Reputation research measures what people think of an organisation and tracks how that judgment changes. In the management literature, reputation is the collective assessment stakeholders hold of a firm's ability to deliver value and of the kind of organisation it is (Fombrun & Shanley, 1990; Rindova et al., 2005; Lange, Lee & Dai, 2011). It is one of the few assets a firm cannot buy, because it is formed in other people's heads and travels between them, and it is one of the few that reaches every stakeholder relationship at once: the customer deciding whether to buy, the graduate deciding whether to apply, the investor deciding whether to hold, the journalist deciding how to frame.

Character and capability

StakeholderWatch treats reputation as several evaluations rather than one score, because the research shows they behave differently. A firm's character reputation (its values, honesty and the way it treats people) and its capability reputation (whether it can deliver what it promises) move on different information, at different speeds, and recover in different ways (Mishina, Block & Mannor, 2012; Park & Rogan, 2019). A product failure damages capability and can be repaired by a demonstrated fix; a revelation about priorities damages character and is repaired only by sustained conduct. A combined score hides which has been hit, and therefore hides what to do. The dashboard shows both, alongside the broader sentiment and trust measures that most reputation trackers report.

How we run it

Reputation research at StakeholderWatch is run for one organisation at a time. The survey is designed for that organisation, with its own competitors, issues and channels, and fielded for it alone every day of the year among the stakeholders who matter to it. The daily rhythm is what makes the research causal. With a continuous series, the day on which a judgment shifts can be estimated and confirmed with a structural break test, the events of that week can be matched to it, and the structural equation model can estimate which of more than fifty factors caused the move and how much of it each explains. A quarterly wave can report that reputation fell; a daily series can say on which day, after what, and through which beliefs.

What the client receives is the standard set of reputation measures, read for any stakeholder group and any segment the sample supports, together with the causal coefficients behind them, the dated breaks, the peer comparison that separates sector movement from the firm's own, and every raw respondent record. Reputation, communications and public affairs teams use the dashboard directly; there is no report to wait for.

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

Since 2013 StakeholderWatch has run reputation research for insurers, pension funds, banks, retailers, energy and food companies, industry, governments and healthcare providers, several of them continuously since 2015. The findings from this work feed a research programme on reputation dynamics with VU Amsterdam, described on the Research page.