Geodemographic Segmentation Data from Caliper Corporation contain demographic data in a way that is easy to visualize and interpret. We provide 8 segments and 32 subsegments for exploring the demographic makeup of neighborhoods across the country.

Demografy is a privacy by design customer demographics prediction AI platform.

Core features: - Demographic segmentation - Demographic analytics - API integration - Data export

Key advantages: - 100% coverage of lists - Accuracy estimate before purchase - GDPR-compliance as no sensitive data is required. Demografy can work with only first names or masked last names

Use cases: - Actionable analytics about your customers to get demographic insights - Appending missing demographic data to your records for customer segmentation and targeted marketing campaigns - Enhanced personalization knowing you customer better

Unlike traditional solutions, you don’t need to know and disclose your customer or prospect addresses, emails or other sensitive information. You can provide even masked last names keeping personal data in-house. This makes Demografy privacy by design and enables you to get 100% coverage of your audience since all you need to know is names.

According to a survey conducted by CSP Magazine in 2019, ** percent of urban consumers stated that they are visiting convenience stores more often than they were two years ago, versus only ** percent of rural consumers and ** percent of suburban customers.

With Versium REACH Demographic Append you will have access to many different attributes for enriching your data.

Basic, Household and Financial, Lifestyle and Interests, Political and Donor.

Here is a list of what sorts of attributes are available for each output type listed above:

Basic: - Senior in Household - Young Adult in Household - Small Office or Home Office - Online Purchasing Indicator
- Language - Marital Status - Working Woman in Household - Single Parent - Online Education - Occupation - Gender - DOB (MM/YY) - Age Range - Religion - Ethnic Group - Presence of Children - Education Level - Number of Children

Household, Financial and Auto: - Household Income - Dwelling Type - Credit Card Holder Bank - Upscale Card Holder - Estimated Net Worth - Length of Residence - Credit Rating - Home Own or Rent - Home Value - Home Year Built - Number of Credit Lines - Auto Year - Auto Make - Auto Model - Home Purchase Date - Refinance Date - Refinance Amount - Loan to Value - Refinance Loan Type - Home Purchase Price - Mortgage Purchase Amount - Mortgage Purchase Loan Type - Mortgage Purchase Date - 2nd Most Recent Mortgage Amount - 2nd Most Recent Mortgage Loan Type - 2nd Most Recent Mortgage Date - 2nd Most Recent Mortgage Interest Rate Type - Refinance Rate Type - Mortgage Purchase Interest Rate Type - Home Pool

Lifestyle and Interests: - Mail Order Buyer - Pets - Magazines - Reading
- Current Affairs and Politics
- Dieting and Weight Loss - Travel - Music - Consumer Electronics - Arts
- Antiques - Home Improvement - Gardening - Cooking - Exercise
- Sports - Outdoors - Womens Apparel
- Mens Apparel - Investing - Health and Beauty - Decorating and Furnishing

Political and Donor: - Donor Environmental - Donor Animal Welfare - Donor Arts and Culture - Donor Childrens Causes - Donor Environmental or Wildlife - Donor Health - Donor International Aid - Donor Political - Donor Conservative Politics - Donor Liberal Politics - Donor Religious - Donor Veterans - Donor Unspecified - Donor Community - Party Affiliation

GapMaps Panorama Segmentation Data from Applied Geographic Solutions (AGS) is built on over three decades of experience in the creation and use of geodemographic segmentation systems in the United States and Canada. Building on and integrating the existing suite of AGS modeling and analytical tools, GapMaps Panorama Segmentation Data creates actionable perspective on an increasingly complex and rapidly churning demographic landscape.

GapMaps Segmentation Data consists of sixty eight segments currently paired with the industry leading GfK MRI survey, providing the essential linkage between neighborhood demographics and consumer preferences and attitudes.

