What Is Machine Learning? And, How Can I Use It For Digital Marketing?

•

3 likes•229 views

Machine learning is a subset of artificial intelligence that can learn from vast data sets, make accurate predictions, and even take decisions. That makes it a hugely powerful tool for digital marketing, along with other area of technology. In particular, machine learning can deliver better performance through remarketing. This presentation covers: - What is machine learning? - How can machine learning deliver better marketing results? - What is remarketing? - How do machine learning and remarketing work together?

What Is Machine Learning? And, How Can I Use It For Digital Marketing?

https://mailchi.mp/16ff381c064c/hi-tech-signup

(https://www.clickz.com/resources/the-state-of-marketing-measurement-attribution-data-management/ )

Google’s self-driving cars and robots
get a lot of press, but the company’s
real future is in machine learning, the
technology that enables computers to
get smarter and more personal. – Eric
Schmidt

https://cloud.google.com/natural-language/

Sixty-one percent of respondents said no, they did
not want tailored ads for products and services, 56
percent said no to tailored news, 86 percent said no
to tailored political ads, and 46 percent said no to
tailored discounts.
People consent because they have no choice.

In this example, the user is interacting with three value propositions and
the current state of his/her interactions are represented by the shaded
circles. The user has seen one impression of the first value proposition
(state 1), has downloaded the second value proposition (state 3), and has
not seen any impressions of the third (state 0).

Your site must be:
An e-commerce site
Generating 500 monthly transactions
Attract 10,000 daily pageviews

https://www.technologyreview.com/s/613063/ai-ethics-mit-college-of-computing-tech-humanities/

https://growthbadger.com/remarketing/
https://searchengineland.com/10-top-retargeting-tips-adwords-users-222603

Similar to What Is Machine Learning? And, How Can I Use It For Digital Marketing?

Psybotics - Impact Plan (1)

Xavier Edokpa

Psybotics proposes to address the lack of communication and coordination between robots through two solutions: systems integration services and product development. The systems integration services will offer integration for both mobile and stationary robots, while their initial product, a mapping product, will provide robots with social mapping capabilities to continually update a shared map of locations and obstacles. Unlike competitors, Psybotics will provide customization, plugin adaptability and shared awareness across mobile and stationary systems. To achieve success, Psybotics will need $3 million - $1 million for systems integration and $2 million for product development comprising four teams: systems integration, product development, marketing, and legal/administration/finance.

[Whitepaper] Robots in Recruiting - The Implications of AI on Talent Acquisition

Appcast

Cookies, FLoC & GDPR: Marketing Impact

CMassociates

CCPA and the Future of Privacy-First Digital Advertising

The Media Kitchen

What is CCPA? The California Consumer Privacy Act (CCPA) - which goes into effect on January 1, 2020 - grants California residents (“consumer”): ● Control over: ○ What entities are collecting their data ○ What type of data is being collected and for what purpose ○ Who the data is being sold to / shared with and for what purpose ● The ability to delete the consumer’s data and/or stopping any selling/sharing of data Under CCPA, data collection and data sharing become fully transparent to the consumer, and, most importantly, companies must process opt-out requests within 45 days.

Monetizing car-data

Merve Kara

Car data from connected vehicles has the potential to generate $450-750 billion in revenue by 2030. To capture this opportunity, companies must develop a compelling value proposition for customers to share their data. A survey found that customers are most interested in data-enabled features that improve safety, convenience, and save time or money. Over 30 potential use cases were identified, including predictive maintenance, over-the-air updates, and usage-based insurance. Developing business models and the necessary technical capabilities will be key for companies to monetize vehicle data.

Nbtb mmc4300

Michelle Font

The document discusses the Google driverless car, which was invented by Sebastian Thrun after his friend died in a car accident. The car uses sensors, cameras, and radars to navigate roadways without human input. It is capable of reacting to surroundings, maintaining distance from other vehicles, and using GPS. Proposed benefits include fewer accidents from human error, reduced traffic and increased productivity. However, concerns include the high cost, lack of testing in harsh weather, and potential hacking or computer errors. The document also questions if and when driverless cars will replace human drivers.

AI tools and the impact on public relations practice

Chartered Institute of Public Relations

A comprehensive review of AI use within the public relations profession. At time of writing (February 2023), there’s been a burst of new AI-driven tools, services and use cases with the potential to impact virtually every aspect of the public relations profession. This report is an attempt to assess the likely rapid progress of AI technology over the next year and the longer-term strategic considerations for all public relations practitioners as a result. Co-authored by Andrew Bruce Smith and Stephen Waddington, with contributions from Professor Anne Gregory, Jean Valin and Scott Brinker.

ifib Lunchbag: CHI2018 Highlights - Algorithms in (Social) Practice and more

hen_drik

The document summarizes several papers presented at CHI 2018 on the topics of: 1) Understanding user experience of co-creation with AI through a drawing collaboration study. 2) Perceptions of justice and fairness in algorithmic decision-making through experimental studies. 3) A qualitative study of perceptions of algorithmic fairness among marginalized groups. 4) The effects of communicating advertising algorithm processes on user perceptions and trust.

Mit tech review_machinelearning

Abhishek Sood

The document discusses the results of a survey about machine learning adoption among businesses. Some key findings include: - 60% of respondents have already implemented ML strategies, with nearly 1/3 considering themselves mature in their initiatives. - Early adopters are realizing benefits like increased data insights and return on investment. - Common ML projects include image recognition, text analysis, and natural language processing. - While most organizations plan to adopt ML, some lack understanding of how to apply it or secure funding. - Data scientists and C-suite executives are often the champions of ML initiatives within organizations.

