Amazon, Google & Co. find new ways to engage with us over other channels, collecting the data, information and knowledge they need to make better decisions and deliver better answers back to us. Speaking of Artificial Intelligence, the Internet giants are fully embracing AI.


How Artificial Intelligence Will Help You Beat the Competition

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Using natural language processing, it's able to separate the wheat from the chaff so your human moderators can bypass spam and prioritize your actual customers' concerns. Here's where Smart Moderation shines: because spam and troll comments are erased by the AI within a minute of its posting, you'll only see engagement from your actual customers (or prospective customers) when monitoring mentions of your brand, which means no time is wasted wading through nonsense. Your team will thank you for implementing such a smooth system that allows them to prioritize and deal with more customers than before--helping your business' reputation for good service against competition. We're still in the early days of utilizing AI for business applications, but AI community monitoring tools like Smart Moderation make it easy to jump on the bandwagon and remain competitive in this new realm of marketing.


How Retailers Can Make AI The Face Of Their Digital Brand

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That means using it for two distinct purposes: first, helping customers find what they are looking for; second, helping them find things they don't yet know they're looking for. With an eye on these trends, leading retailers are exploring how AI can help their customers find what they need by improving reviews and providing more sophisticated recommendations on the website. As AI makes online shopping easier, customers are less likely to visit stores because they need a "commodity" product that can easily be ordered from home, such as laundry detergent, and more likely to go for the pleasure of the experience. In the coming years, as AI becomes increasingly entrenched in the everyday lives of consumers, the leading chains will use AI to win retail's ultimate prize: turning their customers into fans.


Voice-Activated Banking Then, Now And Soon PYMNTS.com

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The solution has been secure, but not perfect: In May, an HSBC customer's non-identical twin managed to breach his brother's account by mimicking his twin's voice. The bank behemoth may have been late to the game, but it used that to its advantage, learning from the other banks' mistakes and leap-frogging the simple account balance checks to immediately offering the ability to transfer funds by voice. Gadget reported that 79 percent of bankers believed artificial intelligence (AI) would revolutionize how banks interact with and learn from customers, according to an Accenture poll, and 76 percent believed AI would soon become the primary point of contact between banks and customers. As Gadget noted, voice technology specifically and artificial intelligence generally will give banks a fresh opportunity to customize their banking experience with tailored recommendations and advice, such as suggesting ways to save more if it detects a customer has had a salary increase.


How Machine Learning is Changing Recruiting - TalentCulture

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Let's explore how machine learning is changing recruiting. From all that data, Belong generates a tailored, SERP-esque database of matches, each unique to the company and the position. Belong's method reportedly gets a minimum of a threefold increase in company-candidate engagement rates. Shelly Kramer is a 20 year marketing veteran and CEO of V3 Broadsuite, a marketing consultancy, and the President of Broadsuite Media Group.