AI Terminologies for Marketers

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AI Terminologies For Marketers
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• Artificial intelligence, more commonly known as
  AI, is continuing to make a big impact in popular
  culture as well as numerous industries.

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• Examples includes chatbots that acts as customer
  service representatives, personalized
  recommendations for customers based on past
  buying history, and automated driving machines.
  To say that AI is impacting the world at large is
  quite an understatement. However, marketing has
  been slow to adapt to AI and realize its many
  benefits.

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• When you first start using AI, it might seem
  like youre speaking a different language. In a
  sense, you are. Thats why its important to
  master its terminology as well as its basic
  functions. Below are terms and definitions that
  everyone working with AI should take the time to
  master.

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Algorithm

• The term algorithm describes a formula that
  represents a relationship that exists between two
  or more variables. Its helpful to think of
  algorithms as a list of instructions that include
  a finite end with the purpose of producing an
  output.

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• A recipe is an everyday example of a common
  algorithm. Its ingredients are the inputs that
  design a specific output such as an apple pie.
  With AI machine learning, a computer uses
  algorithms to make predictions.

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• In marketing, it creates buying suggestions
  based on a consumers past actions to spur him or
  her to buy the suggested item. For example, a
  website visitor will see an ad for a smartphone
  on other sites on the Internet if he or she
  spends time viewing this product online.

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Chatbots/Bots

• A bot, short for chatbot, is a computer program
  within a website or phone application that
  directly interacts with users to assist them with
  simple questions and tasks.

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• Many companies currently use bots for customer
  support, although their use in other areas is
  also growing.

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Cluster

• A cluster is a group of people with common
  demographics or characteristics. AI goes through
  data to determine patterns and make connections
  that a human might easily miss. Marketers can use
  clusters to identify their target audience, thus
  creating new marketing opportunities through
  things the people have in common.

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Cognitive Science

• Cognitive science combines topics such as
  anthropology, linguistics, neuroscience,
  philosophy, and psychology with AI. This helps
  marketers understand how the human mind functions
  so they can program a machine to simulate the
  actions and thoughts of people.

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Machine Learning

• Machines can teach themselves with only minimal
  programming from humans.

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• They can sift though huge amounts of data to
  pick out groupings and patterns of interest to
  marketers. They can then select target audiences
  and decide when to take certain actions based on
  the machines input.

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Deep Learning

• This is a more complex version of machine
  learning. It enables computers to teach
  themselves with little human programming.
  Marketers can use deep learning data to predict
  how consumers might respond to certain products
  and services.

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Image Recognition/Computer Vision

• AI makes it possible to program a computer so it
  can accurately analyze an image. It searches for
  image patterns to identify things that a person
  might miss.

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Natural Language Processing (NLP)

• NLP makes it possible for machines to understand
  spoken language, whether a person is speaking or
  using text. The most sophisticated NLP programs
  can interpret speech in a variety of languages.
  Even more impressive, it understands the actual
  spoken words as well as their context and
  possible hidden meanings.

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Neural Networks

• AI technologists have created neural networks to
  mimic the human brain. For example, it can
  analyze handwriting and identify people in
  pictures based on deep learning and natural
  language processing.

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Semantic Analysis

• Semantic analysis is a sophisticated form of NLP
  that focuses on how people string words together
  as well as how they understand language in its
  cultural context. This could be useful in
  creating blog posts and eBooks and has the
  potential to replace content marketers or human
  writers.

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Supervised Learning

• This type of machine learning requires human
  input to function. A person inputs data into the
  machine and then supervises the process as the
  computer forms one or more desired outcomes.

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Unsupervised Learning

• In contract, machines with unsupervised learning
  capability require minimal or no assistance from
  humans to come up with conclusions based on
  patterns it has uncovered.

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• As you can see, many of these terms overlap and
  have related meaning. You should become familiar
  enough with them to understand how any one of
  these technologies can affect your marketing
  efforts. We are happy to answer your questions at
  any time at Call Sumo and look forward to helping
  your company experience explosive growth with AI.