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The Basic Tools for Building a Profile................................... 1 Evaluating Newspapers in the Marketplace........................... 3 Evaluating a Change in Readership..................................... 5 Readership of the Papers on a “Read Yesterday” and on a “Weekly Cume”Basis......................................................... 6 Reach and Exclusive Readers............................................ 8 Target Group - which papers reach which groups?................ 10 Coverage or Composition.................................................. 12 Household v.s. Population Weighting...................................13 Household v.s. Personal Ownership.....................................14 Filter Questions............................................................... 15 Summary Analysis.......................................................... 15 Volume Analysis.............................................................. 16 How to Read a Cross-Tab.................................................. 19 How to Read a Reach/Frequency Run................................. 21 How to Read E-Tabs......................................................... 23

THE BASIC TOOLS FOR BUILDING A PROFILE NADbank collects a wealth of data not only on newspaper readership and demographics, but also other media usage (including television, radio, magazines and the Internet), media habits and influences, lifestyle activities, life events, retail shopping habits and product usage and ownership. This data can be used on its own to identify target groups, but is most useful when combined with the newspaper readership and demographic data to plan a newspaper campaign. NADbank's authorized software suppliers provide users with a number of programmes to analyze the data in different combinations and formats. MARKET TABLES

Market Tables, in E-Tabs format on a CD, contain data for each of the measured markets. Every newspaper receives the Market Tables for its market as well as an “all markets summary”; agencies and advertisers may order these separately. Market Tables contain the following information: NEWSPAPER READERSHIP


* * * * * * *

read yesterday, 5 day cume, Saturday & Sunday readership, 6/7 day cume, weekly online readership, and total weekly readership number of last 5 weekday issues read number of last 4 Saturday and/or Sunday issues read time spent reading yesterday’s printed issue time spent reading last Saturday and/or Sunday printed issues total amount of time spent reading printed newspapers in the last week time spent reading a newspaper online in past week TV listing magazines read in past 7 days


* * * * * * * *

number of last 4 issues of TV listing magazines read television market quintiles radio market quintiles total time spent reading a magazine in past week total time spent on the Internet in past week total time spent watching television in past week radio stations listened to yesterday radio stations listened to last weekend



* * * * * * * * *

gender age education language spoken most often at home occupation personal & household income own or rent home type of dwelling household composition


IMS Canada (Interactive Market Systems Inc.) and Telmar HMS Ltd. are authorized by NADbank Inc. and provide NADbank members access to the database using software programmes. They have a number of programmes available and offer training to their clients. The two basic programmes are the cross-tab and the reach/frequency analysis, an overview of these programmes follows.


Cross-tabs "cross" or combine 2 or more pieces of information. They are used to: * retrieve basic information from the study, * determine who the users of a product are in order to develop a target group definition, * examine a newspaper's coverage against different target groups and other media, * retrieve information on a market or product and * retrieve "summary" data. A cross-tab example is included on page 19 to show the type of information available and how to interpret it. "summary" or "averages" data can be included in any cross-tab.




A reach/frequency analysis is performed to evaluate newspaper schedules against various target groups. They can tell you how many people are reached (reach), how often they are reached (frequency) and, if costs are input, the cost to reach a thousand people (cost per thousand or CPM). An example is shown on page 21.

EVALUATING NEWSPAPERS IN THE MARKETPLACE NADbank provides average weekday (M-F) and weekend readership data for all daily newspapers in the markets measured. You can look at the data for individual papers, for all papers in the market, or any group of papers or markets you wish to combine. Before you begin to look at individual newspaper profiles, you may want to examine the readership of newspapers in general. While specific opportunities can be masked by the generalities of "all markets" readership figures, it may be a good place to begin your investigation of daily newspapers as a medium. There is a wide variety of demographic data available in NADbank. This information can be used to build newspaper profiles for all the papers in your marketplace. YOU


* * * * * * *

Who reads the paper? Who reads the competition? What are the key demographic differences between papers in your market? Duplicated and exclusive readership Content readership Classified readership What makes one paper or combination of papers, the most efficient and effective advertising medium?


