Artificial intelligence has moved beyond the buzzword stage since the turn of the millennium, as the novelty of watching IBM’s Watson beat humans at chess and “Jeopardy!” has given way to practical applications. Spending on artificial intelligence by businesses passed $87 billion in 2021 and is projected to hit $1.6 trillion by the end of this decade.
The marketing sector has embraced AI as a powerful tool to deliver a superior user experience for consumers and efficiencies for marketers. It is being leveraged in functions from account-based marketing tasks such as lead scoring, to audience segmentation for media planning, and even some creative disciplines.
AI offers marketers the ability to analyze data, glean insights and target messages at light speed, then craft communications and deliver them, faster and more accurately than humans in many cases. But a common misconception confuses AI with robust data management. Big Data enables AI to gain insights, make predictions and evolve its intelligence, but it is just a part of the whole.
Another common mistake among laypeople (that is, most of us) is confusing machine learning with AI, when machine learning is only a segment of AI. While AI seeks to create a machine that can process information and react like a human being thinks, machine learning creates the equivalent of a service animal that can perform tasks and adapt to variations in those tasks with practice. AI goes a step beyond with deep learning, which copies human thought patterns by taking raw data and studying it, then checking against what the system already knows, in order to make predictions and react in ways that go beyond the if/then rules of traditional computing.
AI is still a young technology, its applications and disciplines constantly evolving. A Gartner survey found only 17% of marketing leaders are using AI and machine learning broadly. With all that runway ahead, spending on marketing AI is expected to grow almost 19% every year for the next five, to almost $23.3 billion by 2027. As Gartner noted, “84% of digital marketing leaders believe using AI/ML enhances the marketing function’s ability to deliver real-time, personalized experiences to customers.”
With these ideas in mind, we are pleased to present our list of the marketing AI companies to watch. Learn more about how AI and machine learning are helping brand marketers target their consumers more efficiently at Brand Innovators’ Future of AI & Personalization Summit in New York on June 8th.
Categories
Targeting/Data Insights
Content Creation
Personalization
Influencer Marketing
- Ada: (Personalization) This startup, named after the “first programmer” Ada Lovelace, leverages AI to automate brand interactions across the customer lifecycle. Ada boasts work with over 320 brands, handling customer experiences such as travel bookings and order tracking, CRM support including converting and upselling new sales leads, and more. The platform integrates existing marketing, sales and customer experience tools and back-end systems for verticals including finance, communications, retail, transportation and others and its integrations library offers code to make Ada’s platform work with apps of companies including Convey, Calendly, Shopify, Magento.
- Albert: (Personalization, Targeting/Data Insights) New York-based, Albert AI offers brands software that autonomously plans, executes, tests, optimizes and evolves paid search, social, and programmatic campaigns. The brand serves clients in retail, luxury, ecommerce, telecom, CPG and financial services.
- Appier: (Targeting/Data Insights, Personalization) Started in Taiwan by a husband-and-wife team in 2012, this software as a service (SaaS) company now has offices in 17 countries and went public in the Tokyo exchange in early 2021. Appier uses machine learning and big data to predict customer behavior and deliver personalized messaging across devices. It works with more than 1,000 clients including in retail, finance, gaming and automotive, and is greatly expanding its presence in the U.S. market, where customers grew 14-fold during the most recent quarter.
- Arena: (Targeting/Data Insights, Personalization) Arena builds machine-learning systems underpinned by Active Learning, a subset of AI where systems try out functions and adapt their responses to improve them. Arena uses deep reinforcement learning, a subset of machine learning that helps systems learn how to take data and make their own decisions and applies it to automate and optimize business functions to create better, more efficient customer experiences. It recently partnered with BEES, the e-commerce platform of Anheuser-Busch parent AB Inbev, to create an AI-based recommendation engine that provides customers personalized inventory recommendations, new product suggestions and promotional offerings.
- BEN Group: (Infuencer Marketing/Content Creation) A Bill Gates company, Los Angeles-based BEN Group serves as an entertainment AI company that works to integrate brands into influencer content, streaming content, music, TV, and film. BEN Group helps brands focus on key strategies across different content platforms to get a true return on their advertising spend. Their custom-built AI is designed to showcase products in unique and influential settings.
