Demographic profile
This article has multiple issues. Please help improve it or discuss these issues on the talk page. (Learn how and when to remove these template messages)
|
A demographic profile is a form of demographic analysis in which information is gathered about a group to better understand the group's composition or behaviors for the purpose of providing more relevant services.
In business, a demographic profile is usually used to increase marketing efficiency. This is done by using gathered data to determine how to advertise products or services to specific audiences and identify gaps in marketing strategy.[1] By focusing on a specific audience, a company can more efficiently spend advertising resources to maximize sales.[2] This tactic is more direct than simply advertising on the basis that everyone is a potential consumer; while this may be true, it does not capitalize on the increased returns that more focused marketing can generate.[3]
Traditional demographic profiling involves gathering information on large groups of people in order to identify common trends,[4][unreliable source?] such as changes in population size or composition over time. These trends can be identified by analyzing data gained through surveys, censuses, in-store purchase information, records, registries, and so on.[2] Analysis of this information may promote change in services for a population subset, such as children, the elderly, or working-age people.[1] Newer methods of collecting and using information for demographic profiling include target-sampling, quota-sampling, and door-to-door screening.[5]
A comprehensive demographic profile is a powerful tool for marketing. Detailed information about potential customers provides insight into how to best sell them a product.[4] The term "demographic profiling" is sometimes used as a euphemism for industrial espionage.[6]
Methods edit
Historically, a census has been the most important tool when it comes to tracking demographic data such as population, births, deaths, and relationship status. The United States census was first introduced in 1790 and has been taken every 10 years since under constitutional law. While the questions in the US Census vary each decade, its aim is to quantifiable measure characteristics about the residents within its borders, such as marital status, age, sex, race, education status, employment status, and location. Even though the US Census is the most relied-on tool for collecting this information, it still has its flaws, such as overcount and undercount, which have caused controversy in previous years.[7]
Metadata provides a modern method of constructing demographic profiles.[8][unreliable source?] Certain types of digital metadata are generated by a user's online behavior—such as which websites are frequently visited, the amount of time spent on each website, the website interactions or purchase history, and which other users were interacted with—and serve as a digital footprint. Metadata collection is so pervasive that businesses record most aspects of a user's online activity.[4] Companies such as Google and Facebook make enormous profits through generating and processing metadata, which can then be used for targeted advertising. This process impacts the user's online experience, such as curating which ads are displayed or which websites are suggested.[8][4]
Controversy edit
Metadata collection has proven to be a controversial topic, with concerns expressed over how and why detailed personal information is saved and used by businesses.[8] To avoid future legislation limiting metadata collection, companies must act ethically and have people's privacy in mind when they target people for advertising.[8]
An example of how this could become an issue is presented by Ewing et al. (2013), who proposed the idea of a virtual reality shopping programme. Within this programme, the shopper is greeted by a virtual attendant who knows them by name and suggests an array of suitable clothing options based on their past purchases. The shopper is delighted by the seamless nature of this shopping experience. However, when they try to pay with their credit card, the virtual attendee reveals an unreasonably detailed knowledge about the shopper's financial situation, such as their credit score, payment history, and financial responsibility. This example highlights the need for discretion in the extent to which information is gathered, and how it is applied.[9][unreliable source?][relevant? ]