Changes in a marketplace can affect the readership data of

newspapers. Many factors impact newspaper readership data. Important factors to take into account are demographic shifts, changes in ethnic populations and competitive media. Demographic shifts can affect "Total Readership" and "Cume" as these metrics vary by age group. Changes in the ethnic population can impact reach results if the cultural groups tend to read newspapers in their language rather than the traditional English/French publications. Other factors to consider are new technology and the proliferation of new media choices. The Internet, and in particular online editions of daily newspapers, may affect readership of the printed products, especially for younger adults. There is growing popularity of the online editions of newspapers and for the Internet as a general source for news. Online readership is measured by NADbank. Step 1 Look at a single demographic characteristic to find the opportunities/strengths of any paper. Once you know some basic information you can begin to combine demographics with readership and product/retail/lifestyle data. Step 2 Consider different ways to look at and present the findings of the study particularly if there have been changes in readership levels. Evaluate the results from a variety of perspectives.

Consider looking at total readers in an analysis rather than reach numbers to evaluate year to year shifts. Also take into account the margin of error when looking at changes in readership levels (see chart 1). Reviewing a newspaper’s readership over the past several years may provide insights into readership and smooth out changes related to the margin of error. Comparisons within a market between more than one paper can often be more meaningful than year to year changes for an individual paper.

NOTE: The charts throughout this booklet are only to show how the data can be used and do not reflect data results of any particular year or newspaper.







Consider a market in which the population is projected to be 875,000 in NADbank year 1 (sample size of 800) and 925,000 in NADbank year 2. The reach for the weekday paper is 64% +/- 3.1 in NADbank year 1. In year 2, the population grows and the reach drops to 60% +/- 3.1. This is not a statistically significant decrease in readership; the high of 63% reached in year 2 is within the range of 61%-67% estimated in NADbank year 1. chart 1

The readership is 64% in NADbank year 1, which is 560,000 total readers (the error range applies to these numbers) and 555,000 total readers in NADbank year 2 is 60%. Expressed this way, the change in readership is less dramatic. Likewise, if the weekend readership is 74% (648,000 readers) in year 1 and 71% (656,000 readers) in year 2, this would represent a marginal, but not significant, increase in total readership. (see chart 2 on page 6)



chart 2




"Read yesterday" is a common way to evaluate a paper's reach and position in the market; however, looking at the dynamics of readership build throughout the week gives a full picture of a newspaper's audience. In chart 3, each newspaper has a different reach on a "read yesterday" basis and accumulates readers differently throughout the week, but each paper attains a similar weekly reach level. Paper "A" builds reach quickly then slowly accumulates the rest of its readership throughout the week. Paper "B" builds its total reach more slowly throughout the week, adding a few new readers on the weekend. Paper “B” also has a higher 5 day cume readership than paper "A" although "A" has the highest read yesterday reach. Most of the reach for paper "C" builds through the week with a small accumulation during the weekend.


chart 3

Look at the papers' readership by age and how that changes over the week. Different age groups, or any target group, will have different readership dynamics. Chart 4 shows the percentage of each age group who "read yesterday", over 5 days and over the total week, for any paper in "all markets". Generally, young adults do not read newspapers as often as older adults, meaning weekly readership accumulates more slowly for the younger age group. Ascertain readership dynamics for all demographic groups in order to build a profile for an individual paper. chart 4





Comparing target groups for individual newspapers will highlight differences in reach and readership dynamics. Reach for Paper "A" in chart 5 is higher for adults 18+ than for Paper "B", at 47% and 30% respectively. For men 25-34, the reach figures are reversed with Paper "B" reaching 44% compared to 33% for Paper "A". Unduplicated or exclusive reach, also differs when specific target groups are considered. Paper "A" has a higher percentage of adults 18+ who only read that paper (exclusive readership) than Paper "B". 79% of Paper "A"s readers read only Paper "A" compared to 67% of Paper "B"s readers. Again, this is reversed when men 25-34 are considered; the duplication is higher for men 25-34. Nineteen percent read both newspapers compared to all adults;10% read both papers.

chart 5



It is also important to look at the number of readers, not only the percentage reach of the target group. Different age and income groups are comprised of a different number of adults and therefore, by looking at the number of readers in a particular group a more accurate picture of the market will emerge. As the chart below indicates, 82% of adults 35-49 represents 4.3 million readers compared to 1.6 million or 84% of adults 18-24. Even though the target, adults 18-24, has a higher percentage reach, they represent a small proportion of weekly readers or total audience. When you look at the number of readers it is clear that the 35 - 49 year olds are the largest target group reading any paper in this market in a week.

chart 6




A number of commonly used demographic groups, based on Statistics Canada groupings, can be isolated and analyzed. These include: age, gender, education, employment, income, language first spoken, and household composition. A complete list of all the demographic characteristics collected can be found in the NADbank Study Guide.


