Glossary

Alerting is the automated system of real-time notifications that signal sudden or significant changes in online conversations. These may include spikes in Buzz, shifts in Sentiment, surging Topics, or mentions from high Source Impact profiles.

Automated Translations refer to the use of AI-powered tools and algorithms to instantly convert text or speech from one language to another. Unlike manual translation, automated systems can process large volumes of data at scale and in real time, making them ideal for global brands monitoring multilingual conversations across digital platforms.

Business Intelligence (BI) tools are software solutions that help organizations transform raw data into meaningful insights. They consolidate information from multiple sources—such as social media, web analytics, CRM systems, and financial databases—into dashboards, reports, and visualizations that guide smarter decision-making.

Buzz refers to the volume of online conversations, mentions, and discussions happening around a brand, product, or topic. It captures how much “noise” a subject generates across social media, blogs, forums, and news outlets.

Campaign Evaluation is the systematic process of measuring, analyzing, and assessing the outcomes of a marketing campaign against its predefined objectives. It combines quantitative and qualitative metrics—such as reach, engagement, sentiment, and conversion—to determine how successfully a campaign met its goals, identify what worked, and inform future strategies.

Channel Analysis is the process of evaluating the performance of different digital and social media platforms to understand where, how, and why audiences interact with a brand.
It helps identify which channels drive the most buzz, engagement, sentiment shifts, and potential reach, enabling organizations to optimize their communication and marketing strategies.

ChatGPT is an advanced conversational AI powered by Large Language Models (LLMs). It can understand and generate natural language, enabling human-like interactions with users. Unlike traditional chatbots that follow scripted flows, ChatGPT adapts dynamically, providing contextual answers, summaries, recommendations, or even creative content.

Competitive Benchmarking is the process of measuring a brand’s performance against its competitors using key metrics such as Buzz, Share of Voice (SoV), Engagement, Sentiment, and Earned Media Value (EMV).

Consumer Intelligence is the practice of gathering, integrating, and analyzing data from multiple sources to build a comprehensive understanding of consumer behaviors, preferences, and motivations. It goes beyond simple metrics — it examines why people act, what they care about, and how their opinions evolve across digital touchpoints.

Crisis Management in digital and social media is the structured process of detecting, addressing, and resolving sudden negative events that could harm a brand’s reputation. These events might include viral complaints, misinformation, product issues, PR scandals, or unexpected backlash online.

Dashboards are centralized, interactive interfaces that bring multiple KPIs into one view. They enable teams to track brand performance in real time, ensuring quick access to the most relevant insights.

Data Cleaning is the process of detecting and correcting errors, inconsistencies, or irrelevant information within a dataset to ensure accuracy and reliability. In digital and social media analytics, data cleaning is essential for removing spam, duplicates, or misleading entries so that insights are based on high-quality data.

Data Preparation is the process of collecting, organizing, and structuring raw data so it is ready for analysis. In digital and social media analytics, data preparation ensures that information from multiple sources—such as social networks, forums, web traffic, or CRM platforms—is formatted consistently and accurately before insights are generated.

Data Visualization is the practice of presenting complex data in visual, easy-to-understand formats such as charts, graphs, and maps. Within social and web intelligence, it turns large datasets — mentions, sentiment, engagement, reach — into clear insights that can be acted upon.

Digital Insights are the meaningful conclusions drawn from analyzing data across the entire digital ecosystem. Unlike isolated metrics, insights reveal patterns, behaviors, and opportunities hidden in online interactions. They go beyond Social Media Insights by combining data from multiple sources such as websites, apps, search trends, e-commerce platforms, and online media.

Earned Media Value (EMV) is a metric that estimates the monetary value of a brand’s visibility and engagement across digital channels. It translates online exposure — such as social media mentions, shares, influencer posts, and press coverage — into a financial equivalent, making it easier to assess the effectiveness of marketing and communication efforts.

Elasticsearch is an open-source search and analytics engine designed for fast, scalable, and real-time data exploration. It enables organizations to store, search, and analyze large volumes of structured and unstructured data with high efficiency.

Emotion Analysis is the process of identifying and categorizing emotions expressed in text, speech, or visuals. Unlike basic Sentiment Analysis, which classifies content as positive, negative, or neutral, Emotion Analysis goes deeper—detecting emotions such as joy, anger, fear, surprise, or sadness.

Engagement refers to the level of interaction and involvement an audience shows towards content across digital and social platforms. It includes measurable actions such as likes, comments, shares, clicks, and views, making it a comprehensive indicator of how well content resonates with people.

Gen AI, short for Generative Artificial Intelligence, refers to AI systems capable of creating new content such as text, images, audio, or even data models, based on patterns learned from large datasets. Unlike traditional AI, which classifies or predicts, Generative AI actively produces original outputs that mimic human-like creativity.

Influencer Analysis is the process of evaluating social media influencers to understand their reach, relevance, credibility, and performance. It goes beyond follower counts, focusing on metrics such as engagement, audience demographics, content quality, growth trends, sentiment and alignment with brand values.

