Name a company. Signal reads its public evidence each month and shows whether the story is holding together or drifting.
Built on the Net Entropy Score framework. Working paper on SSRN.
Signal is not a one-time scanner. It is a monthly monitoring layer that builds a timeline for each company you track, on the Net Entropy Score framework.
NES Signal uses aggregate public-signal analysis. Individual reviews are not republished or quoted. Outputs are directional research, not representative customer surveys or statements of fact about any company.
We do not publish the companies you track. Reads are delivered privately.
Signal zones are directional bands. They do not mean a company is good or bad. They describe how consistently the public evidence appears to support the company’s stated story over time.
Anonymized illustrations showing how public-signal reads moved relative to later public events, and in one case how the read matched what the operator’s own management already knew. Brands are not named, no individual review is quoted, and no business, financial, or investment outcome is predicted.
We tracked an independent hospitality property across public review signal for six months. The read showed consistency slipping as guest expectations shifted: once the property moved under a major global hotel brand, guests began measuring it against the standardized consistency of every other branded property in that group, where as an independent it had been able to cater locally and manage expectations directly. On a later call, the company’s top leadership independently confirmed the drivers the read had surfaced, including under-investment relative to the new branded benchmark.
Shared with permission and fully anonymized. A single engagement, n = 1: an illustrative example where a public-signal read matched the operator’s own assessment, not evidence of forecasting accuracy, causation, or predictive reliability. Directional research built from public information; no property or brand is named and no individual review is quoted.
Request the full case study →An aggregate public-signal read placed the brand in the lowest NES public-signal band at the time of analysis. Eleven days later, a separate public announcement reported a workforce reduction of roughly 22 percent. The read did not rely on non-public information and should be treated as an illustrative timing example, not evidence of causation or forecast accuracy.
Single observation, n = 1. This is an illustrative timing example, not evidence of forecasting accuracy, causation, or predictive reliability. NES public signal is directional research, not deterministic analysis and not a prediction about any company.
Request the full read →A retrospective read assembled from public retail review signal showed consistency holding in the Healthy but Constrained zone across the period, broadly consistent with the brand’s observed public trajectory. Shown as a stable-signal counterexample, not every read points down.
Illustrative and built only from public information. Directional research output, not a representative survey or a statement of fact about the brand.
Request the full read →Our first public benchmark reads how DTC brand websites hold together: the typical score, where they win and lose, and what the best do differently. A quick way to see the NES framework in action before you track a company.
See the DTC benchmark →The sample includes a signal zone, monthly delta, six-read trend, source-stream breakdown, confidence level, top watchpoints, and what changed since the previous month.
Signal is built on the Net Entropy Score framework. NES measures consistency, not popularity. It looks at whether a company’s promise, proof, customer evidence, and public narrative hold together over time.
Most tools track sentiment, traffic, mentions, or reputation. Signal tracks consistency drift.
Signal reads are directional research outputs based on publicly available information. They are not investment advice, legal advice, financial forecasts, or factual ratings of company performance.
We build the first monthly read and start tracking.