As a newspaper, you can combine a variety of demographic characteristics with the readership patterns in your newspaper to determine exactly who your readers are. This information can be used to evaluate future business opportunities for your paper. It is also important to find out who is reading the competition and what differentiates your paper from theirs.


As an advertiser, you can find out who your customers are and determine what newspaper or combination of newspapers, they are reading. Often your customers read more than one newspaper in the market; look at reading patterns to determine the most efficient combination of papers to best reach your customers.


Paper A’s readership is made up of an older audience than Paper B’s audience. Compared to the population and to Paper A, Paper B attracts a much younger audience. (chart 7)


chart 7


Paper A’s readership is made up of a higher income audience than Paper B’s readership. Compared to the population and to Paper A, Paper B attracts a lower income audience. chart 8





When planning your campaign and selecting newspapers, you must consider how well each newspaper reaches your target group (coverage) and what percentage of that newspaper's total audience includes your target group (composition). Analysis of audience composition is often referred to as the newspaper's "profile". By adding costs to a reach/frequency run, you will also be able to see which paper or papers are the most efficient vehicles for reaching a target group. DEFINE THE TARGET GROUP


Target group is senior managers with personal incomes of $75K+. BUDGET VACATIONS

Target group is adults 50+ with household incomes of $30K-$50K.


Target group is men 18-34 who are employed.

More than one paper reaches the various target groups (see chart below). Which is the most efficient newspaper? chart 9



If each target group is taken as a percentage of the total readership of each of the newspapers in the market, the efficiency of each paper can be determined. In many campaigns, a combination of papers will be used. This information gives you a starting point for designing schedules for a reach/frequency analysis. CPM's for each target group in each paper should confirm this analysis. chart 10




When questions are based on household use or ownership, you must retrieve information based on household weighting. The percentages and indices you get in your cross-tab will be different if you access the data based on population weights; they are two different analyses. Make sure you know which question you are answering (an example is shown on the following page). Users need to be aware of whether they are examining household or individual questions to understand how to access the correct information. The user should select the appropriate weighting option, either population or household, when using software (e.g. IMS or Telmar Harris) or the E-tabs tables. 13





This tells you the number of households with income less than $50K that have adults with children.

This tells you the population of adults with children that live in households with income less than $50K.

HOUSEHOLD V.S. PERSONAL OWNERSHIP When analyzing a product category data, it is important to recognize that some questions are based on personal ownership and others on household ownership. Household ownership allows you to estimate "penetration," market size or volume of products and services. You can also look at household demographics, such as family composition, language, household income etc. Personal ownership questions allow you to get the same information as well as demographic information in order to build target group profiles. Many of the demographic descriptors can not be applied to household ownership questions, for example: age, gender, occupation, personal income, etc. The automotive category is ideal for looking at the differences between household and personal information. Car ownership is based on cars owned or leased in the household and the car the respondent drives most often. Since the category offers you both options, household or personal, it is important to make sure you know what question you want to have answered. For example, to determine the share of market for compact sedans, you would look at adults 18+ living in households with at least one car who say they own a compact sedan. To develop a profile of compact sedan owners, you would access data on adults 18+ who indicate the car they drive most often is a compact sedan. 14

FILTER QUESTIONS Another issue to consider when preparing a computer analysis is whether a preliminary filter question was asked prior collecting the data for the question in which you are interested. In some cases, questions are only asked of respondents if they answer in the affirmative to a screener or filter question. The subsequent questions are referred to as filtered questions. For example, many questions regarding shopping are only asked if the respondents have indicated that they shopped for that item. Therefore, if you use “yes, I personally bought shoes in the last year” as your base and ask the question “did you buy casual shoes?”, you will obtain the percentage of those adults 18+ who went shoe shopping who bought casual shoes in the past year. If you use adults 18+ as your base and ask the question “did you buy casual shoes?”, you will obtain the percentage of the population who bought casual shoes in the last year, which will be a lower percentage than the percentage of those who went shoe shopping who bought causal shoes. Remember to check the questionnaire or codebook to determine whether a question is filtered before proceeding to code your run.

