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A/B Testing
A/B testing is a method that compares two different versions of a marketing element—such as a webpage, ad, or email—to determine which...
Abandoned Browse
Abandoned browse occurs when users visit a website and explore products or services but leave without taking further action, such as adding...
Abandoned Cart
Abandoned cart refers to situations where users add items to their online shopping cart but leave the site without completing the purchase....
Action Basis
An Action Basis, on the Pixis AI Optimizer dashboard, is the underlying logic that explains why a Pixis AI model recommends a...
Ad Attribution
Ad attribution is the process of identifying which marketing channels and campaigns drive consumer actions, such as purchases or sign-ups. It helps...
Ad Delivery Optimization
Ad delivery optimization is the process of using algorithms and machine learning to serve ads to the people most likely to take...
Ad Effectiveness
Ad effectiveness measures how well an advertisement achieves its intended goals, such as increasing brand awareness, driving sales, or engaging an audience....
Ad Exchange
An ad exchange is a digital marketplace where advertisers and publishers buy and sell ad space in real time. It facilitates automated...
Ad Fatigue
Ad fatigue occurs when consumers see the same advertisement too frequently, causing them to lose interest and engagement. As ad fatigue sets...
Ad Frequency
Ad frequency measures how often the same user sees an ad within a specific time period. It is a key metric for...
Ad Impression
An ad impression refers to the number of times an advertisement is displayed on a screen, regardless of whether the user interacts...
Ad Inventory
Ad inventory refers to the total amount of advertising space available for sale on a website, app, or digital platform. Publishers offer...
Ad Network
An ad network is a platform that connects advertisers with publishers by aggregating available ad inventory and facilitating ad placements across multiple...
Ad Placement
Ad placement refers to the specific locations where an ad appears on a digital platform, such as websites, apps, or social media...
Ad Quality Score
Ad Quality Score is a metric used by platforms like Google Ads to evaluate the relevance and quality of an advertisement. It...
Ad Rank
Ad Rank determines the position of an ad on a search engine results page (SERP) or within a display network. It is...
Ad Recall
Ad recall measures how well audiences remember an advertisement after seeing it. It is a key indicator of brand awareness and ad...
Ad Relevance Score
Ad relevance score measures how closely an ad matches its target audience’s interests and behaviors. Platforms like Meta and Google assign this...
Ad Revenue
Ad revenue is the income generated from displaying advertisements on digital platforms such as websites, apps, and social media channels. It is...
Ad Rotation
Ad rotation refers to the practice of alternating different advertisements within a single placement to test performance and prevent ad fatigue. It...
Ad Scheduling
Ad scheduling, also known as dayparting, allows advertisers to choose specific times and days for their ads to run. This ensures ads...
Ad Server
An ad server is a technology platform that manages, delivers, and tracks digital advertisements across websites, apps, and other digital spaces. What...
Ad Stack
An ad stack is a collection of technologies and platforms that work together to manage, deliver, measure, and optimize digital advertisements. It...
Ad Suppression
Ad suppression is a digital advertising strategy that prevents specific users from seeing certain ads, ensuring that campaigns reach the most relevant...
Ad Targeting
Ad targeting is the process of delivering digital ads to specific audiences based on criteria such as behavior, demographics, interests, and location....
Ad Viewability
Ad viewability measures whether an advertisement is actually seen by users, providing advertisers with insights into how effectively their ads are displayed....
AI Bandits
AI bandits are algorithms that are used to make decisions in situations where there is uncertainty about the outcomes of different actions...
AI Group
An AI Group, on Pixis AI Optimizer, is a list of ad sets or campaigns that have similar objectives, budget settings, bid...
AI Infrastructure
Pixis’ codeless AI Infrastructure refers to the underlying system of pre-trained, customizable AI models and deep-learning technologies that enable training, testing, experimentation...
AI Model
An AI Model is a set of algorithms that allow a machine to perform tasks that mimic human intelligence. These tasks could...
AI Optimizer
Pixis AI Optimizer is a Google Chrome extension that allows users to quickly and easily access Pixis’ three codeless AI engines on...
Artificial Neural Networks
Artificial Neural Networks (or Neural Networks) are modeled on the way neural networks of the biological brain function. They consist of a...
Attention
Attention refers to the ability of a model to focus on a specific subset of its inputs, or “attend” to them, while...
Autoregressive Language Model
An autoregressive language model is a type of Artificial Intelligence (AI) model that is used to predict the next word in a...
Autoregressive Models
Autoregressive Models are a class of statistical models that analyze and predict time series data – basically a machine’s way of measuring...
Backpropagation
Backpropagation is crucial in training artificial neural networks to learn and improve their performance over time. The basic idea behind backpropagation is...
BERT
BERT is a powerful AI model that is designed to understand and generate natural language. It is widely used in a variety...
Black Box
Black Box artificial intelligence and machine learning refers to a system or algorithm whose internal workings are not transparent or easily understandable...
Clarity Scoring
Clarity Scoring, also known as readability scoring or readability assessment, is a process of evaluating the readability of written text using AI...
Codeless AI
Codeless AI refers to Artificial Intelligence (AI) technologies and products that do not require users to have programming skills or knowledge of...
Confidence Score
A Confidence Score is a measure of the reliability or certainty of a prediction or assessment made by a machine learning model...
Content Intelligence
Content intelligence is a field of Artificial Intelligence (AI) that focuses on extracting insights, knowledge, and meaning from large volumes of content,...
Contextual AI Models
Contextual AI Models are Artificial Intelligence (AI) models that are able to take into account the context in which they are operating...
Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are a type of artificial neural network which are tasked with analyzing and understanding complex data for a...
Cosine Similarity
Cosine Similarity is a measure of similarity between two data sets. It is commonly used in information retrieval, recommendation systems, and other...
