7 datasets found
  1. Consumer characteristics used by marketers in targeting worldwide 2021

    • statista.com
    Updated Jul 9, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Consumer characteristics used by marketers in targeting worldwide 2021 [Dataset]. https://www.statista.com/statistics/1345085/consumer-characteristics-define-target-segments/
    Explore at:
    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2021
    Area covered
    Worldwide
    Description

    During a survey carried out in November 2021 among marketers from ** countries worldwide, ** percent stated their organizations used past purchases to define target consumer segments. Consumer demographics, such as age, gender, income, or location, were used most often, named by ** percent of respondents.

  2. d

    Audience Targeting Data | 330M+ Global Devices | Audience Data & Advertising...

    • datarade.ai
    .json, .csv
    Updated Feb 4, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DRAKO (2025). Audience Targeting Data | 330M+ Global Devices | Audience Data & Advertising | API Delivery [Dataset]. https://datarade.ai/data-products/audience-targeting-data-330m-global-devices-audience-dat-drako
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Feb 4, 2025
    Dataset authored and provided by
    DRAKO
    Area covered
    Czech Republic, Curaçao, Armenia, Russian Federation, Equatorial Guinea, Serbia, Namibia, Suriname, Eritrea, San Marino
    Description

    DRAKO is a Mobile Location Audience Targeting provider with a programmatic trading desk specialising in geolocation analytics and programmatic advertising. Through our customised approach, we offer business and consumer insights as well as addressable audiences for advertising.

    Mobile Location Data can be meaningfully transformed into Audience Targeting when used in conjunction with other dataset. Our expansive POI Data allows us to segment users by visitation to major brands and retailers as well as categorizes them into syndicated segments. Beyond POI visits, our proprietary Home Location Model determines residents of geographic areas such as Designated Market Areas, Counties, or States. Relatedly, our Home Location Model also fuels our Geodemographic Census Data segments as we are able to determine residents of the smallest census units. Additionally, we also have audiences of: ticketed event and venue visitors; survey data; and retail data.

    All of our Audience Targeting is 100% deterministic in that it only includes high-quality, real visits to locations as defined by a POIs satellite imagery buildings contour. We never use a radius when building an audience unless requested. We have a horizontal accuracy of 5m.

    Additionally, we can always cross reference your audience targeting with our syndicated segments:

    Overview of our Syndicated Audience Data Segments: - Brand/POI segments (specific named stores and locations) - Categories (behavioural segments - revealed habits) - Census demographic segments (HH income, race, religion, age, family structure, language, etc.,) - Events segments (ticketed live events, conferences, and seminars) - Resident segments (State/province, CMAs, DMAs, city, county, sub-county) - Political segments (Canadian Federal and Provincial, US Congressional Upper and Lower House, US States, City elections, etc.,) - Survey Data (Psychosocial/Demographic survey data) - Retail Data (Receipt/transaction data)

    All of our syndicated segments are customizable. That means you can limit them to people within a certain geography, remove employees, include only the most frequent visitors, define your own custom lookback, or extend our audiences using our Home, Work, and Social Extensions.

    In addition to our syndicated segments, we’re also able to run custom queries return to you all the Mobile Ad IDs (MAIDs) seen at in a specific location (address; latitude and longitude; or WKT84 Polygon) or in your defined geographic area of interest (political districts, DMAs, Zip Codes, etc.,)

    Beyond just returning all the MAIDs seen within a geofence, we are also able to offer additional customizable advantages: - Average precision between 5 and 15 meters - CRM list activation + extension - Extend beyond Mobile Location Data (MAIDs) with our device graph - Filter by frequency of visitations - Home and Work targeting (retrieve only employees or residents of an address) - Home extensions (devices that reside in the same dwelling from your seed geofence) - Rooftop level address geofencing precision (no radius used EVER unless user specified) - Social extensions (devices in the same social circle as users in your seed geofence) - Turn analytics into addressable audiences - Work extensions (coworkers of users in your seed geofence)

    Data Compliance: All of our Audience Targeting Data is fully CCPA compliant and 100% sourced from SDKs (Software Development Kits), the most reliable and consistent mobile data stream with end user consent available with only a 4-5 day delay. This means that our location and device ID data comes from partnerships with over 1,500+ mobile apps. This data comes with an associated location which is how we are able to segment using geofences.

