AI Glossary Terms Every Fast-Paced Marketer Needs to Know

The term ‘artificial intelligence (AI)’ can conjure up diverse images. Maybe you picture robots from sci-fi movies, or perhaps you think of chatbots you’ve interacted with online. But what if you’re a seasoned marketing professional who’s comfortable with tried-and-true methods?

While sticking to what works is understandable, AI offers a treasure trove of innovative tools and solutions to boost your marketing strategies – from content creation and research to social media, video marketing, and beyond. This comprehensive AI glossary for marketers will equip you to work smarter and faster by exploring essential AI-related marketing terms.

Here’s a breakdown of key AI terms marketers should be familiar with in 2024. Ultimately, knowing the terms related to artificial intelligence – and developing your marketing toolkit – should help you get more done, faster, with much better results.

A – F AI Terms for Marketing

AI (Artificial Intelligence)
AI refers to the simulation of human intelligence processes by machines, including learning, reasoning, problem-solving, perception, and language understanding. In marketing, AI technologies automate tasks, personalize customer experiences, analyze data, and optimize campaign performance.

A/B Testing with AI
Imagine A/B testing two headlines for a blog post. AI analyzes which one performs better in terms of clicks and engagement, helping you choose the winner and maximize your content’s impact.

AI Apps
AI apps utilize LLM technologies to perform tasks that typically require human intelligence, including learning, reasoning, problem-solving, understanding natural language, and perception. These apps are used across various industries to enhance efficiency, automate processes, and provide advanced insights. Key examples include virtual assistants like Siri, Google Assistant, and Alexa, as well as customer service chatbots.

Another example is Similarweb’s app intelligence, which is powered by proprietary app data from multiple sources, provides insights into millions of apps across both iOS and Android in over 25 countries. This includes insights on AI apps and any other apps you’re interested in. You can use it to leverage a full suite of mobile app data points to stay ahead of the competition, spanning usage and engagement metrics, retention, app store ranking, and daily performance insights.

AI Chatbots
Chatbots powered by AI can answer customer questions 24/7 on a company website, automate lead generation through chat interactions, and personalize product recommendations, creating a smoother customer experience.

AI-powered Content Creation
Marketers can use AI to generate content ideas, write drafts, and optimize content for different audiences. This saves significant time and resources, allowing you to focus on strategy and refinement.

Algorithm
Think of an algorithm as a set of instructions a computer follows to solve a problem or perform a task. In marketing, algorithms analyze data to predict trends, personalize recommendations, and optimize campaign performance across various channels.

Attribution Modeling with AI
By understanding which marketing channels (social media, email marketing, etc.) are driving the most conversions (customer purchases, sign-ups), marketers can optimize their budget allocation and focus on the most effective strategies. AI-driven attribution modeling helps with this by analyzing customer journeys and pinpointing the touchpoints that lead to conversions.

AR (Augmented Reality)
An interactive experience that combines the physical world with digital elements in real-time. Marketers use AR technology to create immersive brand experiences, showcase products in 3D, and engage customers through interactive storytelling and gamification.

Automation
The use of technology to perform tasks or processes with minimal human intervention. In marketing, automation tools and platforms help streamline workflows, optimize repetitive tasks, and deliver personalized messages at scale, improving efficiency and driving results.

Big Data
Big data refers to large volumes of data, both structured (website analytics, purchase history) and unstructured (social media conversations, customer reviews). Marketers leverage big data analytics to understand customer behavior, segment audiences, personalize campaigns, and make data-driven decisions to achieve marketing objectives.

Chatbot Analytics
The process of measuring and analyzing data generated by AI chatbots to gain insights into user interactions, engagement metrics, and performance indicators. Chatbot analytics help marketers understand user behavior, optimize chatbot workflows, and improve conversational experiences to drive business outcomes.

