These customers know that companies have information about them, and more importantly, they know what companies could do with this information to  customer service experience. For example, millennials are obsess with the customer service experience (ie everything should be simple, fast and smart). This is a list of some practical examples of how AI is transforming business processes.   Learning, responding and pricting  bason the largest amount of artificial intelligence for sales AI offers greater productivity for sales teams by allowing them to focus on opportunities that can be taken to success, as well as saving time for sales staff during the registration of information. Let’s look at some examples below.

Automatically captures sales activities, which means sales staff don’t have to spend time populating the CRM database; Automatically records customer data, for example, website browsing logs that our society generates and stores. These systems are capable of and website connections, among others; Suggest the best follow-up action and recommend email responses by connecting CRM information to inbox; Lead Predictive Valuation: Using predictive analytics, the system will be able to indicate the likelihood of a lead turning into a sale. More interestingly, the system will tell you why this score was reached (eg, lead access channel, industry, etc.).

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For example, Salesforce Einstein lead Cambodia phone number scoring functionality. Artificial intelligence for Customer Service Automatic classification of customer service cases, which avoids relying on the customer service agent to make a decision and therefore saves the agent time. Automatic Case Routing Once the call has been automatically classified, the system can now forward the call to the best qualified agent to determine the type of problem. Recommendation of solutions and knowledge bases. This increases the productivity and quality of a service by suggesting the solution most likely to solve the customer’s problem.

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Self-service communications. Research shows that the current generation of customers prefers self-service (eg, customer portal or app) over calling a call center. Thanks to AI, service communities will be smarter, for example, by personalizing the environment that depends on the customer and automatically suggesting solutions, eg. use image recognition to identify the product that is in a photo taken by the customer. For example, chatbots allow the customer to send text messages to establish communication. artificial intelligence for marketing Marketing is a discipline that has become increasingly analytical and quantitative over the years.

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AI ​​and Predictive Analytics techniques are primarily appli in Marketing, for example, predictive modeling for customer migration, purchase probability, and clustering models for customer segmentation. Here are some of the new advances in AI in marketing, specifically some features of Marketing Cloud Einstein . Predictive (AI): complex systems that manage to process and analyze all the data email scoring: allows marketers to know (before launching an email marketing campaign ) how likely their customers are to respond to the campaign; or else abandon it. The goal here is to anticipate customer response to deliver personalized tours; Predictive audiences.

Based on the predictive score, it will be possible to better segment your customer . And prospect base based on predictive behavior by grouping together people who have common points. The higher the segmentation, the better the conversion. Send time optimization: is it better to send a campaign at 2 pm or 4 am? With Send Time Optimization, the AI ​​algorithm will tell you the time when each contact in your . Customer base is most likely to open an email and engage with your campaign. Artificial Intelligence is transforming our lives and will rapidly revolutionize the way we work. Do you want to know more? Check out the eBook Artificial Intelligence for CRM: A Practical Guide to Everything You Need to Know. Copyright ALBERT EINSTEIN used with permission of the Hebrew University of Jerusalem.

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