    Data Quality: In addition to partnering with trusted SDKs, DRAKO has additional screening methods to ensure that our mobile location data is consistent and reliable. This includes data harmonization and quality scoring from all of our partners in order to disregard MAIDs with a low quality score.

  3. U.S. population by generation 2024

    • statista.com
    • ai-chatbox.pro
    Updated May 13, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). U.S. population by generation 2024 [Dataset]. https://www.statista.com/statistics/797321/us-population-by-generation/
    Explore at:
    Dataset updated
    May 13, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Millennials were the largest generation group in the United States in 2024, with an estimated population of ***** million. Born between 1981 and 1996, Millennials recently surpassed Baby Boomers as the biggest group, and they will continue to be a major part of the population for many years. The rise of Generation Alpha Generation Alpha is the most recent to have been named, and many group members will not be able to remember a time before smartphones and social media. As of 2024, the oldest Generation Alpha members were still only aging into adolescents. However, the group already makes up around ***** percent of the U.S. population, and they are said to be the most racially and ethnically diverse of all the generation groups. Boomers vs. Millennials The number of Baby Boomers, whose generation was defined by the boom in births following the Second World War, has fallen by around ***** million since 2010. However, they remain the second-largest generation group, and aging Boomers are contributing to steady increases in the median age of the population. Meanwhile, the Millennial generation continues to grow, and one reason for this is the increasing number of young immigrants arriving in the United States.

  4. Parameter values, sample properties and demographic models for the...

    • plos.figshare.com
    xls
    Updated Jan 21, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Zhendong Huang; Jerome Kelleher; Yao-ban Chan; David Balding (2025). Parameter values, sample properties and demographic models for the simulation study. [Dataset]. http://doi.org/10.1371/journal.pgen.1011537.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jan 21, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Zhendong Huang; Jerome Kelleher; Yao-ban Chan; David Balding
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Unless otherwise stated, 25 simulation replicates were generated in each scenario. Model Ga is used for inferences given true IBD and Model Gb is used for inferences from inferred IBD. The value of r is assumed known for all inferences, whereas μ, ϵ and N(g), g ≥ 0, are targets of inference.

  5. D

    HDTV (High-definition Television) Market Report | Global Forecast From 2025...

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 12, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dataintelo (2024). HDTV (High-definition Television) Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-hdtv-high-definition-television-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Sep 12, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    HDTV (High-definition Television) Market Outlook



    The global HDTV market size was valued at USD 85 billion in 2023 and is expected to reach approximately USD 135 billion by 2032, growing at a compound annual growth rate (CAGR) of 5.2% during the forecast period. The growth factor driving this market includes the ever-increasing consumer demand for superior viewing experiences, driven by technological advancements and enhanced content availability.



    One of the primary growth factors of the HDTV market is the continuous technological innovation in the television industry. The transition from standard definition (SD) to high definition (HD) has revolutionized the viewing experience, providing consumers with sharper images, vibrant colors, and more immersive sound quality. Innovations such as OLED and QLED technology further enhance picture quality, driving consumer demand. Additionally, the rise of smart TVs, which integrate internet streaming services, has also contributed significantly to market growth by offering a multifaceted entertainment experience.



    The availability of diverse content in high-definition formats has also played a crucial role in driving the HDTV market. The proliferation of HD channels and the rising popularity of streaming services such as Netflix, Amazon Prime, and Disney+ provide ample high-definition content that necessitates the use of HDTVs. This trend is further augmented by the increasing adoption of 4K and 8K content, which requires compatible displays, thus pushing consumers to upgrade their existing television sets. Broadcasters, content creators, and streaming service providers are continually enhancing their HD content libraries, ensuring a steady demand for HDTVs.



