Machine learning in marketing

In today’s world, where social networks such as Instagram, Twitter, YouTube, and of course websites play the first role in introducing brands and identifying products and services, digital marketing has become the heart of various industries. The digital marketing industry keeps pace with technological advancements, including artificial intelligence, and uses machine learning to enhance customer engagement and collect campaign data to create customized marketing journeys that increase consumer satisfaction and thus maximize company profits. . Here’s how machine learning can be used in marketing: Data, harnessed properly, can help marketers and advertisers better understand customers and automate targeted and precise brand campaigns with unparalleled consumer personalization. In order to give you a better understanding of how to do this, in this article from the artificial intelligence website Avir, we have collected 23 examples of the use of machine learning in marketing. Stay with us until the end of this article.

Applications of machine learning in marketing

From e-commerce to banking to healthcare, organizations and departments in various sectors are using machine learning for their marketing efforts. Machine learning experts can enable marketing automation, enhance marketing campaigns, improve customer experience, and create digital marketing strategies using machine learning in the following ways:

Analyzing customer data;

recording and transcribing sales calls;

Offering products and services to customers according to their tastes and interests;

Mapping social networks of leads (leads);

Mining and analyzing public social media posts.

23 examples of using machine learning in marketing

To better understand the use of machine learning in marketing and marketing, we will further explore the following examples.

1. JPMORGAN CHASE company’s use of artificial intelligence copywriter

JPMorgan Chase, the American multinational banking and financial services company, equipped its marketing team with an artificial intelligence copywriter that produces more customer-friendly content. The financial giant, in partnership with artificial intelligence company Persado, announced that it will use machine learning and artificial intelligence technology to write advertising texts to attract consumers’ attention. Using this software startup’s capabilities, JPMorgan Chase has enjoyed higher click-through rates with its revamped copywriting.

• Smart GONG Income Platform

Gong uses artificial intelligence (including machine learning) to help B2B sales teams close more deals by automatically recording, transcribing and analyzing the content of all sales-based calls, web conferences and emails. Its revenue IT integrates seamlessly with platforms like Salesforce, Office 365 and Slack, creating a seamless experience for sales teams looking to streamline their operations.

• Netflix recommender system

Netflix uses machine learning in its recommender system, as well as for research and A/B testing efforts. The company also uses machine learning to make decisions about which content to add to its streaming platform and to inform the production of original TV series and movies through its film studio.

• Watson, IBM’s artificial intelligence assistant

IBM Business Devices International Inc. offers a suite of artificial intelligence tools that help businesses streamline marketing strategies and customer engagement. IBM’s artificial intelligence assistant, Watson, uses machine learning capabilities to perform audience analysis, personalize one-on-one conversations, and connect with audiences through their preferred channels.

• BLUECORE one to one campaign tool

E-commerce companies can stay one step ahead of customers with the Bluecore platform, which personalizes online shopper interactions. Artificial intelligence and machine learning drive one-to-one conversations and recommend products to customers across a range of channels. Automated predictive intelligence also gathers information about ideal ways to reach customers; So teams can tailor marketing activities to audience preferences.

• Use of AEROSOLVE product in AIRBNB

Airbnb, a virtual marketplace for accommodation rentals, hosts several open source products, including Aerosolve, which is a machine learning library. This library is ideal for implementing algorithms with easy-to-interpret features such as keyword searches and filters for vacation rentals. Aerosolve is the same library that Airbnb uses to predict the probability of booking and offer prices to its hosts.

• Customer service chatbot powered by ADA company’s artificial intelligence

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

• GUMGUM Text Intelligence Platform

As part of its partnership with Appen, the text intelligence company GumGum has used artificial intelligence and machine learning to determine the ideal web pages and digital spaces to serve ads. Verity serves as the company’s contextual intelligence platform that 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 brand with irrelevant or controversial content.

• STRONG ANALYTICS platform for creating machine learning applications

The Strong Analytics platform makes it easier for marketers to develop personalized content and campaigns with a machine learning-based platform. A combination of artificial intelligence, analytics, and machine learning tools enables teams to gather data on customer behavior, predict future needs, and tailor marketing efforts to meet those needs. Additionally, marketers can rely on the Strong Analytics platform to help them rapidly deploy machine learning applications and streamline their operations.