- BERA: (Targeting/Data Insights) Backed by investors including former Procter & Gamble CMO Jim Stengel, BERA offers a software-as-a-service product that tries to connect brand investment and business outcomes in a predictive framework. It uses AI to take deep dives into changes in brand equity over multiple dimensions—including geography, competitors and even strong, but non-competitive brands—and turns out actionable insights and predictive intelligence to boost brand performance and business value. In 2021, it signed an agreement with Omnicom Media Group to add its automated metrics and predictive analytics into Omnicom’s Omni marketing operating system.
- Cognitiv: (Targeting/Data Insights) Led by three founders who first met in the fifth grade, Cognitiv uses deep learning to continuously train algorithms to optimize programmatic campaigns and allow marketers to optimize their media at scale, even while a campaign is live. The platform automatically builds a custom algorithm for each marketer that considers the user, the context, the message and the campaign objectives. It leverages data to predict consumer behavior and deliver personalized messages across display, mobile, connected TV and custom audiences.
- Copy AI: (Content Creation) A relative newcomer to the segment, this company founded in 2020 has already attracted multiple venture capital investors with the promise to automate Content Creation with natural language processing. It recently raised $11 million in seed capital with plans to double the size of its team in order to expand the company. Copy AI’s app can produce ad, sales, website and ecommerce copy; blog posts and social media content. The user selects the kind of content required, describes the product and receives results for editing in seconds. The tools support work in 25 languages and offer features such as slogan and blog post idea generators to automate brainstorming for content.
- CreativeX: (Targeting/Data Insights) Originally founded in 2015 as Picasso Labs, CreativeX leverages AI to measure the impact of creative decisions. It analyzes assets such as images, videos and GIFs to get insights about the quality of the creative, brand consistency, compliance, and representation. It maps those assets to attributes that are relevant to the marketer, such as brand’s guidelines or voice, its position in the market, or how it differentiates itself from rival brands. Besides commercial applications, the tools have also been shown effective at analyzing content for issues of diversity and inclusion; it recently formed a partnership with the Geena Davis Institute to give brands the ability to measure the inclusiveness of their creative across gender, race and age range.
- FanAI: (Targeting/Data Insights) Defining the value in sports sponsorships can be a tricky concept and this six-year-old firm specializes in defining the actual return on investment at retail that brands will realize on their sponsorships and how to best drive sales. It counts Coke, AB InBev, PepsiCo and Dunkin among its clients. FanAI’s technology combines exposure, behavioral and purchase data with data from teams, leagues and other sports bodies to help marketers generate reports with insights related to actual purchase behavior and help brands optimize their sponsorships and advertising investments.
- Google Cloud: (Targeting/Data Insights) Google first introduced machine learning into search with RankBrain in 2015, to understand search queries. Over the years, it has expanded its use of AI into a suite of marketing analytics, modeling and insights tools. Vertex AI, Google’s ML platform, integrates with the Big Query data warehouse to generate insights from petabytes of data, and build models using machine learning. Looker, a data application platform based on machine learning, allows marketers to analyze and act on real-time data, and creates data visualizations and dashboards for decision making without requiring data teams to have technical skills to develop them.
- GumGum: (Content Creation, Personalization) Founded in 2008, this “contextual-first” company has been expanded recently, with the acquisition of optimization platform Playground XYZ and the European video marketplace JustPremium. GumGum’s intelligence platform, Verity, uses computer vision and natural language processing to scan images, video and text and check for brand safety, suitability and context. In 2022, GumGum launched The Mindset Matrix, a platform of contextual advertising tools that integrates Verity with a suite of creative tools to execute based on context, and Playground’s attention measurement and optimization solution.
- Helixa: (Targeting/Data Insights) The audience intelligence platform was acquired in late 2021 by Telmar, a provider of media and data analytics solutions, seeking to expand its media planning and audience analysis capabilities. Hellixa’s Discovery platform uses social conversation data to analyze engagement and generate insights into audiences, demographics and psychographics to inform creative, planning, and execution of marketing campaigns. It builds detailed personas to help drive strategy, performs audience segmentation and uncovers influencer marketing opportunities.
