Stakeholder intelligence is the continuous measurement of what each of an organisation's stakeholder groups believes about it, how each evaluates it, and what each intends to do, together with the causes of all three. The idea goes back to stakeholder theory (Freeman, 1984; Mitchell, Agle & Wood, 1997): an organisation's performance depends on relationships with several groups at once, those groups do not see the organisation the same way, and a change in one can reach another. A firm that measures only its customers, or only its employees, sees one face of a relationship that has several.

Several studies, one model

StakeholderWatch runs stakeholder intelligence as a set of parallel studies rather than one survey. Customers, employees, investors, the general public and, where relevant, specific publics such as patients, members or local communities are each measured in their own daily survey, with their own questions and their own sample, and each is read through the same behavioural model.

The parallel design serves two purposes. The first is triangulation: when several groups and several segments within them are measured on comparable evaluations, the average stakeholder evaluation of the organisation, and the average change in stakeholder behaviour, can be estimated with the differences between groups made visible rather than averaged away. A reputation that is rising among customers and falling among employees is two findings, and the dashboard shows both. The second is contagion: because the groups are measured on the same frame, the model can estimate where a change among one group reaches another, in which direction and with what delay. A public issue that becomes an employee concern, or an employee signal that reaches customers, is seen as a dated path rather than inferred after the fact.

The model behind it

The model treats the organisation and its stakeholders as a network of exchanges, in line with social exchange theory (Blau, 1964; Cropanzano & Mitchell, 2005) and network theory (Granovetter, 1973). Macro trends, events and contact channels change what a group believes; beliefs change how the group evaluates the organisation; evaluations change whether the group buys, works, invests or speaks well of it. Every path is estimated every evening as a causal coefficient and shown only when it reaches statistical significance.

What the client receives is one dashboard with a view per stakeholder group and per segment, the causal coefficients for each, the cross-group paths, the dated breaks, and every raw record from every study.

Our approach

Real-time, which means daily. Every study collects a fresh sample every day of the year at the same rate. A change appears in the data on the day it happens, and the estimation that runs every evening carries it onto the dashboard the next morning. Daily collection is the condition for causal estimation: a break can be dated to a day only if there is data for every day.

Real people, verified. We work with several panel bureaus selected against our verification standard, run our own detection on every complete, and remove failures before they reach the model. No large language models, no synthetic respondents, no synthetic sampling.

One world model. Every service is embedded in one behavioural model that holds the economy, the news, the issues of the day and the contact channels at once, so the service's own effects can be isolated from everything else that moves people.

Causal intelligence for every service. The structural equation model is re-estimated every evening and shows the causal effect of more than fifty factors, with an effect shown only when it reaches statistical significance.

Dedicated, never omnibus. Every study is designed for one client and fielded for that client alone. Respondents are not shared between clients.

Raw data, always. Every respondent record is the client's own and can be downloaded at any moment, with the codebook and weights. The coefficients on the dashboard can be reproduced from the raw data.

Track record

Organisations in insurance, pensions, banking, energy, government and healthcare have used stakeholder intelligence from StakeholderWatch since 2013.