There are an infinite number of ways to look at both readership and product/retail/lifestyle category data. To ensure you are getting the answers you seek, review the questionnaire and make sure the percentages are based on the appropriate "base" (household vs. population), "totals" and "filter" data.

SUMMARY ANALYSIS If you are interested in developing profiles for comparisons, between newspapers or stores for example, it can be useful to access summary data which is the average, median, or total for various demographic parameters. (see chart 11)



This information is available for: * * * * * *

Age Personal and household income Time spent reading the newspaper, in minutes TV viewing, in hours Radio listening, in hours Any frequency question, i.e. # of trips to the mall

chart 11

VOLUME ANALYSIS This type of analysis is very useful when you want to look beyond usage numbers and is particularly important when there is an uneven distribution of respondents within the categories you are looking at.

chart 12 Step 1 Usage by age group is a good example. Traditionally, we look at a standard group of age categories, 18-24, 25-34, 35-49, 5064 and 65+. The population is not equally divided among these groups. 16


chart 13

Step 2 The above chart shows that 75% of 18-24 year olds, living in the market, went online at least once in the past week, compared to only 69% of 35-49 year olds. Step 3 This does not mean that the bulk of Internet users are 18-24 since they make up only 12% of the population! By looking at chart 14, one can see that 75% of 12% is a smaller number of people than 69% of 33%. chart 14


Step 4 You can take this one step further and do a volume analysis to determine the total number of hours spent online by each age group. This will tell you what age group makes up the largest proportion of internet users. In the chart below, the total number of hours spent online by each age group is determined by multiplying the average number of hours spent online in a week with the number of adults in that age group (population). Each age group could have a different average number of hours spent online. chart 15

The analysis tells us that 35-49 year olds spent a total of 23 million hours online last week compared to 13 million hours for 18-24 year olds. While each 35-49 year old spends only an average of 12 hours online per week, as a group they still account for the largest percentage of internet users. The sheer size of the 35-49 age group makes them a dominant force in whatever they do!


KEY POINTS There are an infinite number of ways to use the data in the NADbank study. Remember to:

* Consult the questionnaire or the codebook before you prepare your analysis to ensure that your bases and filters and correct.

* Look beyond the percentages, volumes can often tell a more compelling story.

* Use the data to identify opportunities, not just to identify existing customers.

* When trending, focus on percentages rather than absolute numbers.

HOW TO READ A CROSS TAB All Product Markets Adults Age 18+


Read Yesterday (M-F) (any paper)

Read Last Weekend


Unwgt (00) Vert% Horz% Index

25666 146699 100 100 100

14887 85155 100 58.05 100

17076 97552 100 66.5 100

Age 18-24

Unwgt (00) Vert% Horz% Index

3620 17819 12.15 100 100

1799 9306 10.93 52.23 90

2097 10856 11.13 60.92 92

Average age

Unwgt (00) Vert% Horz% Index

25666 44 0.03 100 100

14887 45 0.05 102.27 176

17076 45 0.05 102.27 154

Total amount spent on women’s clothing in past year

Unwgt (00) Vert% Horz% Index

18918 62027688 42282.29 100 100

10810 35818804 42063.07 57.75 99

12656 41973152 43026.44 67.67 102

Average amount spent on women’s clothing in past year

Unwgt (00) Vert% Horz% Index

18918 605 0.41 100 100

10810 618 0.73 102.15 176

12656 616 0.63 101.82 153

NOTE: Caution should be used in analysis when sample size is less than 40, which is indicated in computer access reports by a single asterisk (*). (Extreme caution should be used when sample size is less than 20, so indicated by double asterisks (**). ) In a Telmar cross-tab the second column reads: Audience Resps %Col %Row Index

Please see facing page for definitions.