1. PEOPLE.AI sales automation tools

People.ai sales automation tools use machine learning algorithms; These algorithms free up time for the sales and marketing professionals who use them. With the company’s data platform, teams can gather information from various interactions to determine who to contact to increase revenue streams. The company’s platform also sends timely alerts based on artificial intelligence; So teams know which accounts to focus on to close deals.

1. APPLECART social graph platform

Applecart’s Social Graph Platform finds promising leads – and their connections – that lead to more effective marketing campaigns. After gathering 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 quickly map out social media leads and tailor their content to these audiences.

1. BRANDFOLDER brand smart tool

Working behind the scenes, Brandfolder makes it easier for teams to find marketing assets with the Brand Intelligence platform. The platform uses artificial intelligence, natural language processing and machine learning algorithms to tag creative assets, understand how they are organized and recommend ways to categorize them. Teams and managers and stakeholders can save time and energy in locating assets in a healthier marketing ecosystem.

1. Real Estate Marketing Tools from YLOPO

Ylopo, a digital marketing technology platform for real estate agents, incorporates various components including social media marketing, targeted demographic and psychographic advertising, big data and artificial intelligence into its digital marketing solution product. RAIYA’s AI agent combines natural language processing and machine learning to conduct conversations with customers and guide them throughout their property search.

1. DRIFT conversation cloud platform

Drift helps businesses connect with existing and potential customers through its AI-powered platform. Powered by machine learning, Drift’s cloud chat platform engages with site visitors and potential buyers to answer questions, close deals and encourage future visits. The platform’s chatbots also record statistics and information during each conversation, so companies can understand customer needs and better serve visitors.

1. ACQUIA Marketing Cloud Data Platform

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 specific behaviors; So marketing teams can build accurate insights and buyer personas. As a result, businesses can tailor their products to customer preferences and create unique marketing experiences.

1. Recommended tools from DYNAMIC YIELD

Dynamic Yield uses advanced machine learning to help marketers increase revenue through single-platform personalization, recommendations, automated optimization and one-to-one messaging. When businesses connect their marketing campaigns to the Dynamic Yield platform, they can curate rich data sets and curate content that meets the interests of target audiences.

1. AFFINITIV’S ATLAS DX PLATFORM

Affinitiv’s platform helps auto dealerships and OEMs improve customer service and long-term loyalty with digital services. The company’s Atlas DX platform has rich demographic and behavioral data; So dealers can match their marketing content to the interests of potential and current customers. As a result, teams can determine the best channels to reach audiences and convert them into buyers.

1. Purchase machine learning media from BLISS POINT MEDIA

To optimize marketing campaigns, Bliss Point Media has designed an app that shows where marketers should focus their attention. Machine learning tools collect real-time data, analyze it, and determine which resources are most profitable. Marketers can shape strategies around their target audience while diversifying their channels and methods of outreach.

1. Chatbots generating artificial intelligence from CONVERSICA

Built on an AI platform that combines machine learning with natural language processing and natural language generation, Conversica’s AI assistant automatically contacts and engages leads using natural two-way communication. It brands, conditions them and then follows them. It also fills in lead contact information and keeps the company’s CRM up to date.

• Emotional analysis tools from SWAYABLE

Swayable’s AI allows companies to gauge audience opinions through sentiment analysis. A combination of machine learning and computer vision technology captures consumer reactions to products and tracks broader opinions after data collection. Businesses are using Swayable’s AI to power their marketing campaigns right from the start.

• INSTAPAGE artificial intelligence created landing page copycat

Instapage, a landing page builder, helps marketers design their website with conversion rates in mind. The company uses artificial intelligence and machine learning to analyze ad campaigns and match language with landing pages for more successful conversion rates. AI-generated landing page content saves marketers time and money that would otherwise be spent on rewriting and A/B testing.

• DSTILLERY Custom Audience Artificial Intelligence Tool

Dstillery, an applied data science company, uses machine learning to generate actionable customer insights from its vast database of constantly updated online and offline behavioral profiles. Marketers use Dstillery’s custom AI audience tool to build customer profiles with first-party data and identify relevant leads.

• DOORDASH HISTORICAL MARKETING CAMPAIGN DATA

By using machine learning to study past campaigns, DoorDash offers smarter ways to spend your marketing budget. Machine learning algorithms examine historical data to separate successful campaigns from less successful ones. With a clearer picture of what’s working and what’s not, DoorDash can adjust its marketing strategies and invest in content that better aligns with customers’ needs and interests.

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