UPDATED BY
Matthew Urwin | Jul 06, 2022

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

So declared tech insider Mariya Yao in a 2018 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.”

Machine Learning in Marketing

The digital marketing industry is employing machine learning to boost customer engagement by collecting campaign data to create customized marketing journeys that maximize consumer happiness and company profits.

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.

To give you a better sense of how machine learning is used in marketing, we rounded up 22 examples of companies involved in doing just that.

 

Machine Learning in Marketing Examples

Companies Using Machine Learning in Marketing

  • JPMorgan Chase
  • IBM
  • Bluecore
  • Ada
  • Applecart
  • Drift
  • Bliss Point Media
  • Swayable

 

Founded: 2000

Location: New York, New York

JPMorgan Chase equipped its marketing team with an AI copywriter that produces more customer-friendly content. The financial giant showcases a partnership with Persado, which uses machine learning and AI technology to write ad copy that catches consumers’ attention. By enlisting the capabilities of this software startup, JPMorgan Chase has enjoyed higher click rates with its revamped copywriting.

 

Founded: 2015

Location: San Francisco, California

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. Its revenue intelligence technology integrates well with platforms like Salesforce, Office 365 and Slack, creating a seamless experience for sales teams looking to refine their operations.

 

Founded: 1911

Location: New York, New York

IBM offers a suite of AI tools that helps businesses streamline their marketing strategies and customer interactions. Its AI assistant Watson taps into the possibilities of machine learning to conduct audience analytics, personalize one-on-one conversations and connect with audiences through their preferred channels.

 

Founded: 2013

Location: New York, New York

E-commerce companies can stay one step ahead of customers with Bluecore’s platform, which personalizes interactions for online shoppers. AI and machine learning guide one-on-one conversations and recommend products to customers across a range of channels. Predictive automated intelligence also gathers info on the ideal ways to reach out to customers, so teams can adapt marketing activities to audiences’ preferences.

 

Founded: 2016

Location: Fully Remote

Ada gives companies the ability to deliver consistent, high-quality customer service with a brand interaction platform that displays conversational AI features. Machine learning models enable Ada’s platform to analyze text in over 100 languages and then predict the needs of customers. With this proactive technology, businesses can reduce the time it takes to resolve issues and provide customers with the answers they’re looking for.

More on Marketing20 Big Data Companies Redefining Marketing

 

Founded: 2007

Location: Santa Monica, California

As part of its partnership with Appen, GumGum has leveraged AI and machine learning to determine ideal web pages and digital spaces for posting ads. Verity serves as the company’s contextual intelligence platform, which scans videos, audio clips, images, text and other online elements. With this tool, businesses can place ads on web pages and platforms without accidentally associating their brands with irrelevant or controversial content.

 

Founded: 2015 

Location: Chicago, Illinois

Strong Analytics makes it easier for marketers to develop personalized content and campaigns with a machine learning platform. A combination of AI, analytics and machine learning tools enables teams to compile data on customer behavior, predict future needs and tailor marketing efforts to meet those needs. In addition, marketers can rely on Strong Analytics’ platform to help them quickly deploy machine learning applications and streamline their operations.

 

Founded: 2016 

Location: San Francisco, California

People.ai’s sales automation tools use machine learning algorithms, freeing up time for the sales and marketing professionals who use them. With the company’s data platform, teams are able to compile information from various interactions to determine who needs to be contacted to increase revenue streams moving forward. The company’s platform also sends out timely AI-driven alerts, so teams know which accounts to focus in order to close deals.

 

Founded: 2013

Location: New York, New York

Applecart’s marketing platform locates promising leads — and their connections — leading to more efficient marketing campaigns. After collecting data from public sources, the company’s Social Graph Platform uses machine learning algorithms to determine professional and personal relationships for each individual. Companies can now quickly map out the social networks of leads and tailor their content to these audiences.