World demographic profile (2017) edit
| 2017 | |
|---|---|
| World Population | 7,405,107,650 (July 2017) |
| 10 Most Populated Countries (In Millions) | China: 1379.3 India: 1281.93 United States: 326.6 Indonesia: 260.58 Brazil: 207.35 Pakistan: 204.92 Nigeria: 190.63 Bangladesh: 157.83 Russia: 142.26 Japan: 126.45 |
| Age Structure | 0–14 years: 25.44% (male 963,981,944/female 898,974,458) 15–24 years: 16.16% (male 611,311,930/female 572,229,547) 25–54 years: 41.12% (male 1,522,999,578/female 1,488,011,505) 55–64 years: 8.6% (male 307,262,939/female 322,668,546) 65 years and over: 8.68% (male 283,540,918/female 352,206,092) |
| Dependency Ratio | total dependency ratio: 52.5 youth dependency ratio: 39.9 elderly dependency ratio: 12.6 potential support ratio: 7.9 |
| Median age | total: 30.4 years male: 29.6 years female: 31.1 years |
| Birth rate | 4.3 births every second |
| Death rate | 1.8 deaths every second |
| Maternal mortality | 216 deaths/100,000 live births |
| Sex ratio | at birth: 1.03 male(s)/female 0–14 years: 1.07 male(s)/female 15–24 years: 1.07 male(s)/female 25–54 years: 1.02 male(s)/female 55–64 years: 0.95 male(s)/female 65 years and over: 0.81 male(s)/female total population: 1.02 male(s)/female |
| Life Expectancy | total population: 69 years male: 67 years female: 71.1 years |
| Total Fertility Rate | 2.42 children born/woman |
| Languages | Mandarin Chinese: 12.2% Spanish: 5.8% English: 4.6% Arabic: 3.6% Hindi: 3.6% Portuguese: 2.8% Bengali: 2.6% Russian: 2.3% Japanese: 1.7%
|
| Religions | Christian: 31.4% Muslim: 23.2% Hindu: 15% Buddhist: 7.1% folk religions: 5.9% Jewish: 0.2% other: 0.8% unaffiliated: 16.4% |
Source: CIA World Factbook[10]
Demographic profiles of top 3 most populated countries edit
United States edit
| The United States | 2017 |
|---|---|
| Population | 326,625,791 |
| Age Structure | 0–14 years: 18.73% (male 31,255,995 per female 29,919,938) 15–24 years: 13.27% (male 22,213,952 per female 21,137,826) 25–54 years: 39.45% (male 64,528,673 per female 64,334,499) 55–64 years: 12.91% (male 20,357,880 per female 21,821,976) 65 years and over: 15.63% (male 22,678,235 per female 28,376,817) |
| Dependency Ratios | total dependency ratio: 51.2 youth dependency ratio: 29 elderly dependency ratio: 22.1 potential support ratio: 4.5 |
| Population Growth Rate | 0.81% |
| Birth Rate | 12.5 births per 1,000 people |
| Death Rate | 8.2 deaths per 1,000 people |
| Net Migration | 3.9 migrant(s) per 1,000 people |
| Sex Ratio | 0–14 years: 1.04 male(s) per female 15–24 years: 1.05 male(s) per female 25–54 years: 1 male(s) per female 55–64 years: 0.93 male(s) per female 65 years and over: 0.79 male(s) per female total population: 0.97 male(s) per female |
| Infant Mortality | total: 5.8 deaths per 1,000 live births male: 6.3 deaths per 1,000 live births female: 5.3 deaths per 1,000 live births |
| Ethnic Groups | White: 72.4% Black: 12.6% Asian: 4.8% Amerindian and Alaska native: 0.9% native Hawaiian and other Pacific Islander: 0.2% Other: 6.2% 'Two or more races: 2.9% |
| Maternal Mortality | 14 deaths per 100,000 live births |
| Education Expenditure | 4.9% of GDP |
| Languages | English: 79% Spanish: 13% other Indo-European: 3.7% Asian and Pacific island: 3.4% Other: 1% |
| Religions | Protestant: 46.5% Roman Catholic: 20.8% Jewish: 1.9% Mormon: 1.6% other Christian: 0.9% Muslim: 0.9% Jehovah's Witness: 0.8% Buddhist: 0.7% Hindu: 0.7%: other: 1.8% unaffiliated: 22.8% don't know/refused: 0.6% |
| Total Fertility Rate | 1.87 children born per woman |
| Life Expectancy at Birth | total population: 80 years male: 77.7 years female: 82.2 years |
Source: CIA World Factbook[10]
China edit
| China | 2017 |
|---|---|
| Population | 1,384,688,986 |
| Age Structure | 0–14 years: 17.15% (male 127,484,177/female 109,113,241) 15–24 years: 12.78% (male 94,215,607 per female 82,050,623) 25–54 years: 48.51% (male 341,466,438 per female 327,661,460) 55–64 years: 10.75% (male 74,771,050 per female 73,441,177) 65 years and over: 10.81% (male 71,103,029 per female 77,995,969) |
