Media Intelligence Glossary

An attribution model is a model that assigns credit for conversions to marketing touch points. It allows businesses to understand what marketing channels drive sales the most and optimize their advertising and budget allocation based on this data. Attribution models range from very simple ones, where businesses simply record the last touch point before target action such as purchase, to complex ones, where businesses track the entire customer journey, analyzing weights of each touch point and whether they contribute to awareness, interest, or intent.

Brand safety is a set of practices aimed at ensuring that your brand’s reputation remains protected from the damaging effects of your online advertising appearing next to inappropriate or polarizing content, such as obscenity, hate speech, and piracy.

A coverage report is a summary document that provides an overview of the media coverage received within a specific timeframe. It typically includes metrics such as reach, engagement, and sentiment analysis of news articles. In Public Relations, it is used to analyze the impact of PR campaigns.

Crisis monitoring is the process of continuously scanning media publications in order to detect articles and posts that signal potential threats to a company’s reputation, operations, or finances. It allows organizations to identify risks early and manage them effectively before they escalate into large problems.

Data-driven marketing is a marketing strategy that involves basing marketing campaigns on customer data and analytics instead of trying to guess what would resonate with your audience. Data-driven marketing uses hard evidence as a basis for decisions, and it has shown its effectiveness at delivering results and minimizing guesswork, thus reducing the risks businesses have to take when choosing how to market their products.

In media intelligence, fact-checking refers to the practice of vetting the information gathered through traditional or social media monitoring before acting on it. Acting on misinformed media posts without verifying their accuracy can bring serious reputational and even legal risks for businesses.

First-party data refers to the information businesses collect from their customers directly without employing a third party. First-party data typically includes details such as purchase history, website behavior, account information, and customer feedback. This data is valuable to businesses because they can be sure it is accurate and reliable, and it allows them to understand customer preferences, leading to more personalized marketing and products better suited to their customers’ needs.

Forecasting is the analysis of past and present data and patterns using statistical models to predict future events with varying degrees of certainty. Businesses use forecasting across different areas, such as marketing, budgeting, sales, and customer demand, to inform strategic decisions and allow them to plan ahead, reducing the inherent uncertainty of future changes.

Generative AI is a subset of artificial intelligence systems that are designed to generate new content. AI in general can perform various tasks, such as classification and detection, predictive analysis, computer vision, and running robotic systems. Generative AI specifically refers to AI models that create text, images, videos, or code.

In media monitoring, insights are pieces of information that warrant action, such as revealing opportunities or identifying issues. For example, the number of mentions per week is not an insight, while learning that negative mentions covering product delays have increased is an insight, because it can inform action. If the delays are yours, it signals a problem; if they are your competitors’, it is a marketing opportunity.

In media monitoring, issue tracking means following a specific problematic topic to see how it develops over time. It involves monitoring mentions and sentiment changes around the issue in order to understand how it evolves and decide when and how to respond.

KPI is a quantifiable measure of progress toward a business goal. Creating a KPI involves setting a goal, for example, “increase website sales”, then identifying which available metrics can best reflect the progress toward that goal, for example, "monthly visitors” and “conversion rate”, and setting a quantitative target for those metrics, for example, “increase monthly visitors by 30% and conversion rate by 1%”. In essence, KPI is simply a metric with a target that is used as a measure of progress towards your goal.

A knowledge graph is a structured network of information that consists of entities, such as people, companies, products, or concepts, connected with relationship indicators that show how these entities are related. For example, “iPhone” and “iOS” would be connected with “runs on”, and “Apple Inc.” and “iPhone” would be connected with “makes”. Knowledge graphs are used by both humans and AI systems to understand connections and context, and extract insights from complex data.

Large language models are a type of artificial intelligence that can understand and generate human-like text. They process vast amounts of data to learn language patterns, rules, and context. When trained, LLMs can perform various natural language processing tasks such as summarizing, writing, translating, and answering questions.

Machine learning is a branch of artificial intelligence that involves writing code that allows a system to recognize patterns in data and then use those patterns to solve problems, instead of explicitly programming step-by-step instructions on how to solve problems. Machine learning is widely used to create AI for different applications, such as recommendation algorithms, self-driving vehicles, and AI assistants.

Media coverage refers to the attention an event, person, company, or topic receives across media platforms, including news articles, broadcasts, and online content. Broad media coverage can create an increase in public awareness and credibility, as well as shape how the topic of coverage is perceived.

Media landscape refers to the overall environment of media outlets and channels. It is shaped by the current narratives and sentiment in the media, the structure and the makeup of outlets and channels, and the authors, journalists, and influencers who drive the conversations.

A media list is a database that contains information about media outlets, journalists, and influencers relevant to a specific industry or a topic. Media lists typically include contact information, areas of coverage, and audience information. Organizations can leverage this data to pitch stories, find partnerships, or build relationships with authors relevant to their industry.

Media monitoring is the process of collecting relevant news publications and analyzing them. Media monitoring can serve different purposes: it can be used to track competitor actions, regulatory changes, identify potential PR threats and opportunities, or consumer demand changes.

Misinformation detection is the process of identifying false, misleading, or inaccurate information in media content. Typically, the goal is to help organizations recognize misleading narratives so they are able to respond before misinformation spreads widely and causes reputational harm.

Natural language processing is a branch of artificial intelligence that allows computers to understand, interpret, and generate human language. All AI systems that deal with human language, for example, sentiment analysis tools, translators, text-to-speech apps, or large language models, use NLP techniques to process language and generate responses.

Sentiment analysis in media monitoring refers to the automated identification of the tone and attitude expressed in news articles and social media posts. It is used to determine whether mentions of companies and products are positive, neutral, or negative at large scales, eliminating the need to scan every mention manually to understand if it’s praise or criticism.

Share of Voice or SoV is a popular general metric that represents how much media attention a company is getting compared to its competitors. It is calculated simply by dividing your brand mentions by mentions of all brands in your industry to get the percentage.

Social media listening is the process of monitoring online conversations on social media about a brand, industry, and products in order to understand customer sentiment, identify popular topics or features, and uncover opportunities by analyzing customer needs and pain points.

Web analytics refers to collecting, measuring, and analyzing data about website usage to understand user behavior and improve outcomes. In business, web analytics typically includes tracking metrics such as the number of monthly visitors, traffic sources, and engagement to understand how the website can be improved to provide a better user experience or drive sales.

Zero-party data is information that a customer directly shares with a company intentionally and proactively. Examples of zero-party data include customers answering questionnaires, personal data customers provide to join a loyalty program, indicating what they want to buy, or selecting preferred communication channels.