Understanding Artificial Intelligence Marketing: Approaches and Techniques

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What Is Artificial Intelligence Marketing?

In marketing, artificial intelligence (AI) is the process of using data models, mathematics, and algorithms to generate insights that marketers can use. Marketers use insights gained from AI to guide future decisions on event spending, strategy, and content topics. AI also makes it possible to measure and optimize marketing activities without human intervention.

AI marketing uses both classical machine learning algorithms and neural network methods to analyze patterns in large volumes of customer and user data, such as purchases, web visits, clicks, and product usage. Insights are provided to marketers through dashboards, reports, and recommendations.

AI marketing can be used at all stages of the marketing process:

  • Planning and strategy
  • Product personalization
  • Promotion
  • Performance and tracking

Marketers use artificial intelligence in one of two ways. One is to use an existing marketing technology software with artificial intelligence capabilities. The other is to use in-house or outsourced development resources to implement artificial intelligence algorithms and technologies specifically customized to their needs.

Why Is AI Marketing Important?

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The recent CMO Survey reported that marketers are seeing an increase of 27 percent in active use of AI technology in their marketing programs and expect to see an increase of 59 percent in the usage of AI in the next few years.

A primary reason for the importance of AI marketing is that the insights it provides can help marketers increase the effectiveness of their campaigns and achieve a faster return on investment (ROI).

Another key reason is that in today’s digital economy, personalization is critical to remaining competitive. Personalizing products and online experiences at scale is difficult or sometimes infeasible, and AI is particularly suited to this challenge.

Core Elements of Artificial Intelligence Marketing

AI marketing solutions have a dual challenge. On the one hand, they need to make use of Data Science techniques and advanced algorithms to generate insights from existing datasets. On the other hand, they need to be practical and easy for marketers to use in their day-to-day jobs.

Marketing AI solutions that meet these challenges have three main components: big data, machine learning inference, and integrated toolkits.

Big Data

AI solutions ingest big data from a variety of sources, such as customer relationship management (CRM) systems, web analytics, or third-party data providers. They can be trained to comb through the data to identify patterns or insights that can benefit marketing programs, much like a human analyst would.

AI training relies on thousands of real-world examples, which the algorithm uses to build a cognitive model, which it can then apply to new, unseen data points.

Machine Learning Inference

Once an AI solution has ingested data and trained a model, it enters the inference stage, in which it can identify trends and predict customer reactions to various signals. AI can operate in real-time, providing outputs such as the best ad to show a specific consumer or the parameters of an offer that will cause a specific customer segment to buy.

AI can also analyze large datasets to identify details important for marketers. For example, it can automatically extract a list of customers who are likely to respond to a specific promotion or predict future trends for a large number of products to help make a strategic decision about marketing budgets.

Integrated Toolkits

At the end of the day, even the smartest AI system will not be usable if it is not integrated with a marketer’s existing stack of workflows and toolkits. AI marketing solutions must be delivered as toolsets that marketers can easily access and use.

In many cases, AI can be delivered as an enhancement to existing tools — for example, a new panel on an existing dashboard that delivers a new type of insights or a widget added to a CRM system that provides AI-driven analysis of customer data.

Benefits of Artificial Intelligence Marketing

Here are several ways AI marketing can help marketers drive better results.

Increased Marketing ROI

AI software can provide actionable insights in real-time. These insights are delivered to marketers, who can then decide how to utilize the information. AI platforms can also act on these insights, leveraging the information in real-time.

For example, AI can analyze ad placements and optimize for high performance at the lowest cost. The software then intelligently distributes funds across various channels, continuously implementing intelligent budget allocation processes to improve marketing ROI.  

Personalized Content Delivery

AI systems can go beyond simple customer segmentation, analyzing the individual profile of each existing and potential customer. If regular audience analytics provides demographic information, hyper-personalized AI processes provide information about each individual.

eCommerce websites, for example, leverage AI marketing processes to deliver personalized content tailored to the unique tastes and needs of the user. Streaming services, like Netflix, use hyper-personalization to provide personalized content suggestions to each user.

Improved Campaign Reporting and Measurement

Aggregating and analyzing the large volumes of data generated from today’s marketing activities can be difficult. Marketers can find it challenging to create meaningful reports and prove the success of their campaigns.

With AI-assisted dashboards, marketers can fully understand the elements of the activity they are working on, identify successful patterns, and adjust their activities accordingly to improve results. AI can also be used to build smart reports that can help communicate the value of marketing activity to management.

Artificial Intelligence Marketing Methods

Here are a few practical ways AI can help marketers in their day-to-day jobs.

Sales Forecasting

Marketers can use AI to process and analyze data about customer transactions and interactions. AI can analyze any type of data, including unstructured data like phone calls, meetings, and emails. AI marketing solutions can help predict the sales outcomes of different sales and marketing activities.

Customer Insights

Artificial intelligence marketing can help analyze customer expectations. By analyzing consumer behavior, AI can predict which customers need your products the most and when. Digital marketers can automatically create profiles and segments and target them with personalized offers.

Personalized Pricing

Artificial intelligence marketing can also help digital marketers personalize prices to individual customers and situations. In this strategy, retailers set product prices based on the needs of their audience.

One example is a ride-hailing application, in which the cost of a ride is dynamically computed according to the current availability of drivers and other transportation options in the area. Another example is an eCommerce site in which prices can be automatically adjusted to current demand on the website or in the industry in general.

Content Creation

AI can be used to generate content. At this point in time, AI algorithms cannot replace human writers but can produce simple blog posts and news releases. Conversational AI is widely used to communicate with prospects online and answer common questions. Digital marketers can also use AI marketing solutions to analyze content performance and predict content topics that will be successful in the future.

Automated Ad Targeting

Marketers can automate the advertising buying and selling process, using data generated from cookies delivered to visitors of apps and websites. Artificial intelligence is useful because it can effectively identify and target a large number of very specific audiences. For example, Facebook Ads uses AI to target and retarget customer ads and is able to automatically create “lookalike” audiences that resemble a company’s current customers.


Artificial intelligence marketing is not a futuristic concept — it is already deployed in the field and provides practical tools that help marketers save time and gain new insights about customers and campaigns.

Still, beyond the immediate benefits, we are only scratching the surface of AI marketing. In the future, human-machine collaboration will create new types of marketing activities and new marketing roles.

Just like the digital age introduced the digital marketer, the AI revolution will create new marketers savvy in Data Science techniques, who can create and leverage AI algorithms to transform marketing programs.

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