How is TV viewership measured?

I’m sure you must have read the headlines. You know, the kind where we get to hear how badly a highly anticipated show did, just hours after it came on TV. Or how well a particular show is doing against shows on competing TV networks? My question is, how do these people measure these numbers, and measure them so quickly?


Think about it for a second. Television is, for the most part, a broadcast medium. That is, our television sets mostly just receive data and hardly ever send anything back. You could say that this communication channel is mostly one way.

The Wikipedia page on Nielson ratings sheds some light on the matter:

One involves the use of viewer “diaries,” in which a target audience self-records its viewing (or listening) habits.

I’m not sure how much trust I can put in this methodology. But there is hope:

A more technologically sophisticated system has used Set Meters, which are small devices connected to every television in selected homes. These devices gather the viewing habits of the home and transmit the information nightly to Nielsen through a “Home Unit” connected to a phone line.

But this still doesn’t sound like a good solution. I also read somewhere that another popular methodology involves calling up randomly selected people and questioning them about their viewing habits!!

These days the situation is still a little bit better. Set-top boxes and  DVRs are becoming increasingly prevalent. These devices are significant more powerful and smarter than their ancestors, in the sense that they already do a fair bit of communication with your cable company, and hence it is conceivable that they enable collection of more accurate usage statistics.

Overall, it seems like a hard problem to me, since television has traditionally not been a connection oriented medium. This might change moving forward as IPTV and on-demand videos become more common. If you have some more information on the nitty-gritties of how this all works, please do share!


  1. Steve Loughran

    * in the UK, Sky TV require your satellite receiver to be connected to the phone line; it loads up viewer stats on every single household.

    * I could imagine something with bluetooth in scanning the # and ID of all discoverable devices. Better yet, you’d add a feature like phone-control so that people would want to bond their phones to the box. Then you could log #of viewers, and even who they were. The final step would be to cache/stream specific adverts to specific individuals

    • Tel

      Absolute rubbish about in the UK Sky require you to be connected to your phone line. It does not require you to be connected to the phone line. Mine isn’t! So how the hell do they know what I’m watching?
      The day after Question time on which contrversial politcal party leader Nick Griffin appeared, it was estimated over 8 MILLION VIEWERS WATCHED THE SHOW!
      The numbers were made up by the BBC media as if to show more than 4 times the regular amount of viewers tuned in to the most boring show on EARTH to up their ratings and advertise next week’s show. Simple as that.

  2. Harsha

    One of my friends used to work in Nielsen. He said that most of their ratings are based on viewership in households that participate in their monitoring. Nielsen hands out instrumented remotes to these households and the remote is assigned to one particular member in the household. The latter step enables Nielsen to not only track the number of participants that viewed a particular program, and for how long, etc., but also to break down the viewers based on categories such as age, sex, etc.

    As you mention in your post, the self-selecting nature of the sampled population raises obvious concerns over the validity of this data.

  3. Bruce Roberson

    Marketplace (US Television Household Estimates Designated Market Area(DMA)

    Sales figures and _______________, no data, no off audience, 1 0.2876 Internet Products and Serviced goods?

    Miami-Fort Lauderdale, Florida 1.352
    Orlando-Daytona Beach-Melbourne, Florida 1.281
    Charlotte, North Carolina 0.981
    Baton Rouge, Louisiana 0.285
    Tallahassee, FL – Thomasville, GA 0.247
    Augusta, GA 0.222
    Gainesville, Florida 0.114
    Lake Charles, Louisiana 0.083
    Alexandria, Louisiana 0.078

    April 22 – , 2009

    1:25 pm Message 604 Bad Content Form

    April 23, 2009

    1.3 – 3.3% (Second rate quote in operation, $227 million?)

    Single Payroll Exempt? $82,250.00 – $171,550.00
    $171,550.00 – $372,950.00
    $372,950.00 – over

    Pricing Matrix – Since advertising the designs, the counter only shows me the clicks. Visitors and queries are all with a .com? The month created a pair and there maybe another run. To the last digit before recycling to zero again.

