1 / 44

Consumer Survey Datasets

Consumer Survey Datasets. What are they? How do you interpret the data? A brief look at Mediamark Reporter Online …. Simmons. What are they?. They are the tabulated, numeric results of huge surveys of many consumers. The major producers are: Simmons Market Research Bureau (SMRB)

nascha
Download Presentation

Consumer Survey Datasets

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Consumer Survey Datasets What are they? How do you interpret the data? A brief look at Mediamark Reporter Online …

  2. Simmons What are they? They are the tabulated, numeric results of huge surveys of many consumers. • The major producers are: • Simmons Market Research Bureau (SMRB) • Mediamark Research Inc. (MRI) Mediamark Research & Intelligence

  3. Types of Data Collected: • Demographics (lots of them!) • Product usage • Brand preferences • Media usage • Media preferences • Lifestyle (psychographics, mostly in Simmons)

  4. Methodology: • Twice-a-year in-depth surveys of 20-30 thousand adult consumers. Includes: • ~10 days of keeping a ‘diary’ of all activities, purchases, consumption, media, etc. • In-person fieldworker interview of household • Data from surveys is ‘projected’ onto annual Census Bureau Population Estimates

  5. Limitations: • Separate studies for minors. • Best for consumer products, not so much for B2B products. • Academic libraries are onlyallowed to buy out-of-date data (1-year-old for Mediamark, 2-years-old for Simmons) • Mediamark is online, but only provides pre-formatted, ‘canned’ crosstab reports • Simmons is cd-rom data (no online access), but has a powerful interface that allows lots of customization

  6. Typical questions: • Demographically, who are the best buyers or customers of product x or brand y? • Demographically, who should the manufacturer target in order to increase market share? • How do I find psychographics for this target group? (Simmons only)

  7. Let’s briefly look at how to retrieve a crosstab in Mediamark Reporter, which is the easiest to use. Starting from the Libraries’ homepage, here’s how to get to it …

  8. Be sure to use the ‘online version’ of Mediamark Reporter. (The cd-rom version has much older data.)

  9. You’ll need this information when you first register for an account … It’s also repeated on a screen later in this Powerpoint file. If you’ve already registered, just go directly to www.mriplus.com/.

  10. Registration: Use your first.last@marquette.edu email to register for an account – ‘marquette’ must be spelled out in full. Both email address and the password you create are case sensitive!! After registering, you’ll receive an email message with an activation link from Mediamark. Login at left or Register for Freeto begin using MRI+. This account is free to you: the Libraries pay for the subscription to the database … By the way, the database works best with Internet Explorer.

  11. Mediamark registration • Use your Marquette email address & create a password • Use the format first.last@marquette.edu. ‘marquette’ must be spelled out in full in the domain name (@marquette.edu) • Password does NOT need to be your eMarq password • Use the MU Libraries’ address & phone number: 1355 W. Wisconsin Ave. Milwaukee, WI 53233 414.288.7556 • Go to your eMarq account to complete registration

  12. Mediamark Reporter Once you’ve logged in, click on this link to launch the Reporter … A new browser window will be launched, so be sure that your browser allows pop-ups.

  13. Volume Types: Product: profiles who uses different product types, brands, etc. Also includes profiles of behaviors (e.g. leisure activities / hobbies, sports participation, voting, lottery, etc.) Media: profiles the media used by different demographic groups (e.g. by age, occupational group, educational level, etc.). Includes the media quintiles. Magazine Qualitative: provides a qualitative measure of how a magazine is used by readers (e.g. where do they read it, with how much attention and thoroughness, do they take any action after reading it). Magazine Cumulative: provides 4-issue reach and frequency data for each title. Spring 2008 Product • Click in the Report Volume selection box to choose a report. This will trigger the appearance of another selection box … • In general, it’s better to start with the Spring datasets because they are usually larger.

  14. Scroll through the report categories to choose a product type, media user type (demographic group), etc. • You can also search by keyword. • ► But beware! Keyword searching works best with brand names and other distinctive single words. Until you are familiar with the database’s terminology, it can be less useful.

  15. The Submenus/Search Results AND Crosstab display… The left half of the screen shows the category submenus (or keyword search results). This is an awkward screen that tries to combine two different things …

  16. The Submenus/Search Results AND Crosstab display… The right half automatically shows a crosstab for the first selection on the left. The Crosstab on the right always reflects the variables highlighted on the left.