Content Personalization
Personalization in content is crucial for advancing customer relationships, boosting sales, and driving long-term growth. It demonstrates a deep understanding of your customers’ needs, encouraging repeat business. By delivering tailored content based on preferences, behavior, and website demographics, AI-powered algorithms analyze user data in real-time to create personalized recommendations, emails, website experiences, and advertisements, thereby increasing engagement and conversions.

Conversational AI
AI-powered technology that enables natural language interactions between humans and machines. In marketing, conversational AI platforms, such as chatbots and virtual assistants, engage with users in real-time conversations, answering questions, providing recommendations, and guiding them through the customer journey.

Customer Lifetime Value (CLTV) Prediction
A predictive analytics technique that forecasts the future value of a customer over their entire relationship with a brand. AI-powered CLTV prediction models analyze historical customer data to identify high-value segments, optimize acquisition and retention strategies, and maximize long-term revenue.

CLV Formula
Wondering how to calculate customer lifetime value on your own? Use this Customer Lifetime Value Calculator (CLTV) to estimate the net profit attributable to a client’s future relationship. CLTV also defines the maximum threshold for client acquisition.

• CLV = (Revenue from a single customer over their lifetime) – (The cost of acquiring them)

If you’re not sure how much a customer has spent over their lifetime with your business, you can use this alternative customer lifetime value calculation:

• CLV = (Average annual revenue from a single customer) × (Number of years) – (Customer acquisition cost for that customer only)

Customer Segmentation
Customer segmentation is the process of dividing a target market into distinct groups based on shared characteristics, preferences, and behaviors. AI-driven customer segmentation algorithms analyze large datasets to identify meaningful segments, enabling marketers to personalize messaging, tailor offers, and optimize marketing campaigns for different audience segments.

Similarweb’s market research tools, for instance, allow marketers to segment any industry and better understand customer behaviors and needs. The Segment Analysis tool lets you analyze specific portions of a website by building a custom segment.

For example, to improve laptop-related sales for Samsung.com, comparing it to HP.com at a site level isn’t enough. Instead, you’ll want to analyze the “laptop” sections of both websites for an accurate, apples-to-apples performance assessment. As part of the capabilities within Segment Analysis, algorithms are used to ensure easier and faster segmentation based on the pages that you want to include and exclude, per website.

Data Analysis
The process of inspecting, cleaning, transforming, and modeling data to uncover insights, patterns, and trends. AI-powered data analysis tools leverage machine learning algorithms to process large datasets, extract actionable insights, and inform marketing strategies and decision-making processes.

For example, with Similarweb’s Data-as-a-Service (DaaS), you are able to harness the power of 30+ billion data points for comprehensive data analysis. That means you can dive deep into competitors’ online activities, analyzing their web traffic and acquisition strategies, or alternatively, monitor market leaders to maintain your business’s top position. DaaS eliminates hours of manual sifting through dashboards, providing efficient and targeted analysis.

Deep Learning
A subset of machine learning that uses artificial neural networks to model complex patterns and relationships in data. In marketing, deep learning algorithms are used for image recognition, natural language processing, sentiment analysis, and personalized content recommendations, enabling marketers to deliver more relevant and engaging experiences to customers.

Dynamic Pricing with AI
A pricing strategy that adjusts product prices in real-time based on market demand, competitor pricing, and other factors. AI-driven dynamic pricing algorithms analyze data from various sources to optimize pricing strategies, increase revenue, and maximize profitability for marketers.

Facial Recognition
AI-powered technology that identifies and verifies individuals by analyzing facial features from images or video footage. In marketing, facial recognition technology can be used for personalized advertising, audience segmentation, and experiential marketing activations, enhancing customer engagement and brand interactions.

G – M AI Terms for Marketing

Generative AI
Generative AI is a type of artificial intelligence that is capable of creating new content forms, such as text, images, music, and videos. It is powered by large foundation models capable of multitasking and performing various tasks like summarization, Q&A, and classification.

Hallucination
In AI, a hallucination — also known as confabulation or delusion — is when an AI generates a response containing false or misleading information presented as fact. Unlike human hallucinations, which involve false perceptions, AI hallucinations stem from erroneous responses or beliefs.

