Personalization Flashcards
is “a process that
creates a relevant, individualized interaction between two
parties designed to enhance the experience of the
recipient.”
personalization (According to Gartner)
is the act of tailoring an experience or communication based on information
a company has learned about an individual
Personalization
What types of experiences can be tailored? Most of the channels in which customer
interactions take place can be personalized. Some of the main ones include:
- Websites
- Mobile apps
- Emails
- Web apps (like a SaaS application)
- Online ads
- In-store/in-branch communications
- Online chats
- Call centers
What kind of information can be acted on to tailor experiences in those channels? It’s
basically an unlimited list that contains any information a company can collect about its
customers and prospects. Some of the most common include:
- Geolocation
- Source (such as search, email, social, paid ad, referring site, etc.)
- Firmographic information for B2B (such as industry, company, revenue, employee
count, technology stack, etc.) - Buyer persona
- Buyer status (e.g. customer or prospect)
- Time of day
- Browser or device type
- Number of site visits, logins, or pages/screens viewed
- Active time spent
- Time elapsed since last visit, email open, call center interaction, etc.
- Purchases made, articles read, videos viewed, etc.
- Lifetime value (LTV)
- Mouse movement (scrolling, hovering, inactivity)
- Affinity toward content and products along with their characteristics (categories, tags,
brands, colors, keywords, etc.) - Email opens and clicks
- Push notification dismissals or click-throughs
It is the simulation of human intelligence processes by
machines, especially computer systems. These processes
include learning (the acquisition of information and
rules for using the information), reasoning (using rules
to reach approximate or definite conclusions) and selfcorrection.
Artificial Intelligence
AI can be categorized as
Weak AI / Strong AI
also known as narrow AI, is
an AI system that is designed and trained for a particular task.
Weak AI
also known as artificial general intelligence, is
an AI system with generalized human cognitive abilities.
Strong AI
allows individuals and companies to
experiment with AI for various business purposes and sample multiple platforms before making
a commitment
Artificial Intelligence as a Service (AIaaS)
Types of Artificial Intelligence
Type 1: Reactive machines.
Type 2: Limited memory.
Type 3: Theory of mind.
Type 4: Self-awareness.
the IBM chess program that beat
Garry Kasparov in the 1990s.
Deep Blue
can identify pieces on the chess board and make predictions, but it has no memory and cannot use past experiences to inform future ones. It analyzes possible moves – its own and its opponent – and chooses the most strategic move.
Deep Blue
An example is Deep Blue, the IBM chess program that beat
Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chess board and make
predictions, but it has no memory and cannot use past experiences to inform future ones. It
analyzes possible moves – its own and its opponent – and chooses the most strategic move.
Deep Blue and Google’s AlphaGO were designed for narrow purposes and cannot easily be
applied to another situation.
Type 1: Reactive machines.
These AI systems can use past experiences to inform future
decisions. Some of the decision-making functions in self-driving cars are designed this way.
Observations inform actions happening in the not-so-distant future, such as a car changing
lanes. These observations are not stored permanently.
Type 2: Limited memory.
This psychology term refers to the understanding that others
have their own beliefs, desires and intentions that impact the decisions they make. This kind of
AI does not yet exist.
Type 3: Theory of mind.
In this category, AI systems have a sense of self, have
consciousness. Machines with self-awareness understand their current state and can use the
information to infer what others are feeling. This type of AI does not yet exist.
Type 4: Self-awareness.
AI Applications
AI in Healthcare.
AI in Business.
AI in Education.
AI in Finance.
AI in Law.
AI in Manufacturing.
The biggest bets are on improving patient outcomes and reducing
costs. Companies are applying machine learning to make better and faster diagnoses than
humans. One of the best known healthcare technologies is IBM Watson. It understands natural
language and is capable of responding to questions asked of it. The system mines patient data
and other available data sources to form a hypothesis, which it then presents with a confidence
scoring schema. Other AI applications include chatbots, a computer program used online to
answer questions and assist customers, to help schedule follow-up appointments or aid patients
through the billing process, and virtual health assistants that provide basic medical feedback.
AI in Healthcare.
AI can automate grading, giving educators more time. AI can assess
students and adapt to their needs, helping them work at their own pace. AI tutors can provide
additional support to students, ensuring they stay on track. AI could change where and how
students learn, perhaps even replacing some teachers.
AI in Education.
Robotic process automation is being applied to highly repetitive tasks
normally performed by humans. Machine learning algorithms are being integrated into
analytics and CRM platforms to uncover information on how to better serve customers.
Chatbots have been incorporated into websites to provide immediate service to customers.
Automation of job positions has also become a talking point among academics and IT analysts.
AI in Business.
AI in personal finance applications, such as Mint or Turbo Tax, is
disrupting financial institutions. Applications such as these collect personal data and provide
financial advice. Other programs, such as IBM Watson, have been applied to the process of
buying a home. Today, software performs much of the trading on Wall Street.
AI in Finance.
The discovery process, sifting through of documents, in law is often
overwhelming for humans. Automating this process is a more efficient use of time. Startups
are also building question-and-answer computer assistants that can sift programmed-toanswer
questions by examining the taxonomy and ontology associated with a database
AI in Law.
This is an area that has been at the forefront of incorporating
robots into the workflow. Industrial robots used to perform single tasks and were separated
from human workers, but as the technology advanced that changed.
AI in Manufacturing.