  17. “Beware the Asterisk, er, the Jabberwock, my son!” Whenever you see an asterisk (*), be aware that the sample size for this question in the survey was too small for statistical reliability. Use these data with caution. Educ: did not graduate HS * 33,991

  18. When you change the selection in the Category box, the variables in the Target box will also change … And so will the crosstab. Athletic Shoes – Brands Bought

  19. Here you see a new Crosstab, reflecting the selections on the left. So now the question is: how do you interpret these numbers?!

  20. Percent Across 18.0 26.7 27.3 24.7 15.2 8.8 4.5 28.4 25.5 22.8 25.7 23.5 21.8 Percent Down 100.0 18.9 27.1 26.6 16.4 7.0 4.0 24.2 42.4 35.5 21.7 39.4 34.6 Total Age 18-24 Age 25-34 Age 35-44 Age 45-54 Age 55-64 Age 65+ Men 18-34 Men 18-49 Men 25-54 Women 18-34 Women 18-49 Women 25-54 Total ‘000 222,210 28,312 39,835 43,118 43,296 31,707 35,941 34,257 66,661 62,432 33,891 67,280 63,818 Proj ‘000 40,091 7,558 10,868 10,661 6,589 2,800 1,615 9,716 16,999 14,231 8,710 15,806 13,887 Index 100 148 151 137 84 49 25 157 141 126 142 130 121 Athletic Shoes, Brands bought last 12 months: Nike Percent Across Percent Down Index Let’s enlarge this a bit … Then we have three calculated variables … These data are from the Census Bureau’s Annual Population Estimate Survey These data are projected, or extrapolated, from the Mediamark survey results.

  21. Percent Across 18.0 26.7 27.3 24.7 15.2 8.8 4.5 28.4 25.5 22.8 25.7 23.5 21.8 Percent Down 100.0 18.9 27.1 26.6 16.4 7.0 4.0 24.2 42.4 35.5 21.7 39.4 34.6 Total Age 18-24 Age 25-34 Age 35-44 Age 45-54 Age 55-64 Age 65+ Men 18-34 Men 18-49 Men 25-54 Women 18-34 Women 18-49 Women 25-54 Total ‘000 222,210 28,312 39,835 43,118 43,296 31,707 35,941 34,257 66,661 62,432 33,891 67,280 63,818 Proj ‘000 40,091 7,558 10,868 10,661 6,589 2,800 1,615 9,716 16,999 14,231 8,710 15,806 13,887 Index 100 148 151 137 84 49 25 157 141 126 142 130 121 What is the Index? The Index is a measure of the probability of finding a user in a specific small, group relative to the probability of finding a user in the larger, general population. Also called the ‘propensity to use’ … Athletic Shoes, Brands bought last 12 months: Nike Index 151 English ‘translation’: People who bought Nike athletic shoes in the past 12 months are 51% more likelyto be in the 25–34 age range than the general population.

  22. Percent Across 18.0 26.7 27.3 24.7 15.2 8.8 4.5 28.4 25.5 22.8 25.7 23.5 21.8 Percent Down 100.0 18.9 27.1 26.6 16.4 7.0 4.0 24.2 42.4 35.5 21.7 39.4 34.6 Total Age 18-24 Age 25-34 Age 35-44 Age 45-54 Age 55-64 Age 65+ Men 18-34 Men 18-49 Men 25-54 Women 18-34 Women 18-49 Women 25-54 Total ‘000 222,210 28,312 39,835 43,118 43,296 31,707 35,941 34,257 66,661 62,432 33,891 67,280 63,818 Proj ‘000 40,091 7,558 10,868 10,661 6,589 2,800 1,615 9,716 16,999 14,231 8,710 15,806 13,887 Index 100 148 151 137 84 49 25 157 141 126 142 130 121 How do you get that English ‘translation’? You subtract 100 from the value. If the answer is positive, you say ‘more likely’. Athletic Shoes, Brands bought last 12 months: Nike Index 151 151 – 100 = + 51% English ‘translation’: People who bought Nike athletic shoes in the past 12 months are 51% more likely to be in the 25–34 age range than the general population.

