20 Machine Learning in Marketing Examples You Should Know

“In the digital age, marketers can’t win without mastering data, analytics and automation.”

So declared tech insider Mariya Yao in a recent Forbes column that enumerated the various ways machine learning can (and should) be employed to improve marketing efforts in today’s data-glutted world.

“In the new economy,” Yao added, “a marketing unit without machine learning mastery operates at a serious handicap.”

As a Technology Review article put it, machine learning (which uses an algorithm to identify and learn from data patterns) helps marketers “radically rethink” their campaigns by anticipating future customer moves and more accurately assessing needs through the scouring of data, the identification of patterns and the creation of “predictive models.”

The ultimate goal: more personalized targeting.

Machine Learning in Marketing

The digital marketing industry is employing machine learning to boost customer engagement through personalization and customization of marketing journeys. Machine learning has been an important tool for marketers to capture campaign data and turn it into experiences that maximize consumer happiness and company profits.

Here are 20 examples of how machine learning is revolutionizing marketing.

OneSpot machine learning in marketing


Location: Austin, Texas

How it’s using machine learning in marketing: Combining machine learning with natural language processing, OneSpot aims to increase brand engagement and content consumption via algorithms that automatically analyze a brand’s content assets.

Industry impact: The company’s most prominent clients include Campbell’s and Delta.

Agreeable Research machine learning in marketing
agreeable research

Agreeable Research

Location: Austin, Texas

How it’s using machine learning in marketing: Agreeable Research employs what are called networked surveys to map and measure relationships between respondents, among other factors. It does this by creating what are called “controlled social networks” from which actionable insights are automatically plucked to reveal the reasoning behind consumer behavior when it comes to purchasing, voting and other things.

Industry impact: Industry feedback about Agreeable’s services includes praise from Digible CEO Reid Wicoff, who claimed it took “less than 30 days for [Digible] to achieve a tangible ROI on our investment.”

Funnel AI machine learning in marketing

Funnel AI

Location: Austin, Texas

How it’s using machine learning in marketing: FunnelAI combines machine learning with broader artificial intelligence and social media to help businesses increase sales opportunities and growth.

Industry impact: The company recently got seed round funding to expand into more verticals.

ZyloTech machine learning in marketing


Location: Cambridge, Massachusetts

How it’s using machine learning in marketing: MIT-born ZyloTech uses machine learning sort through and merge customer data that is then subjected to advanced analytics in order to produce “relevancy-based recommendations” for any type of marketing engine.

Industry impact: The company recently raised $5.5 million in funding.

Frase machine learning in marketing


Location: Boston, Massachusetts

How it’s using machine learning in marketing: Frase combines machine learning with human intelligence to improve research and produce better content that improves human creativity. Its creative community includes news organizations, freelance writers, in-house marketing teams and others.

MarketMuse machine learning in marketing


Location: Boston, Massachusetts

How it’s using machine learning in marketing: A creator of AI marketing and optimization software, MarketMuse’s recently launched Suite enables companies to better plan, analyze, create and optimize content to ensure the reasoning and ROI behind it.

Industry impact: The company recently made it even simpler for companies “to create strategic content plans” via its MarketMuse Suite.

Optimail machine learning in marketing


Location: Chicago, Illinois

How it’s using machine learning: Machine learning helps Optimail enhance the effectiveness of email marketing campaigns by automating their continuous optimization in terms of purchasing, sharing, retention and other factors.

Industry impact: Since its launch in early 2017 at Northwestern University in the Chicago suburb of Evanston, Optimail continues to grow.

PeopleAI machine learning in marketing


Location: San Francisco, California

How it’s using machine learning in marketing: People.ai uses machine learning to augment productivity by building sales automation tools that free up time for employees to focus on more important aspects of their sales and marketing efforts.

Industry impact: The company recently raised $30 million in Series B funding.

Retention Science machine learning in marketing

Retention Science

Location: Santa Monica, California

How it’s using machine learning in marketing: Retention Science uses AI and machine learning to facilitate brand-customer communication by revealing customer trends, interpreting data and increasing the effectiveness of marketing campaigns.

Industry impact: One study by the company revealed that many more online consumers preferred free shipping over a discount due to what’s called the Perceived Value Theory.

Converseon machine learning in marketing


Location: New York, New York

How it’s using machine learning in marketing: With its team of experts in computational linguistics, market intelligence, social business and machine learning, Converseon culls and analyzes data from social media channels to help businesses better respond to customer needs and requests without bias.