| Dependency Ratio | total dependency ratio: 37.7% youth dependency ratio: 24.3% elderly dependency ratio: 13.3% potential support ratio: 7.5% |
| Population Growth | 0.41% |
| Death Rate | 7.8 deaths per 1,000 people |
| Birth Rate | 12.3 births per 1,000 people |
| Sex Ratio | at birth: 1.15 male(s) per female 0–14 years: 1.17 male(s) per female 15–24 years: 1.14 male(s) per female 25–54 years: 1.04 male(s) per female 55–64 years: 1.02 male(s) per female 65 years and over: 0.92 male(s) per female total population: 1.06 male(s) per female |
| Maternal Mortality | 27 deaths per 100,000 live births |
| Infant Mortality | total: 12 deaths per 1,000 live births male: 12.3 deaths per 1,000 live births female: 11.7 deaths per 1,000 live births |
| Life Expectancy | Average: 75.7 years male: 73.6 years female: 78 years |
| Total Fertility Rate | 1.6 children born per woman |
| Ethnic Groups | Han Chinese: 91.6% Zhuang: 1.3%, other: 7.1% (Hui, Manchu, Uighur, Miao, Yi, Tujia, Tibetan, Mongol, etc.) |
| Religions | Buddhist: 18.2% Christian: 5.1% Muslim: 1.8% folk religion: 21.9% Hindu: < 0.1% Jewish: < 0.1% other: 0.7% (Daoist or Taoist) unaffiliated: 52.2% |
| Languages | - Standard Chinese or Mandarin - Yue (Cantonese) - Wu (Shanghainese) - Minbei (Fuzhou) - Minnan (Hokkien-Taiwanese) - Xiang - Gan |
| Literacy | total population: 96.4% male: 98.2% female: 94.5% |
Source: CIA World Factbook[10]
India edit
| India | 2017 |
|---|---|
| Population | 1,281,935,911 |
| Age Structure | 0–14 years: 27.34% (male 186,087,665 per female 164,398,204) 15–24 years: 17.9% (male 121,879,786 per female 107,583,437) 25–54 years: 41.08% (male 271,744,709/female 254,834,569) 55–64 years: 7.45% (male 47,846,122 per female 47,632,532) 65 years and over: 6.24% (male 37,837,801 per female 42,091,086) |
| Dependency Ratio | total dependency ratio: 52.2% youth dependency ratio: 43.6% elderly dependency ratio: 8.6% potential support ratio: 11.7% |
| Population Growth | 1.17% |
| Birth Rate | 19 births per 1,000 people |
| Death Rate | 7.3 deaths per 1,000 people |
| Sex Ratio | at birth: 1.12 male(s) per female 0–14 years: 1.13 male(s) per female 15–24 years: 1.13 male(s)/female 25–54 years: 1.06 male(s)/female 55–64 years: 1.01 male(s)/female 65 years and over: 0.9 male(s)/female total population: 1.08 male(s)/female |
| Infant Mortality | total: 39.1 deaths per 1,000 live births male: 38 deaths per 1,000 live births female: 40.4 deaths per 1,000 live births |
| Life Expectancy | total population: 68.8 years male: 67.6 years female: 70.1 years |
| Total Fertility Rate | 2.43 children born per woman |
| Maternal Mortality | 174 deaths per 100,000 live births |
| Ethnic Groups | Indo-Aryan: 72% Dravidian: 25% Other: 3% |
| Religions | Hindu: 79.8% Muslim: 14.2% Christian: 2.3% Sikh: 1.7% other and unspecified: 2% |
| Languages | Hindi: 41% Bengali: 8.1% Telugu: 7.2% Marathi: 7% Tamil: 5.9% Urdu: 5% Gujarati: 4.5% Kannada: 3.7% Malayalam: 3.2% Oriya: 3.2% Punjabi: 2.8% Assamese: 1.3% Maithili: 1.2% other: 5.9% |
| Literacy | total population: 71.2% male: 81.3% female: 60.6% |
Source: CIA World Factbook[10]
See also edit
References edit
- ^ a b "Lesson 3: Creating a Demographic Profile". MEASURE Evaluation.
- ^ a b FitzGerald, Maureen; Arnott, David (August 1996). "Understanding demographic effects on marketing communications in services". International Journal of Service Industry Management. 7 (3): 31–45. doi:10.1108/09564239610122947. ProQuest 233640609.
- ^ Jothi, A. L. (2015). "A study on influence of demographic factors on customers' preference towards cosmetic products". Sumedha Journal of Management. 4 (4): 39–48. ProQuest 1776777815.
- ^ a b c d "Tech Trends 2016: Understanding the driving forces behind the connected consumer". WARC.
- ^ Treiman, Donald J.; Lu, Yao; Qi, Yaqiang (8 December 2014). "New Approaches to Demographic Data Collection". Chinese Sociological Review. 44 (3): 56–92. doi:10.2753/csa2162-0555440303. PMC 3704565. PMID 23844330.
- ^ Hudson, John (1 December 2002). "Demographic profiling". Ubiquity. 2002 (December): 1. doi:10.1145/764008.763951. S2CID 28020979.
- ^ https://www.census.gov/prod/2001pubs/censr01-2.pdf[full citation needed]
- ^ a b c d "Why Big Data is a Small Idea: And why you shouldn't worry so much". WARC.
- ^ a b c d . Archived from the original on June 1, 2007.