 

Founded: 2012

Location: Denver, Colorado

Working behind the scenes, Brandfolder makes it easier for teams to find marketing assets with its Brand Intelligence platform. This platform uses AI, natural language processing and machine learning algorithms to tag creative assets, understand how they’re organized and recommend ways for classifying them. Teams and stakeholders can then save time and energy locating assets within a cleaner marketing ecosystem.

 

Founded: 2014 

Location: Santa Monica, California

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. Its AI agent RAIYA blends natural language processing and machine learning to carry conversations with customers and guide them along their property search.

 

Founded: 2015

Location: Fully Remote

Drift helps businesses forge bonds with customers and prospects through its AI-based platform. Equipped with machine learning, Drift’s Conversational Cloud platform engages with site visitors and potential buyers to answer questions, close deals and encourage future visits. Chatbots also record insights during each conversation, so companies can understand customer needs and better serve returning visitors.

 

Founded: 2007

Location: Boston, Massachusetts

Acquia provides marketers with the data they need to better understand audiences and tailor content to specific target groups. Machine learning features build models and classify customers based on certain behaviors, so marketing teams can form accurate insights and buyer personas. As a result, businesses can adapt their products to customers’ preferences and create unique marketing experiences.

 

Founded: 2011

Location: New York, New York

Dynamic Yield employs advanced machine learning to help marketers increase revenue through single-platform personalization, recommendations, automatic optimization and one-on-one messaging. Once businesses link their marketing campaigns with Dynamic Yield’s platform, they can sort through rich data sets and select content that caters to target audiences’ interests.

 

Founded: 2016

Location: Fully Remote

Affinitiv helps car dealerships and OEMs improve customer service and long-term loyalty with digital services. The company’s Atlas DX platform features rich demographic and behavioral data, so dealerships can match their marketing content to the interests of prospective and current customers. As a result, teams can determine the best channels through which to contact audiences and convert them into buyers.

 

Founded: 2014

Location: Santa Monica, California

To optimize marketing campaigns, Bliss Point Media has designed an application that reveals where marketers should focus their attention. Machine learning tools compile real-time data, analyze it and determine sources that deliver the most revenue. Marketers can shape strategies around their target audiences while still diversifying their channels and outreach methods.

 

Founded: 2007

Location: Foster City, California

Built on an AI platform that blends machine learning with natural language processing and natural language generation, Conversica’s AI assistant automatically contacts, engages, qualifies and follows up with leads using natural two-way communication. It also fills in lead contact information, keeping a company’s CRM up to date.

 

Founded: 2017

Location: San Francisco, California

Swayable allows companies to gauge audience opinions through emotional analyses. A mix of machine learning and computer vision technology captures consumers’ reactions to products and tracks wider opinions after gathering data. Businesses use Swayable’s causal AI to sharpen their marketing campaigns right from the beginning.

More on Machine Learning16 Machine Learning Examples You Should Know

 

Founded: 2012

Location: Austin, Texas

Postclick developed an AI and machine learning platform that focuses on optimizing conversion rates for marketing teams. The company’s Advertising Conversion Cloud tracks the ads users click on and the number of clicks each ad receives. By charting consumer journeys across web pages, Postclick’s platform reveals which ads and web designs best engage users and allows companies to increase conversions after making any necessary changes.

 

Founded: 2008

Location: New York, New York

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. Marketers use Dstillery’s Custom AI Audiences to build customer profiles with first-party data, pinpointing relevant leads.

 

Founded: 2017

Location: Austin, Texas

FunnelAI combines machine learning with broader artificial intelligence and social media to help businesses increase sales opportunities and growth. The company’s search and engagement platform sifts through millions of social posts, identifying potential leads. Organizations can then start online conversations with these prospects, increasing the likelihood of conversions while cutting down time looking for qualified leads.

 

Founded: 2013

Location: San Francisco, California

DoorDash is coming up with smarter ways to spend its marketing budget by employing machine learning to study previous campaigns. Machine learning algorithms review historical data to separate successful campaigns from less successful ones. With a clearer picture of what works and what doesn’t, DoorDash can adjust its marketing strategies and invest in content that resonates more with customers’ needs and interests.

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