Industry impact: Converseon recently released a comprehensive library of pre-built machine learning models “designed to drive enhanced value and use of social listening data.”

Ylopo machine learning in marketing


Location: Marina Del Rey, California

How it’s using machine learning in marketing: A digital marketing technology platform for real estate agents, Ylopo incorporates a variety of ingredients — including social media marketing, targeted demographic and psychographic advertising, big data and AI — into its Total Digital Marketing Solution product.

Industry impact: Realtor.com’s Move Inc. recently invested in Ylopo Inc. and already uses the company’s technology.

Datagran machine learning in marketing


Location: New York, New York

How it’s using machine learning in marketing: Datagran uses machine learning in its AI Suite to help businesses use their data to predict clusters and more effectively target customers via different marketing avenues. Clients also can determine which marketing initiatives are working best via real-time feedback

Industry impact: Datagran recently had a successful $2.35M funding round.                   

Mautic machine learning in marketing


Location: Medford, Massachusetts

How it’s using machine learning in marketing: Mautic’s open marketing cloud lets businesses integrate and personalize digital properties and channels. With its use of machine learning in marketing automation, the company aims to improve content and campaigns.

Industry impact: The year-over-year growth of Mautic’s marketing automation management platform Maestro is pegged at 800%.

PushSpring machine learning in marketing


Location: Seattle, Washington

How it’s using machine learning in marketing: A specialist in mobile marketing that employs advanced machine learning, PushSpring helps advertisers tailor and improve their mobile targeting strategy using verified device-level data.

Industry impact: PushSpring recently entered into a partnership with comScore so the latter’s clients can use its core mobile measurement solution “to analyze and define mobile audiences, and instantly send these audience definitions to PushSpring for same-day campaign execution via the marketer’s DMP or DSP of choice.”

Sailthru machine learning in marketing


Location: New York, New York

How it’s using machine learning in marketing: With the help of machine learning, Sailthru helps companies with centralized and automated email management that can personalize a massive amount of messages via the use of proprietary algorithms.

Industry impact: Sailthru recently released its second annual Retail Personalization Index based on survey feedback from 13,000 consumers.

Dstillery machine learning in marketing


Location: New York, New York

How it’s using machine learning in marketing: An applied data science company, Dstillery employs machine learning to produce actionable customer insights from its sprawling database of constantly updated online and offline behavioral profiles.

Industry impact: Dstillery recently partnered with marketing measurement company Commerce Signals. Per a release, the partnership “combines Dstillery’s fresh and dynamic audiences with Commerce Signals’ ability to quickly bring sales data to market, helping accelerate incremental sales for brands and retailers.”

Primal Digital machine learning in marketing
primal digital

Primal Digital

Location: Aurora, Colorado

How it’s using machine learning in marketing: Deploying machine learning as part of its hotel digital marketing process, Primal Digital helps properties to enhance their marketing efforts through paid search, SEO, email, social media and other means.

Industry impact: According to a company case study, “Primal Digital Helped Hotel X Thailand increase their market position and cross-selling opportunities while reducing market spend.”

Intentwise machine learning in marketing


Location: Evanston, Illinois

How it’s using machine learning in marketing: Machine learning enables Intentwise to offer automated downloads and dashboards for different types of marketing campaigns. Other benefits: automated access to extremely specific performance data; automated bid recommendations and management; and algorithms that recommend new keywords based on search data.

Conversica machine learning in marketing


Location: Foster City, California

How it’s using machine learning in marketing: Built on an AI platform that blends machine learning with natural language processing and natural language generation,  Conversica’s AI Sales Assistant automatically contacts, engages, qualifies and follows up with leads via natural two-way communication.

Industry impact: Conversica recently raised $31 million in a growth round and is now valued at about $300 million.

Dynamic Yield machine learning in marketing
dynamic yield

Dynamic Yield

Location: New York, New York

How it’s using machine learning in marketing: Dynamic Yield employs advanced machine learning to help marketers increase revenue through single-platform personalization, recommendations, automatic optimization and one-on-one messaging.

Industry impact: The company recently partnered with AI digital experience insights platform ContentSquare to help companies more effectively determine customer intent so they can make better decisions about personalized marketing tactics.

Gong machine learning in marketing


Location: San Francisco, California

How it’s using machine learning in marketing: Gong employs AI (including machine learning) to help B2B sales teams close more deals by automatically recording, transcribing and analyzing the content of all sales-oriented calls, web conferences and emails.

Industry impact: Gong recently landed on crn.com’s roundup of “10 Coolest Machine-Learning and AI Startups Of 2018.”