Influencers Categorization is the classification of social media influencers based on their audience size, reach, and impact. It helps brands and agencies understand the scale of influence each type of creator has, and how best to collaborate with them depending on campaign goals and budget.

Influencers Discovery is the process of identifying influencers who align with a brand’s goals, niche, or audience before any formal evaluation or partnership. Unlike influencer analysis (which evaluates preselected candidates), discovery involves finding new creators who could potentially drive value — based on metrics, content, relevance, sentiment and alignment with brand values.

An LLM, or Large Language Model, is an advanced type of AI trained on vast amounts of text data to understand, generate, and interact in natural language. Unlike traditional models that perform narrow tasks, LLMs can summarize conversations, answer questions, translate content, and generate insights across industries.

LLM Training Models refer to the methods and datasets used to teach Large Language Models (LLMs) how to understand and generate human-like language. Training involves exposing the model to massive amounts of text, enabling it to learn grammar, context, facts, and reasoning patterns.

Media Monitoring is the practice of tracking mentions and coverage of a brand, organization, or topic across digital media outlets, including online news, blogs, forums, and press sources.

Net Sentiment, also known as net sentiment percentage or net sentiment score, is a metric that evaluates the overall tone of online conversations about a brand, product, or topic. It is calculated by taking the difference between the proportion of positive mentions and negative mentions, resulting in a score that shows whether sentiment leans more positively or negatively.

Potential Reach is an estimate of the maximum number of unique users who could have been exposed to a piece of content, mention, or campaign across digital and social channels.

Power BI is Microsoft’s business analytics tool that transforms raw data into interactive dashboards, reports, and visualizations. For brands and organizations, Power BI acts as a centralized hub where digital and social data can be connected, analyzed, and shared across teams to support data-driven decision-making.

Queries are the specific requests or instructions used to search and retrieve information from a database, search engine, or analytics platform. In digital and social media analytics, queries define what data to collect—such as keywords, hashtags, mentions, or phrases—ensuring that monitoring and insights are targeted and relevant.

Real-Time Alerting is a specialized form of alerting that delivers instant notifications the moment critical changes occur. Unlike periodic reports, real-time alerts are immediate, ensuring brands never miss the moment when action is most needed.

Real-Time Monitoring is the continuous tracking of online conversations, mentions, and digital signals on social media and the web the moment they happen. Unlike periodic reporting, real-time monitoring delivers instant visibility into brand performance, audience reactions, and market trends across social media, web publications, and digital platforms.

Reputation Management is the ongoing process of monitoring, shaping, and improving public perception of a brand. It ensures that the digital footprint of an organization aligns with its values and supports long-term growth

Sentiment refers to the emotional tone or attitude expressed in online conversations about a brand, product, topic, or campaign. Mentions are typically classified as positive, negative, or neutral. Social intelligence platforms employ natural language processing (NLP) and language models to interpret words, phrases, sarcasm, and context so as to assign sentiment labels.

Share of Engagement (SoE) shows the percentage of all audience interactions — such as likes, comments, shares, and reactions — that a brand receives compared to its competitors.

Share of Voice (SoV) is a metric that measures the percentage of total mentions or conversations a brand captures compared to competitors over a defined period, within a defined market or topic. It reflects how visible and dominant the brand is in a given digital ecosystem.

Social Media Analytics is the practice of collecting, measuring, and analyzing data from social platforms to understand performance, audience behavior, and brand perception.

Social Media Insights are the actionable learnings that brands extract from analyzing conversations, behaviors, and trends across digital platforms. Unlike raw data or basic metrics, insights provide context and meaning—helping organizations understand not only what is happening, but also why.

Social Media Intelligence (SMI) is the process of collecting, analyzing, and leveraging data from social networks to support strategic decision-making. It goes beyond tracking likes or shares; it transforms raw data into actionable insights about audiences, trends, competitors, and the digital landscape.

Social Media Listening is the process of tracking, collecting, and analyzing conversations, mentions, and trends across social platforms to understand how audiences perceive a brand, product, or industry.

Social Media Monitoring is the process of tracking and recording mentions of a brand, product, competitor, or keyword across social networks in real time.

Source Impact is a metric that evaluates the influence and contribution of a source — such as a website, social media account, news outlet, or influencer — within the digital ecosystem. It goes beyond counting mentions and assesses how much visibility and engagement a source can generate for a brand.

Sponsorship Evaluation is the process of measuring and analyzing the impact, visibility, and value generated from a brand’s sponsorship activities. This includes tracking audience exposure, engagement, sentiment, and media coverage related to sponsored events, partnerships, or activations.

Topic Analysis is the process of identifying, grouping, and interpreting the core themes or keywords that appear across online conversations. Using Natural Language Processing (NLP) and machine learning, the system filters and categorizes posts, articles, comments, or mentions into meaningful topics or clusters.

Trend Detection is the process of identifying emerging topics, patterns, and behaviors within digital conversations before they become mainstream. In social and web intelligence, it involves monitoring mentions, sentiment, hashtags, and topic clusters to spot shifts in consumer interest and market dynamics.