- IBM Watson: (Targeting/Data Insights, Personalization, Content Creation) The original AI brand, Watson was early into the application of AI to guide marketing data and automate user experience management. IBM Watson Advertising leverages Watson technology across the whole marketing stack. Watson’s suite of advertising solutions includes Advertising Accelerator, which uses data to predict, assemble and deliver personalized ads; Predictive Audiences, which seeks out new consumers; Advertising Conversations, which uses AI to automate one-on-one consumer communications; and weather analytics and targeting, among other functions.
- Influential: (Influencer Marketing) CEO Ryan Detert stumbled into influencer marketing in the early days of Twitter by creating comedy parody accounts. Today, Influential uses IBM Watson technology to bring together brands and its network of more than 3 million social influencers. It analyzes campaigns across a number of variables of effectiveness including demographics, contextual relevance, psychographics, and gauges a practical return on ad spend, based on how an influencer can drive tangible results, such as increased in-store sales or TV audiences. Most recently, during the Covid pandemic, it teamed up the World Health Organization with influencers to encourage behaviors to stop the spread of the virus.
- Inuvo: (Targeting/Data Insights) Its IntentKey AI technology, originally developed in a machine-learning lab at UCLA, tries to solve a tough question of advertising performance: to understand why consumers consume products and services, not who those consumers are. Built around a consumer privacy approach, Inuvo maps connections between more than 25 million intent-based signals—about people, places, things, products, ideas, or even emotions—to help marketers understand why consumers would be interested in their products or services, and why consumers would be visiting certain web pages. When the reasons match, it places advertising on that page, having profiled more than 95% of the websites that show ads. The technology, designed to work without depending on third-party data or cookies, claims results for clients exceeding goals by 50% on average across both B2B and B2C brand, product and service advertising.
- Invoca: (Targeting/Data Insights, Personalization) With backing from investors including Salesforce Ventures, Invoca has been expanding its “conversational Intelligence” platform across a number of verticals, but it’s still best known for enabling marketing, sales, customer experience, and eCommerce teams to use information gleaned from customer-service conversations. Invoca’s Signal AI tool automates call listening to capture data to inform customer acquisition strategy, align sales and marketing and improve the customer experience. Signal Discovery uses machine learning to understand macro and micro trends in customer conversations and optimize the buyer journey.
- Jasper AI: (Content Creation) The company was originally called Jarvis, until it received a testy letter from Marvel, which did not approve of the founders using the name of Iron Man’s digital assistant. The AI copywriting tool uses natural language processing and machine learning to produce various kinds of content optimized for search engines, including website copy, blog posts and social media posts. Users choose a template for the content, then enter the company name, a product description and some context and choose the tone of the piece, and Jasper generates a draft in seconds. A premium Boss Mode product also writes long-form copy, even books.
- Junction AI: (Targeting/Data Insights) A company that bills itself as AI-as-a-Service, Junction AI offers a platform that combines AI and machine learning to deliver data-driven insights for last-mile decisions. It automates many data wrangling and modeling functions to provide a fast, cost-effective solution to businesses looking to leverage AI in marketing functions. Junction AI applies AI and machine learning to produce sales forecasts, applies data models to predict lead value and lead forecasting and analyzes creative with digital shelf insights for marketing optimization.
- NetBase Quid: (Targeting/Data Insights) The market intelligence company made a strategic move in late 2021 by acquiring social analytics firm Rival IQ to add to its social listening capabilities. NetBase Quid’s suite of tools uses artificial intelligence to process structured and unstructured data and delivers actionable data for business decisions. Its products and services include social listening, media monitoring, and predictive analytics, among other features.
- Persado: (Content Creation) Founded on 12/12/12 by self-described “math nerds,” Persado nonetheless leverages AI to match the right words to messages. Its AI platform uses machine learning and natural language generation to create personalized, relevant content for email, web, mobile, social media, and display ads. In 2021, it was awarded an Honorable Mention in Fast Company’s 2021 World Changing Ideas Awards in the category of Best World Changing Idea North America for its Mindful Narratives program that trained AI to understand the context of the COVID-19 pandemic, and how brands needed to adapt.
- Placer AI: (Targeting/Data Insights) Analyzing location data can be challenging, but with the help of artificial intelligence, Placer helps generate data insights for clients ranging from retailers BJ’s Wholesale and Wegmans to real estate developers Cushman & Wakefield and Tishman Speyer. Its dashboard analyzes foot traffic and dwell times against dimensions including the characteristics of the surrounding area, customer profiles and competitive segment data to optimize engagements and reveal emerging trends.
