As consumers get more comfortable with AI and understand its ability to improve their lives, companies are making investments to improve key supporting technology, such as translation, algorithms and discovery.
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In IBB Consulting’s work with media companies, we’ve identified three key areas where opportunity exists to integrate AI and machine learning to improve the customer experience, boost revenues, increase productivity and more. From chatbots and content creation to new levels of personalization, the following areas are opportunities to integrate AI into everything from consumer-facing properties to internal functions.
Chatbots For The Customer Experience & Engagement Win
AI-driven chatbots can already interact with people on the web or on mobile to help find information, answer questions and sell services. We’re early in the game when it comes to how they will be deployed, with the goal being to ultimately get to a place where communicating with a chatbot feels no different than chatting with a real person. Most customer requests and issues are basic and can be handled by programming chatbots to understand questions and trigger words, then provide answers by querying specific data sources. From a customer care perspective, chatbots and virtual assistants can be a cost-effective way to meet the needs of customers any time of day, with no wait. If necessary, chatbots can be programmed to hand off to a human agent should the conversation become too complicated. Over time, this will not be necessary as machine learning drives continuous improvements and the chatbot’s understanding of how to address an issue it once could not.
Content That Creates Itself
AI can also serve the role of content creator. It’s not going to start writing TV scripts, but today, AI is smart enough to pull data from multiple sources to generate financial reports, sports commentaries and brief event summaries, it can aid in research or even basic content creation. However, while AI can report facts, it cannot add emotional responses or opinions. It also struggles to create detailed storylines. As machine learning continues to evolve, media companies can lean on the technology to produce other kinds of content, such as series and movie reviews that pull from, and aggregate in a cohesive story, what consumers are saying on social media.
Getting More Intelligent About Personalization
Today, personalization is a major differentiator as media properties compete for customers. Viewers are favoring tailored recommendations, like Spotify’s Discover Weekly. Netflix’s recommendation algorithm has been estimated to save the company $1B annually by keeping users engaged and reducing churn. AI can be used to customize service interfaces or web homepage experiences, hiding content that would not appeal to a certain customer, while putting a spotlight on precisely what will keep them watching, listening or clicking for long periods of time. AI can also be trained over time to offer recommendations that are personalized, but not too personal (aka creepy).
read more – copyright by v-net.tv
As consumers get more comfortable with AI and understand its ability to improve their lives, companies are making investments to improve key supporting technology, such as translation, algorithms and discovery.
copyright by v-net.tv
Chatbots For The Customer Experience & Engagement Win
AI-driven chatbots can already interact with people on the web or on mobile to help find information, answer questions and sell services. We’re early in the game when it comes to how they will be deployed, with the goal being to ultimately get to a place where communicating with a chatbot feels no different than chatting with a real person. Most customer requests and issues are basic and can be handled by programming chatbots to understand questions and trigger words, then provide answers by querying specific data sources. From a customer care perspective, chatbots and virtual assistants can be a cost-effective way to meet the needs of customers any time of day, with no wait. If necessary, chatbots can be programmed to hand off to a human agent should the conversation become too complicated. Over time, this will not be necessary as machine learning drives continuous improvements and the chatbot’s understanding of how to address an issue it once could not.
Content That Creates Itself
AI can also serve the role of content creator. It’s not going to start writing TV scripts, but today, AI is smart enough to pull data from multiple sources to generate financial reports, sports commentaries and brief event summaries, it can aid in research or even basic content creation. However, while AI can report facts, it cannot add emotional responses or opinions. It also struggles to create detailed storylines. As machine learning continues to evolve, media companies can lean on the technology to produce other kinds of content, such as series and movie reviews that pull from, and aggregate in a cohesive story, what consumers are saying on social media.
Getting More Intelligent About Personalization
Today, personalization is a major differentiator as media properties compete for customers. Viewers are favoring tailored recommendations, like Spotify’s Discover Weekly. Netflix’s recommendation algorithm has been estimated to save the company $1B annually by keeping users engaged and reducing churn. AI can be used to customize service interfaces or web homepage experiences, hiding content that would not appeal to a certain customer, while putting a spotlight on precisely what will keep them watching, listening or clicking for long periods of time. AI can also be trained over time to offer recommendations that are personalized, but not too personal (aka creepy).
read more – copyright by v-net.tv
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