  23. Percent Across 18.0 26.7 27.3 24.7 15.2 8.8 4.5 28.4 25.5 22.8 25.7 23.5 21.8 Percent Down 100.0 18.9 27.1 26.6 16.4 7.0 4.0 24.2 42.4 35.5 21.7 39.4 34.6 Total Age 18-24 Age 25-34 Age 35-44 Age 45-54 Age 55-64 Age 65+ Men 18-34 Men 18-49 Men 25-54 Women 18-34 Women 18-49 Women 25-54 Total ‘000 222,210 28,312 39,835 43,118 43,296 31,707 35,941 34,257 66,661 62,432 33,891 67,280 63,818 Proj ‘000 40,091 7,558 10,868 10,661 6,589 2,800 1,615 9,716 16,999 14,231 8,710 15,806 13,887 Index 100 148 151 137 84 49 25 157 141 126 142 130 121 Athletic Shoes, Brands bought last 12 months: Nike Index But if the answer is negative... 49 – 100 = – 51% 49 English ‘translation’: People who bought Nike athletic shoes in the past 12 months are 51% less likely to be in the 55–64 age range than the general population.

  24. Index numbers • Index value 100 = dead average for total general population • However, there is really an average ‘range’: 90 – 110, or 85 – 115 • Therefore: index values ≥ 110 are significant index values ≤ 90 are significant

  25. Index = 100 Index = 110 Index = 90 The average range for index values: On this bell curve, all the average probability people fall between the 90 and 110 index lines. The people with greater and lesser probability, statistically speaking, are in the outside triangular areas.

  26. Use high and low index #’s to determine: • Demographics of ‘best’ or core customers • Demographics of low-use customers • Demographics of group to which you might aim an ad campaign.

  27. Index numbers are NOT enough! Index numbers are always and only comparative, NOT quantitative: they compare data for a small demographic group to the same data for the general population. Classic example: Asian-Americans have high index values (180-200) for the purchase of Hondas and Toyotas. However, they only constitute ~4.3% of the total population of the US (in 2005). Therefore, they cannot constitute a significant portion of the total number of the buyers of imported Japanese cars.

  28. Vertical % or % down numbers arequantitative! • Use % down/vertical % to see how many of your target group (column variable) also fall into a specific, smaller demographic (row variable). • Mediamark uses the label ‘% down’, and Simmons uses the label ‘vertical %’ – different names for the exact same value.

  29. Percent Across 18.0 26.7 27.3 24.7 15.2 8.8 4.5 28.4 25.5 22.8 25.7 23.5 21.8 Percent Down 100.0 18.9 27.1 26.6 16.4 7.0 4.0 24.2 42.4 35.5 21.7 39.4 34.6 Total Age 18-24 Age 25-34 Age 35-44 Age 45-54 Age 55-64 Age 65+ Men 18-34 Men 18-49 Men 25-54 Women 18-34 Women 18-49 Women 25-54 Total ‘000 222,210 28,312 39,835 43,118 43,296 31,707 35,941 34,257 66,661 62,432 33,891 67,280 63,818 Proj ‘000 40,091 7,558 10,868 10,661 6,589 2,800 1,615 9,716 16,999 14,231 8,710 15,806 13,887 Index 100 148 151 137 84 49 25 157 141 126 142 130 121 16,999 40,091 X 100 = 42.4% Athletic Shoes, Brands bought last 12 months: Nike Percent Down 40,091 Good English ‘translations’: Among buyers of Nike athletic shoes in the last 12 months, 42.9% were men aged 18–49. Men aged 18–49 constitute 42.4% of all buyers of Nike athletic shoes in the past 12 months. 42.4 16,999

  30. Index values + vertical %’s = • A good, reliable profile of best customers • A good profile of customer groups to target with an ad campaign The following slide will show a selection of rows on Nike buyers, mostly with higher index values and higher %’s down.

  31. What is missing here? Reasoning and explanations for these data …Context …

  32. You have to figure out the reasons for the data ... For example, look at the numbers for people in the two Census Regions, South and West. Nike buyers are less likely to live in the West (index=93; %down=20.8) , than in the South (index=103; %down=37.6). When you check the crosstabs for competitor brands, you find that in the West, the Vans shoe brand is much more popular ...