For example, a chatbot like ChatGPT may embed plausible-sounding falsehoods within its generated content. This is something to always consider when using chatbots.

Hyper-Personalization
A marketing approach that delivers highly customized and relevant content, offers, and experiences to individual customers based on their unique preferences, behaviors, and characteristics. AI-driven hyper-personalization algorithms leverage real-time data and machine learning to deliver personalized messages across multiple channels, driving customer loyalty and engagement.

Influencer Marketing with AI
The use of artificial intelligence to identify, evaluate, and collaborate with influencers for marketing campaigns. AI-powered influencer marketing platforms analyze social media data to identify relevant influencers, predict campaign performance, and measure ROI, helping marketers identify the most effective influencers to reach their target audience.

Large Language Model (LLM)
An LLM is an AI program designed to understand and generate text. These models are trained on vast amounts of data from online sources such as blogs and message boards, giving them the ability to recognize and interpret human language. LLMs use a machine learning technique called a transformer model to process this data. In essence, an LLM is a computer program that learns to understand language by analyzing large datasets. The quality of the data used in training can significantly influence the LLM’s ability to grasp and generate natural language, so programmers often use carefully curated datasets.

Machine Learning
A subset of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. In marketing, machine learning algorithms are used for predictive analytics, customer segmentation, content personalization, and campaign optimization, helping marketers make data-driven decisions and automate processes for better results.

Marketing Attribution with AI
The process of assigning credit to marketing touchpoints along the customer journey using AI algorithms to determine the most effective channels and campaigns. AI-driven marketing attribution models analyze multi-channel data to accurately measure the impact of marketing efforts, optimize budget allocation, and improve ROI.

Marketing Frameworks for AI
Marketing frameworks for AI involve structured approaches that help businesses effectively integrate artificial intelligence into their marketing strategies. These frameworks guide the planning, implementation, and optimization of AI technologies to enhance customer engagement, streamline operations, and drive business growth. Here are a few key AI marketing frameworks:

• AIDA: Attention, Interest, Desire, Action
• PAS: Problem, Agitate, Solution
• BAB: Before, After, Bridge

Whenever creating a prompt in your AI tool, make sure to specify the framework you’d like the output to use – along with all the other context we’ve spoken about. Alternatively, ask the AI which framework would be most appropriate and have it use that within the output too.

You can learn more about this term in the dedicated blog post we wrote, “The SEM Guide to Using ChatGPT.”

Micro Moments Marketing
A marketing strategy that targets consumers during “micro moments” when they turn to their devices to solve an immediate need or answer a question. AI-powered micro moments marketing campaigns leverage real-time data sources and machine learning algorithms to deliver relevant messages and offers to consumers, driving engagement and conversions in real-time.

N – S AI Terms for Marketing

NLP (Natural Language Processing)
Imagine a computer that actually understands your emails or social media posts! NLP allows AI to do just that. In marketing, NLP algorithms power features like sentiment analysis, chatbots, content generation, and voice search optimization. This enables marketers to understand and engage with customers more effectively through natural language interactions.

Predictive Analytics
Ever wish you could predict future customer behavior? Predictive analytics, using historical data and machine learning algorithms, helps you do just that. In marketing, these models analyze customer data to predict purchasing behavior, identify high-value prospects, and personalize marketing campaigns. This allows marketers to anticipate customer needs and optimize marketing strategies for better results.

Programmatic Advertising with AI
Imagine buying and selling online ads with the efficiency of a robot! Programmatic advertising utilizes AI algorithms to automate ad placements, targeting, and bidding in real-time. This translates to personalized ads delivered to individual users across multiple channels, improving ad performance and campaign efficiency for marketers.

Prompt Engineering
Prompt engineering involves crafting instructions that a generative AI model can interpret and execute. A prompt is a natural language description of the task, such as “write a CV focused on field marketing experience,” which the AI then uses to generate the appropriate output.