Digital Reroutes The Auto Purchase Journey

Stradablog

This document discusses how digital technologies have transformed the automobile purchase journey. It finds that 50-70% of car buyers now choose the make and model before visiting a dealership, with 40-50% making their choice based on online information. The main purpose of dealership visits is now to experience the vehicle in person. OEMs need to adapt by using digital channels more effectively to engage consumers earlier in the purchase process. They also need to rethink strategies around brand engagement, distribution, marketing, and measuring sales performance to better address how digital is changing consumer behavior and expectations.

The state of AI & Chatbots 2018

Gerardo Salandra

The document discusses how chatbots and artificial intelligence will change business. It describes Rocketbots, a platform for creating chatbots, and its founder Gerardo Salandra. The rise of messaging as a preferred communication channel for many is driving the development of chatbots. Chatbots use various artificial intelligence techniques like retrieval-based models and generative models to understand language and hold conversations. While building basic chatbots is now easy, developing truly intelligent ones remains a challenge. The document outlines several examples of chatbots and their applications in areas like finance, social media, and human resources.

[REPORT PREVIEW] The Customer Experience of AI

Altimeter, a Prophet Company

This 3-page document provides an executive summary of a report on how AI is transforming the customer experience. It discusses how AI will become ubiquitous in the next 5 years and profoundly shape interactions with companies through technologies like chatbots and augmented reality. It also outlines some of the key challenges AI poses for customer experience, such as new interaction models, information asymmetry, and the amplification of biases. The summary concludes by emphasizing the need for business leaders to establish principles to ensure AI is developed and applied in a customer-centric manner.

Industry Graph plus IBB plus Discovery 06

James J. Andrus

1) The Industry Graph provides contextual information about competitive industries to enhance searching, discovery, and decision-making. It maps over 16,000 granular industries and the relationships between competitors, suppliers, buyers, and other forces within each industry. 2) The Industry Graph allows users to search for a company like Toyota within a specific industry context, such as the transportation energy industry. This provides relevant competitive intelligence instead of broad results across all industries. 3) Discovery algorithms analyze news, social media, and other unstructured data to surface interesting trends and changes within industries. This helps users gain real-time situational awareness without manually searching large amounts of data.

Government as a Platform and the Digital Front Door

Tim O'Reilly

The Work Ahead in Intelligent Automation: Coping with Complexity in a Post-Pa...

Cognizant

Minne analytics presentation 2018 12 03 final compressed

Bonnie Holub

A large transportation company needed help optimizing their transportation model to reduce costs. Teradata developed a transportation optimization model and user interface tool that takes forecasted volumes and determines the most optimal transportation modes and routes to deliver products to customers while considering capacities, constraints, and business rules. The tool selects the lowest cost solutions for each material/customer pair and allows users to conduct "what-if" analysis of scenarios to further reduce total costs.

How machine learning & artificial intelligence implement in e commerce

Robert Smith

Cmo insights ibm institute for business value

Paul Writer

- The document summarizes insights from a study of 524 Chief Marketing Officers (CMOs). - It finds that CMOs can be categorized into three groups: Traditionalists, Social Strategists, and Digital Pacesetters, with Digital Pacesetters being the furthest along in implementing digital strategies. - Key factors that distinguish the highest performing Digital Pacesetters include their use of advanced analytics to gain deep customer insights, focus on designing rewarding customer experiences, and ability to effectively execute on the customer promise through new technologies.

Stepping Up To The Challenge - CMO Insignt From The Global C-Suite Study

Evgeny Tsarkov

This document summarizes insights from a study of 524 chief marketing officers (CMOs). It finds that: 1) While CMOs are gaining influence, few have built robust digital capabilities, with only 20% setting up social networks and 13% integrating customer touchpoints. 2) CMOs fall into three categories: Traditionalists lacking digital skills; Social Strategists building social media infrastructure; and Digital Pacesetters using data analytics for customer insights. 3) Digital Pacesetters who invest heavily in analytics throughout the customer lifecycle help their companies financially outperform by 43% compared to 25% for Traditionalists.

Stepping up to the challenge - CMO insights from the global C-suite study

IBM Software India

Similar to What Is Machine Learning? And, How Can I Use It For Digital Marketing? (20)

Psybotics - Impact Plan (1)

[Whitepaper] Robots in Recruiting - The Implications of AI on Talent Acquisition

Cookies, FLoC & GDPR: Marketing Impact

CCPA and the Future of Privacy-First Digital Advertising

Monetizing car-data

Nbtb mmc4300

AI tools and the impact on public relations practice

ifib Lunchbag: CHI2018 Highlights - Algorithms in (Social) Practice and more

Mit tech review_machinelearning

Digital Reroutes The Auto Purchase Journey

The state of AI & Chatbots 2018

[REPORT PREVIEW] The Customer Experience of AI

Industry Graph plus IBB plus Discovery 06

Government as a Platform and the Digital Front Door

The Work Ahead in Intelligent Automation: Coping with Complexity in a Post-Pa...

Minne analytics presentation 2018 12 03 final compressed

How machine learning & artificial intelligence implement in e commerce

Cmo insights ibm institute for business value

Stepping Up To The Challenge - CMO Insignt From The Global C-Suite Study

Stepping up to the challenge - CMO insights from the global C-suite study

More from Clark Boyd

Emeritus Insights Live - AI & Business Strategy - 20th Apr 2023.pdf

What Is Machine Learning? And, How Can I Use It For Digital Marketing?

More Related Content

Similar to What Is Machine Learning? And, How Can I Use It For Digital Marketing?

Similar to What Is Machine Learning? And, How Can I Use It For Digital Marketing? (20)

More from Clark Boyd

More from Clark Boyd (20)

Recently uploaded

Recently uploaded (20)

What Is Machine Learning? And, How Can I Use It For Digital Marketing?