Creative Adversarial Network
A Creative Adversarial Network (CAN) is a type of Artificial Intelligence (AI) system that generates original content in a specific domain, such...
Data Agnostic
Data Agnostic refers to the ability of an Artificial Intelligence (AI) system to operate without being specifically tailored or trained on a...
Data Augmentation
In the context of Artificial Intelligence (AI), Data Augmentation refers to the process of generating additional data samples from existing ones. It...
Decision Intelligence
Decision Intelligence is a field of Artificial Intelligence (AI) that focuses on using data and algorithms to make informed decisions. This can...
Decision Tree
A Decision Tree is a type of machine learning algorithm that is used to make predictions or decisions based on a set...
Deep Learning
Deep Learning is a subfield of machine learning that involves the use of artificial neural networks, which are complex mathematical models inspired...
Descriptive Analytics
In the context of Artificial Intelligence (AI), Descriptive Analytics involves using AI algorithms and models for understanding patterns and trends in data...
Deterministic Dependency Parsing
Deterministic Dependency Parsing is a process used by Artificial Intelligence (AI) systems to analyze and understand the relationships between words in a...
Diagnostic Analytics
In the context of Artificial Intelligence (AI), Diagnostic Analytics involves the use of machine learning algorithms and other AI techniques to analyze...
Domain Agnostic AI
Domain Agnostic AI refers to an AI model or system that is designed to be flexible and adaptable to all business domains....
Dynamic Dashboard
A Dynamic Dashboard is a type of interactive data visualization tool that allows users to explore and analyze data in real-time. It...
Enterprise Internet of Things (IoT)
Enterprise Internet of Things (IoT) refers to the use of connected devices, sensors, and systems within a business or organization to collect,...
Generative Adversarial Networks
A class of machine learning models that consist of two neural networks: a generator and a discriminator. GANs are used for generating...
GPT-3
GPT-3 (Generative Pre-training Transformer 3) is a state-of-the-art Artificial Intelligence (AI) language model designed to process and generate human-like language. GPT-3 is...
Hyperparameters
Hyperparameters are settings or parameters that are chosen before training a machine learning model to adjust or control its learning process and...
Inference
Inference in the context of AI refers to the process of using previously learned knowledge to make predictions or conclusions about new...
Latent Space
Latent space refers to a mathematical representation or space where complex data or information is encoded into a more condensed and meaningful...
LSTM
LSTM stands for Long Short-Term Memory. It is a type of artificial neural network used in the field of Artificial Intelligence (AI)...
Metaheuristic
Metaheuristics are a type of Artificial Intelligence (AI) algorithm that can be used to solve complex optimization problems by finding good solutions...
Natural Language Generation
Natural Language Generation (NLG) is a field of Artificial Intelligence (AI) that involves creating a human-like language from data or computer-generated information....
Natural Language Processing
Natural Language Processing (NLP) is a field within Artificial Intelligence (AI) that focuses on the ability of computers to understand, interpret, and...
Optimization Events
Optimization Events refer to the process of improving the performance or efficiency of a machine learning model or algorithm. This can be...
Pico Segmentation
Pico segmentation is a way of dividing a large group of people or things into smaller, more specific subgroups. In the context...
Predictive Analytics
Predictive Analytics is a type of Artificial Intelligence (AI) that helps to predict future outcomes or events based on past data and...
Q-Learning
Q-Learning is a type of Artificial Intelligence (AI) training that is often used in situations where the computer needs to make decisions...
Reasoning Engine
A Reasoning Engine is a component of Artificial Intelligence (AI) that is responsible for making logical deductions and reaching conclusions based on...
Recommendation
Recommendation in the context of Pixis AI refers to the use of Artificial Intelligence (AI) to generate recommendations on an account based...
Recurrent Neural Network
A Recurrent Neural Network (RNN) is a type of artificial neural network that has a loop in its architecture, allowing it to...
Recursive Neural Network
A Recursive Neural Network is a type of artificial neural network that takes a piece of data, analyzes it, and then uses...
Reinforcement Learning
Reinforcement Learning is a type of Artificial Intelligence (AI) training that involves training a machine to take actions in a specific environment...
ResNet
ResNet is a type of artificial neural network that is particularly useful for tasks that require a lot of processing power, such...
Self-Supervised Learning Framework
Self-Supervised Learning is a type of machine learning in which the model is given a task to perform, but is not explicitly...
Semantic Mapping
Semantic Mapping in the context of Artificial Intelligence (AI) refers to the process of assigning meaning to different elements or concepts within...
Sentiment Analysis
Sentiment Analysis is a way for Artificial Intelligence (AI) to analyze and understand the underlying emotions and opinions of words and language....
Style Transfer
Style Transfer is a process in which the style of one image is applied to another image, creating a new and unique...
Supervised Learning
Supervised Learning is a type of machine learning that involves training a machine model on a dataset that has already been labeled...
Target Daily Results
Target Daily Results is a term that refers to the goals or objectives that an Artificial Intelligence (AI) system is designed to...
Target-Cost Per Optimization Event
The Target-Cost per Optimization Event refers to the desired cost of using Artificial Intelligence (AI) to optimize a specific task or process....
Testing Dataset
A Testing Dataset is a set of data that is used to evaluate the performance of an AI model. It is used...
Training Dataset
A Training Dataset is a collection of data that is used to teach a machine learning model how to perform a particular...
Transfer Learning
Transfer Learning is a machine learning technique that involves taking a pre-trained model developed for a task and adapting it for use...
Unsupervised Learning
Unsupervised learning is a type of machine learning where the model is not given any labeled training data or feedback on its...
Variational Auto Encoders (VAEs)
Variational Autoencoders (VAEs) are generative models that are used to learn and generate new data samples, typically in the form of images,...