Number of actual people interviewed. Also called number of respondents or sample size (e.g. 25,666 adults 18+ were interviewed in all product markets). (00)/AUDIENCE

Projected Population. Number or people (in hundreds) that the sample (unwgt) represents, (e.g. there are 14,669,900 adults 18+ in all the product. VERT%/%COL (VERTICAL)

Composition of the column. Represents the relationship of the cell population to the total column, (e.g. 10.93% = 9306 divided by 85155). This reads: 10.93% of all adults, in all product markets, who read any paper yesterday, are 18-24 years old. HORZ%/%ROW (HORIZONTAL)

Composition of the row. Represents the relationship of the cell population to the total row population, (e.g. 52.23% = 9306 divided by 17819). This reads: 52.23% of all 18-24 year olds, in all product markets, read a paper yesterday. INDEX

A comparative measure. Points out strengths or weaknesses based on 100 being average. It is a comparison of the cell to the base (e.g. 90 = 10.93 divided by 12.15 or 52.23 divided by 58.05). This reads: Adults 18-24 are 10% less likely to read a daily newspaper than all adults 18+. SUMMARY DATA PRESENTED IN A CROSS TAB FORMAT

Average Age: The numbers in the Unwgt cell are the number of adults interviewed in all the product markets who read a paper yesterday (14,887 respondents). The average age is the data in the (00) cell. This reads as: the average age of all adults, in all product markets, who read a newspaper yesterday is 45. Total and Average Amount Spent on Women’s Clothing: The number in the Unwgt cell is the number of adults interviewed in all product markets who read a newspaper yesterday and purchased women’s clothing last year (10,810 respondents). The total dollars spent was $3.5 billion and the average spent was $618. 20



Pop (00):



Market A, managers and professionals with personal incomes of $75K+


Media/ Calculations:



Paper A Paper B Paper C

4 2 1

3 3 1

Total Inserts Gross Impressions Gross Rating Points Net Reach (00) Reach Percent Average Frequency

7 5823 337 1522 88.13 3.83

7 5902 342 1525 88.28 3.87


Projected population of the target group in hundreds, there are 171,700 managers and professionals with personal incomes of $75K+ in Market A. MEDIA/CALCULATIONS

Two schedules, A and B, were selected for 3 papers in the market. TOTAL INSERTS

The total number of insertions in the papers (7 for each schedule).



The total number of exposures or opportunities to see the advertisment in the schedule. For schedule A there are 582,300 potential viewings of the message. GROSS RATING POINTS

An aggregate of the total ratings in the schedule against the target group, the reach percent multiplied by the average frequency. In schedule A, 337 GRP's. NET REACH

The total number of adults 18+, in hundreds, reached by the schedule one or more times. In the first schedule 152,200 managers and professionals with personal incomes of $75K+ living in Market A will potentially be reached by the advertising message. REACH PERCENT

Percentage of the target group reached by the schedule. For schedule A, 88.13% of managers and professionals with personal incomes of $75K+ living in Market A will potentially be reached with this schedule. AVERAGE FREQUENCY

Average number of times the target group will be exposed to the advertising messages in the schedule. For schedule A, 88% of the target group will be reached and each will be exposed to the advertising message an average of 3.83 times.


23 TO


Newbury Times





Number of actual people interviewed. There are 233 respondents in the Newbury market.


The 233 respondents sampled represent the projected population of 75,300 adults 18+ in the Newbury market.


85 respondents weighted to 29,400 (39%) Newbury adults 18+ read Newbury Times yesterday. VERT%/%COL

Of all those who read Newbury Times yesterday, 51.1% were male. HORZ%/%ROW

41.2% of males in Newbury read Newbury Times yesterday.


45 is the average age of all Newbury adults 18+ who read at least one of the past M-F issues of Newbury Times.




Daily Newspaper and Research Terms Executive Readership Summary for each Study How to Read E-Tabs How to Read a Cross Tab How to Read a Reach Frequecy Run Margin of Error Planning Using NADbank Proprietary Questions Guidelines Sample Size Guidelines Study Guide for each Study Why Newspapers - various topics

NADbank Planning Booklet - English  

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