Real-time Marketing with AI
In today’s fast-paced world, reacting quickly is key. Real-time marketing leverages AI to analyze data and deliver timely, relevant, and personalized messages to consumers based on their current context, behavior, and preferences. This allows marketers to react quickly to market trends, events, and customer interactions, driving higher engagement and conversions.

Recommendation Engines
Have you ever browsed Netflix and felt like they know exactly what you want to watch? Recommendation engines powered by AI analyze user behavior and preferences to generate personalized suggestions for products, content, and experiences. In marketing, recommendation engines can significantly boost sales, engagement, and customer satisfaction by delivering relevant recommendations based on past interactions and preferences.

Sentiment Analysis
Imagine gauging customer opinion from a mountain of social media comments and reviews! Sentiment analysis, a branch of NLP, analyzes text data to determine the emotional tone expressed by users. Marketers can leverage this to understand public opinion, gauge brand sentiment, and identify trends. This enables data-driven decisions and effective brand reputation management.

Understanding sentiment is crucial for AI-led marketing, and Similarweb can help there too. With Similarweb’s Demand Analysis tool, you gain a comprehensive view of the customer journey from search to clicks, capturing real intent signals. By analyzing search data, you can evaluate genuine intent and reach a broader audience, complementing social listening and traditional survey insights to create a robust picture of consumer trends.

Social Listening with AI
Keeping your ear to the ground on social media is crucial. Social listening with AI-powered tools allows you to monitor and analyze social media conversations to gain insights into customer opinions, trends, and sentiments. Marketers can use this to track brand mentions, identify relevant conversations, and engage with audiences in real-time, ultimately understanding customer needs, addressing issues, and optimizing marketing strategies.

T – Z AI Terms for Marketing

Tera Operations Per Second (TOPS)
Tera “trillion” Operations Per Second (TOPS), measures the performance of a supercomputer or high-end circuit board, particularly in AI tasks. It indicates the potential peak AI inferencing performance, based on the architecture and frequency of processors like the Neural Processing Unit (NPU).

Transformer
A transformer is a deep learning architecture developed by Google researchers in 2017. It uses a multi-head attention mechanism, enabling faster training by eliminating recurrent units. Originally designed for machine translation, transformers have become foundational in natural language processing, computer vision, and other AI applications, and have led to innovations like GPT and BERT.

Visual Search Optimization
Did you know you can search using images? Visual search optimization utilizes AI algorithms to analyze and interpret visual data, optimizing images and visual content for search engines. This helps marketers improve online visibility, drive organic traffic, and enhance user experience by making visual content more discoverable and accessible to search engines and users alike.

Voice Search Optimization
The way people search is evolving! Voice search optimization optimizes content and websites for voice-based search queries using AI algorithms to understand natural language and intent. This helps marketers improve search engine rankings, increase organic website traffic, and reach consumers who use voice-enabled devices to search for information and make purchases.

VR (Virtual Reality)
Imagine transporting customers to a virtual world to experience your product! VR creates a computer-generated simulation of an immersive, three-dimensional environment that users can interact with in real-time. Marketers can leverage VR for interactive storytelling, product demonstrations, and virtual tours, ultimately engaging consumers and driving brand awareness, affinity, and sales.

And that’s a wrap on our AI glossary for marketers! 

As the AI landscape continues to evolve, so too will the terminology. We’ll keep this glossary updated to reflect the latest advancements. This post was – only naturally – crafted with the help of AI, demonstrating the technology’s potential to streamline content creation for marketers.

To explore how AI can improve your own marketing strategy, check out Similarweb’s SimilarAsk. Our new AI-driven data analytics tool provides easy-to-understand, actionable insights – helping you make smarter business decisions.

We’ve got a bunch of other glossaries too, check them out:

• Digital marketing terms
• Ecommerce terms
• Stock market terms
• Digital research terms
• Market research terms
• Sales terms
• SEO terms