Welcome to C-Score.ai
– Reputation Intelligence

C-Score.ai is the leading AI-based executive reputation benchmark system that turns public, citable information about an executive into a structured, evidence-based reputation profile and compares it to relevant peers in their market.

The system analyzes multiple reputation signals and organizes them into 72 Data Points, 7 reputation dimensions and 3 main reputation categories. These inputs are aggregated to produce a Reputation Total from 0 to 100.

C-Score.ai is no social-media tool or score. Digital presence is perhaps one thenth of the C-Score.ai framework.

C-Score.ai is no media sentiment analysis tool. Media coverage, sentiment and public perception are aggregated into just one of the seven reputation dimensions.

C-Score.ai is no investment rating or financial recommendation system. Financial results of a certain company under a certain leader play a role in their reputation, however the tool does not provide investment recommendations.

Traditional tools, Google searches, or AI-powered chatbots tell people what they want to hear. They flatter you. But that is very different from how the world actually perceives you. If you are wondering why you aren’t getting enough invitations to panel discussions, presentations, keynote speeches, conferences, membership in professional associations, or new career opportunities, or why your messages go unanswered, the reason may lie in your personal reputation. The C-Score.ai benchmark shows you exactly what to do to improve your standing in the industry.

C-Score.ai is designed around public, citable sources.

The methodology focuses on evidence that can be connected to identifiable public information.

Depending on the executive and the available evidence, the reputation record may include information from areas such as company communications, media coverage, professional platforms, public corporate records, institutional sources, employee-perception sources and other relevant public material. All information within a data set is verified by independent sources and weighted based on its plausibility. This virtually eliminates fake news.

No.

C-Score.ai analyzes reputational evidence, not an executive’s personality or psychological characteristics.

The methodology focuses on public information and reputational risk at the intersection of an executive’s role, organization and stakeholders. It does not infer sensitive personal attributes or psychological traits.

The Market Uneasiness Score (MUS) is a separate indicator that summarizes the reputational risk signals in an executive’s public record, for example controversy in the media, crisis handling or governance questions. It is reported alongside the Reputation Total, not as part of it, so that a strong overall score and an elevated risk signal can occur at the same time.

The Reputation Total runs from 0 to 100. The higher score, the better, however the score is benchmarked in terms of industry cohorts and being on top of the industry cohort is good.

The market knows reputation tracking systems that focus on company reputation. Benchmarks that take care of the long neglected influence of the leadership team on company reputation are new. The financial value of the leadership’s contribution to company reputation is extremely high (for a tech company with 1 billion USD Market Cap the Value of Reputation of its CEO is 115 million USD).

CEO rankings produce a list position, usually from a single data source such as employee ratings or media volume. C-Score.ai produces an auditable profile from 72 Data Points across seven dimensions, including employee ratings or media volume, but many more.

Media monitoring is an entirely different product category. It was developed to measure the results of the communications team’s activities, such as published articles, interviews, roadshow announcements, etc.

Executive benchmarking is a different product. It provides a focused, top-down overview of management’s position within its industry compared to competitors. C-Score.ai therefore focuses on reputation capital.

C-Score.ai can use comparison cohorts to provide context around individual reputation dimensions and results.

Benchmarking helps answer an important question: Is a particular person’s score strong or weak relative to a relevant comparison group?

Yes.

Clearly, white collar criminals fall into this category and C-Score.ai has a distinct system in place to identify these individuals. White-collar criminals draw extensive public attention but have very low overall reputation.

In general, Visibility and reputation are related, but they are not identical. An executive can receive extensive media coverage or have a large digital audience while still facing weaknesses in areas such as leadership, employee perception, industry influence or stakeholder confidence. Conversely, an executive can have strong credibility and stakeholder confidence while remaining comparatively underexposed.

C-Score.ai is designed to make these differences visible and actionable.

In an Executive Reputation project, clients get personalized consulting based on our generated C-Score.ai benchmark reports and later receive a how-to-read document to interpret the results. We also provide insights into the aggregated information about industry peers to identify industry best practices.  The result of a working relationship is a measurable improvement in Personal Reputation, measured across a period of between 6 months and 13 months.

 It is not possible to obtain clean, aggregate, repeatable and auditable benchmark information from a chatbot. Here is why:

• A general AI model does not reliably filter and validate sources, it takes shortcuts and does not go for all available information.

• The analysis will not be structured and auditable regarding veritable sources.

• The criteria the model chooses typically change from one analysis to the next.

C-Score.ai is designed to solve these problems. The methodology remains consistent from one assessment to the next. Evidence can be traced, results can be compared over time, and changes in reputation can be measured against the same analytical framework rather than against whatever criteria a general-purpose AI happens to apply on a particular day.

C-Score.ai is designed to make executive reputation structured, explainable and auditable.

The system is based on a long tradition of approaches to understanding human nature. Aristotle identified logos, pathos, and ethos as the three essential pillars of a person’s reputation. Jürgen Habermas built upon this model with his theory of the three worlds. Recently, Prof. Markus Eisenegger (University of Zurich) defined functional, social, and expressive reputation as the three main components of reputation. C-Score.ai is based on this model, dividing personal reputation into performance, social engagement, and presence.

The 72 resulting Data Points which build the three scores have been derived from CEO Positions AG’s long-standing experience in executive positioning and reputation management. The framework has been refined through years of practical application, repeated testing and dozens of validation rounds, with the aim of identifying which reputation factors consistently matter, how they should be clustered and how they should contribute to the overall assessment.

Start with our Executive Reputation Check on this website or contact CEO Positions AG directly (office@ceo-positions.net). C-Score.ai will also be available through partner agencies, executive search firms and coaches.

C-Score.ai is offered as a four-step ladder. Step 1 is a the Executive Reputation Check, a self-assessment across the seven reputation dimensions. For individual executives, we recommend the Personal Positioning Day. For companies we have a Plug & Play offering and offer alternatively a structured Project Process. The planned Enterprise Version is an inhouse solution for large organizations.