    25% 28% 33% 35%

    $12.50 $12.78
    $12.75 $13.03
    $13.00 $13.28
    $13.25 $13.53
    $13.50 $13.78
    $13.75 $14.03
    $14.00 $14.28
    $14.25 $14.53
    $14.50 $14.78
    $14.75 $15.03
    $15.00 $15.28
    $15.25 $15.53
    $15.50 $15.78
    $15.75 $16.03
    $16.00 $16.28
    $16.25 $16.53
    $16.50 $16.78
    $16.75 $17.03
    $17.00 $17.28
    $17.25 $17.53
    $17.50 $17.78


    April 28, 2009

    Amateur Publishings? Nielsen/Net Ratings Reports Internet Penetration and Usage for Top 20 Local Markets (Business Wire, April 12, 2000)

    Employee Identification Number 80-0120261, and industry data with local level marketing segments to circuit? Local Market reports site traffic, average time spent in a market.

    Federal Reserve Board Conference – August 30, 2005

    A trigger and updated every year in the month of April. Lists the distressed or underserved nonmetropolitan, middle income geographics. Unemployment rates at 1.5% of a national average. Poverty rate of 20% and population losses of 10% to a decennial census? Migration loss and advertisers, agencies, news and information, content is not a trend to open? 5%

    Sole Proprietor Television (PEG Access)

    Demographic data about the market, was construed from county-level Census Bureau data. Population and income, which is aggregated to the Direct Marketing Association level. The data used is the total population of the DMA. The Direct Marketing Association’s per capita income and the percent of classified as black and as Hispanic. DMAs with large populations likely have greater aggregate demand for news. Demand may also be affected by the ethnic background and the average income of people in the market.

    The market defined is the DMA, as defined by Nielsen for its ratings service. Almost all broadcast television stations are carried by their local Multichannel Video Programming Distributions, including cable companies and the Direct Broadcast Satellite providers. Thus their geographic reach is much larger that for radio stations. This is why the market definition, used by Nielsen for measuring ratings for television stations, the DMA, is much larger than the markets used by Arbitron for rating radio stations, the Arbitron radio metro market.

    The ownership and station characteristics data from BIA and FCC Media Ownership Study Number 2: Ownership Structure and Robustness of Media included dummy variables that indicated: (1) whether the station was locally owned; (2) whether the station was minority owned; (3) whether the station was female owned; (4) whether the station was participating in local marketing/management agreement (LMA) with another station in the same market, in which one station’s operations were managed by the other station, or it was managing the operations of another station; (5) whether the station was a non-commercial station; (6) whether the station was a VHF frequency (channels 2 -13); (7) whether the station owned and operated by one of the big four networks; (8) whether the station was cross-owned with a radio station in the same city; and (9) whether the station was cross-owned with a newspaper in the same city.

    Ownership can also affect programming decisions of a station through its impact on the cost of obtaining news programming. There may be economies of scale of providing news programming, such that the average cost of providing news concerning a larger geographic area is lower for owners of many stations. This lower cost may also be obtained from economies of scope obtained from sharing news stories with co-owned radio stations and newspapers. Note that this scale economies effect may not be important to the extent, that independent stations can enjoy the same benefits by affiliating with a national network, or if viewers value only local reporting or reporting concerning the local impact of a story. The scale economies effect may even work against increased news programming. The extent to which scale economies affects the quantity of news programming, should show up in the coefficients to the variables measuring the size of the owner, in terms of programming the co-owned stations provide within the market. The variables for cross-ownership with radio stations and newspapers within the market, should capture whether there are economies of scope of news programming.

    The ownership structure for the firm is also likely to affect a station’s programming, for two basic reasons, one relating to the demand in the market, the other relating to the cost of producing news. Concerning the demand side, much has been written in the economies literature about how a station would be expected, ceteris paribus, to want to position its programming further apart from the programming of a co-owned station, in order to maximize the joint audience of the two stations, even if this lowers somewhat the audience of the given station.

    “A debtor that is self-employed and incurs trade credit in the production of income from such employment is engaged in business?”

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