  33. You have to figure out the reasons for the data ... If you look at the data about people who’ve never married (index=137, %down=34.4) and focus especially on the index value, you might think that Nike buyers are mostly single. However, when you look at the numbers for people who are married, you see that married people do buy Nike’s. And in fact, they represent just over half of all Nike buyers (%down=52.0) even though their likelihood of buying is low-average (index=93). So how do you explain this? Look at the numbers for people with children in the household … Who do you think they’re likely buying for?!

  34. Sex and Race: For these two categories of variable, be aware of the underlying demographic composition of the country. Only when quantitative values (%’s down) diverge from the underlying demographics are they truly of interest. • For sex (gender), the US is close to 50% men and 50% women (except among the elderly). • For race or ethnic group, we are roughly* as follows: * This is an extract from the American Community Survey data for 2006-08. See the Census Bureau’s website for more complete data and explanations.

  35. Sex (gender) and Nike buyers: There is little difference in the Nike buying patterns for men (42.4%) and women (39.4%) in the age range 18-49.

  36. Race and Nike buyers: For race, there is a difference of note: 19.5% of Nike buyers are African-Americans, a larger proportion than the underlying composition would account for. And only 64.9% are white, a smaller proportion than accounted for by the underlying demographics.

  37. % across / horizontal % • Horizontal %’s are also quantitative • Use them to see how many of your row group also fall into your target (column) group. • This value is used mostly in media planning (e.g. when buying ads, you’ll need to know what percentage of a magazine’s readership fits into a particular demographic category.) • Know how to read this value, if only so that you can readily distinguish it from the % down / vertical %

  38. Percent Across 18.0 26.7 27.3 24.7 15.2 8.8 4.5 28.4 25.5 22.8 25.7 23.5 21.8 Percent Down 100.0 18.9 27.1 26.6 16.4 7.0 4.0 24.2 42.4 35.5 21.7 39.4 34.6 Total Age 18-24 Age 25-34 Age 35-44 Age 45-54 Age 55-64 Age 65+ Men 18-34 Men 18-49 Men 25-54 Women 18-34 Women 18-49 Women 25-54 Total ‘000 222,210 28,312 39,835 43,118 43,296 31,707 35,941 34,257 66,661 62,432 33,891 67,280 63,818 Proj ‘000 40,091 7,558 10,868 10,661 6,589 2,800 1,615 9,716 16,999 14,231 8,710 15,806 13,887 Index 100 148 151 137 84 49 25 157 141 126 142 130 121 16,999 66,661 X 100 = 25.5% Athletic Shoes, Brands bought last 12 months: Nike Percent Across Good English ‘translations’: Among all men aged 18–49, 25.5% bought Nike athletic shoes in the past 12 months. Buyers of Nike athletic shoes in the past 12 months constitute 25.5% of all men aged 18–49. 66,661 16,999 25.5

  39. The % down and % across values tell you about the relationship (or proportions) between three groups of people: those in the row variable, those in the column variable, and those in both. Let’s try looking at these two calculated variables, % down and % across, another way.

  40. Column: Bought Nike’s in last 12 mos. (40,091) Row: Men aged 18–49 (66,661) X: (16,999) • Above is an ordinary Venn diagram representing two of the variables, and their cross-section (X). • (Apologies: the circles are only very roughly proportional …) • Now let’s look at how % down and % across are calculated for these variables.

  41. % Down: • 16,999 • 40,091 X 100 = 42.4 % Column: Bought Nike’s in last 12 mos. (40,091) X: (16,999) Here you see that the cross-section of the two variables (X) represents 43% of the total for the column variable (people who bought Nike’s in the last 12 months).

  42. % Across: • 16,999 • 66,661 X 100 = 25.5 % Row: Men aged 18–49 (66,661) X: (16,999) Here you see that the cross-section of the two variables (X) represents 21% of the total for the row variable (men aged 18–49).

  43. And that’s our introduction to consumer survey datasets! What they are, and how to interpret the numbers … For more help with using consumer survey datasets (Mediamark or Simmons), please contact us at the Information Desk. 414.288.7556 Or, fill out the research consultation request form at: http://www.marquette.edu/library/research/consultations.shtml

More Related