- Quantcast: (Targeting/Data Insights) As its name suggests, this company was founded in 2006 by quantitative technologists seeking to address what they saw as deficiency of online advertising: accurate data to guide advertising beyond search. ARA, Quantcast’s platform, uses machine learning and AI to query a database of over a trillion online signals in fractions of a second and turns real-time data from over 100 million online destinations into behavioral patterns to deliver relevant advertising for its context. Quantcast claims it can maximize the return on a campaign budget and beat campaign goals by 120% on an average.
- RAD AI: (Influencer Marketing, Content Creation) Rad Intelligence claims to be the first AI platform with EQ, or emotional intelligence. RAD’s technology analyzes the behavior of hundreds of thousands of online consumer touchpoints in real-time and generates content based on real-time engagement metrics. It uses machine learning and natural language generation to create influencer marketing programs across the entire marketing mix including paid advertising, blogs, emails and brand-owned digital properties.
- Salesforce: (Targeting/Data Insights) The sales software giant claims Einstein AI is the first comprehensive CRM solution using AI. Machine learning products automate data management to streamline decision making: Einstein Discover picks up relevant patterns in data and surfaces insights and recommendations; Einstein Prediction Builder forecasts business outcomes, such as churn or lifetime value; and Einstein Next Best Action delivers recommendations to clients and employees directly in the apps where they work. Natural language processing tools glean meaning from communications and deliver relevant answers: Einstein Language classifies intent and sentiment to route inquiries and Einstein bots build and train chatbots to connect to customer data.
- Tellius AI: (Targeting/Data Insights) Tellius was recently recognized for the first time in Gartner’s Magic Quadrant for Analytics & Business Intelligence Platforms as a Visionary. The company’s platform tries to make AI-powered data management accessible to non-technical staff by allowing users to perform ad hoc data exploration, and generate insights using natural language. Teams can query all the data stores connected with Tellius through the dashboard with simple questions such as “why did conversions drop” or “show me revenue growth.” The analysis uses natural language to help users of all levels of data expertise interpret the results.
- The Trade Desk: (Targeting/Data Insights) The Trade Desk put AI technology at the core of Solimar, the new media planning and buying platform that became the largest new product introduction in its history when it launched in 2021. The company built on its stores of programmatic advertising data in 2018 when it launched KOA, its AI engine. Koa gleans audience insights and makes recommendations, manages bidding and automatically selects the best cross-device vendor. Once the campaign is live, Koa optimizes performance and spend to improve reach and reduce wasted spending.
- Unanimous AI: (Targeting/Data Insights) Combining AI with the wisdom of crowds, Unanimous AI’s Swarm AI technology uses the principle of swarm intelligence—the same process that helps fish and bees move quickly together—to enable decision making. It uses AI to amplify the intelligence of business teams addressing business issues; team members connect to the platform and tackle a question together as the algorithm gauges the strength of their responses and guides the group through several feedback loops to a strong consensus. It helps market researchers gain faster, more accurate feedback and marketers achieve better forecasting and predictive intelligence. The technology has demonstrated effectiveness in some high-profile tests, such as accurately predicting the outcome of sports and entertainment events and the 2020 U.S. election.
- Xomad: (Influencer Marketing, Content Creation) This 12-year-old company was an early mover in the influencer marketing space, helping brands, advocacy groups and organizations in the public sector activate social media communicators. It connects through its in-house AI engine to an influencer advisory council platform that arms influencers with analytics, audience demographics, and automated campaign tracking to co-create and deploy campaigns for brands. Recently Xomad supported the launch of the vaccine against Covid-19 by developing a platform to connect influencers and health officials to respond to new developments, such as misinformation or an expansion of vaccine eligibility.
- Zoomd: (Targeting/Data Insights) The 10-year-old marketing technology company vaulted up the ranks of AI in March 2022 when it acquired Albert AI, a platform that uses AI to operate paid search, social and programmatic accounts. Albert processes and analyzes audience and tactical data, allocates budgets and optimizes creative and evolving campaigns across paid search and social media autonomously. It parses data, gathers insights, and autonomously acts on them, across channels, devices, and ad formats.
