The investor's view of the same market. Kagan estimates what stations earn, tracks who owns what, and records what properties sell for.
Investment analysts, lenders, private equity, corporate development teams, brokers and appraisers — and the strategy side of large media companies. Formerly SNL Kagan, now folded into S&P Global Market Intelligence, it is a capital-markets product that happens to contain excellent media operating data.
Local sellers rarely have a seat, but the data reaches them indirectly through trade press coverage and through their own company's planning assumptions.
To let someone value a media asset without owning it. That means station-level and market-level revenue estimates, cash flow multiples, subscriber and household counts, ownership and license records, transaction histories, and long-range projections across broadcast, cable, satellite, streaming and digital.
Where Miller Kaplan reports what participants booked and BIA forecasts what a market will spend, Kagan estimates what an individual property earns and what it is therefore worth.
Public company filings, FCC ownership and license records, transaction filings and deal disclosures, regulatory data, proprietary analyst estimates, and direct company contact. For privately held broadcasters — most of the industry below the top markets — the revenue figures are analyst estimates built from market size, ratings position, format and comparable properties.
Ownership, license and transaction records are effectively current, because they track filings. Revenue estimates run behind: an estimate for a private station in a small market may be anchored on figures a year or more old and updated by model rather than observation.
Multiples move with the credit market, so a valuation benchmark more than a year old should be treated as history rather than guidance.
Two practical uses at the local level. First, it is the fastest way to establish who actually owns and controls a competing signal, and what else that owner holds — useful when a prospect says they are already talking to someone across the street. Second, when trade coverage or a corporate memo cites what a market is worth or what a cluster earns, Kagan is very often the underlying source, and knowing that tells you how much confidence the figure deserves.
Analysts reconcile disclosed financials from public companies against regulatory records and market data, then build estimates for private properties using comparables — market revenue size, audience share, format, signal coverage and ownership scale. Transaction data is captured from filings and public announcements and normalized into multiples of broadcast cash flow.
The output is estimate-heavy by design. It is honest about being an analyst's view rather than a reported figure, which is a different epistemic status from a Miller Kaplan pool number.