    The affordability factor has been another key driver for the HDTV market. The price of HDTVs has seen a significant decline over the past few years due to advancements in manufacturing processes and the economies of scale achieved by manufacturers. This price reduction has made high-definition televisions accessible to a broader demographic, including middle and lower-income households. Additionally, various financing options and attractive offers from retailers and e-commerce platforms have further facilitated the purchase of HDTVs, thereby propelling market growth.



    From a regional perspective, the Asia Pacific region is expected to witness the highest growth rate in the HDTV market during the forecast period. The rapid urbanization, increasing disposable incomes, and a burgeoning middle class in countries such as China and India are contributing to the high demand for HDTVs. Moreover, the presence of major television manufacturers in this region, coupled with government initiatives aimed at digitalizing the broadcasting sector, further bolsters the market growth.



    Resolution Analysis



    The HDTV market is segmented by resolution into 720p, 1080p, 4K, and 8K categories. Each of these segments caters to different consumer needs and price points, driving the overall market dynamics. The 1080p segment, also known as Full HD, has been the most prevalent resolution, providing a balanced combination of performance and affordability. While it was the industry standard for many years, its market share is gradually being overtaken by higher resolutions such as 4K and 8K.



    The 4K resolution segment, also known as Ultra HD, is experiencing significant growth due to its superior picture quality. With four times the pixels of 1080p, 4K offers remarkable clarity and detail, making it an attractive option for consumers seeking a premium viewing experience. The increasing availability of 4K content across various platforms, including streaming services, gaming consoles, and Blu-ray discs, is further fueling this segment's growth. Moreover, the prices of 4K TVs have been decreasing, making them more accessible to the average consumer.



    The 8K resolution segment, though currently in its nascent stage, is poised for substantial growth in the coming years. Offering sixteen times the resolution of 1080p and four times that of 4K, 8K TVs provide an unparalleled viewing experience. As more 8K content becomes available and broadcasting standards evolve, the adoption of 8K TVs is expected to increase. Manufacturers are also investing heavily in research and development to enhance 8K technology and bring down costs, which will likely boost this segment's growth.



    The 720p resolution segment, often referred to as HD Ready, still holds a niche market. These televisions are generally more affordable and are suitabl

  6. f

    Definition of blue/white collar by ANZSCO Level 1 major groups.

    • plos.figshare.com
    xls
    Updated Apr 18, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yiping Yan; Abraham Leung; Matthew Burke; James McBroom (2024). Definition of blue/white collar by ANZSCO Level 1 major groups. [Dataset]. http://doi.org/10.1371/journal.pone.0301001.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 18, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Yiping Yan; Abraham Leung; Matthew Burke; James McBroom
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Definition of blue/white collar by ANZSCO Level 1 major groups.

  7. Literacy rate in India 1981-2022, by gender

    • statista.com
    • ai-chatbox.pro
    Updated May 30, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Aaron O'Neill (2025). Literacy rate in India 1981-2022, by gender [Dataset]. https://www.statista.com/topics/10801/demographics-of-india/
    Explore at:
    Dataset updated
    May 30, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Aaron O'Neill
    Area covered
    India
    Description

    Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2022, the degree of literacy in India was about 76.32 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

  8. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Consumer characteristics used by marketers in targeting worldwide 2021 [Dataset]. https://www.statista.com/statistics/1345085/consumer-characteristics-define-target-segments/
Organization logo

Consumer characteristics used by marketers in targeting worldwide 2021

Explore at:
Dataset updated
Jul 9, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Nov 2021
Area covered
Worldwide
Description

During a survey carried out in November 2021 among marketers from ** countries worldwide, ** percent stated their organizations used past purchases to define target consumer segments. Consumer demographics, such as age, gender, income, or location, were used most often, named by ** percent of respondents.

Search
Clear search
Close search
Google apps
Main menu