The segments include: 01 One Percenters 02 Peak Performers 03 Second City Moguls 04 Sprawl Success 05 Transitioning Affluent Families 06 Best of Both Worlds 07 Upscale Diversity 08 Living the Dream 09 Successful Urban Refugees 10 Emerging Leaders 11 Affluent Newcomers 12 Mainstream Established Suburbs 13 Cowboy Country 14 American Playgrounds 15 Comfortable Retirement 16 Spacious Suburbs 17 New American Dreams 18 Small Town Middle Managers 19 Outer Suburban Affluence 20 Rugged Individualists 21 New Suburban Style 22 Up and Coming Suburban Diversity 23 Enduring Heartland 24 Isolated Hispanic Neighborhoods 25 Hipsters and Geeks 26 High Density Diversity 27 Young Coastal Technocrats 28 Asian-Hispanic Fusion 29 Big Apple Dreamers 30 True Grit 31 Working Hispania 32 Struggling Singles 33 Nor'Easters 34 Midwestern Comforts 35 Generational Dreams 36 Olde New England 37 Faded Industrial Dreams 38 Failing Prospects 39 Second City Beginnings 40 Beltway Commuters 41 Garden Variety Suburbia 42 Rising Fortunes 43 Classic Interstate Suburbia 44 Pacific Second City 45 Northern Blues 46 Recessive Singles 47 Simply Southern 48 Tex-Mex 49 Sierra Siesta 50 Great Plains, Great Struggles 51 Boots and Brews 52 Great Open Country 53 Classic Dixie 54 Off the Beaten Path 55 Hollows and Hills 56 Gospel and Guns 57 Cap and Gown 58 Marking Time 59 Hispanic Working Poor 60 Bordertown Blues 61 Communal Living 62 Living Here in Allentown 63 Southern Small City Blues 64 Struggling Southerners 65 Forgotten Towns 66 Post Industrial Trauma 67 Starting Out 68 Rust Belt Poverty

This profile is designed to accompany the Joint Strategic Needs Assessment (JSNA) chapter on Demographics, which looks at segmenting the borough’s population by their most significant health and social care need. This supplement looks at adults (aged 18 and over) instead of the overall population, because the health and social care need segments covered in this section are more common in adults.

This map shows the dominant lifestyle segment in an area in 2012, based on Esri's Tapestry Segmentation system. The map displays the dominant segment's LifeMode summary group color. The "dominant" segment is most useful at at tract and block group levels.

Tapestry Segmentation, Esri's geodemographic market segmentation system, classifies U.S. neighborhoods into 65 segments based on their socioeconomic and demographic composition. For a broader view of markets, segments are grouped into 12 LifeMode Summary Groups that reflect lifestyles/life stages and 11 Urbanization Summary Groups that show levels of affluence and population density.

The geography depicts States at greater than 50m scale, Counties at 7.5m to 50m scale, Census Tracts at 200k to 7.5m scale, and Census Block Groups at less than 200k scale.

Scale Range: 1:591,657,528 down to 1:72,224

For more information on this map, including our terms of use, visit us online at http://goto.arcgisonline.com/maps/Demographics/USA_Tapestry

With Versium REACH Demographic Append you will have access to many different attributes for enriching your data.

Basic, Household and Financial, Lifestyle and Interests, Political and Donor.

Here is a list of what sorts of attributes are available for each output type listed above:

Basic: - Senior in Household - Young Adult in Household - Small Office or Home Office - Online Purchasing Indicator
- Language - Marital Status - Working Woman in Household - Single Parent - Online Education - Occupation - Gender - DOB (MM/YY) - Age Range - Religion - Ethnic Group - Presence of Children - Education Level - Number of Children

Household, Financial and Auto: - Household Income - Dwelling Type - Credit Card Holder Bank - Upscale Card Holder - Estimated Net Worth - Length of Residence - Credit Rating - Home Own or Rent - Home Value - Home Year Built - Number of Credit Lines - Auto Year - Auto Make - Auto Model - Home Purchase Date - Refinance Date - Refinance Amount - Loan to Value - Refinance Loan Type - Home Purchase Price - Mortgage Purchase Amount - Mortgage Purchase Loan Type - Mortgage Purchase Date - 2nd Most Recent Mortgage Amount - 2nd Most Recent Mortgage Loan Type - 2nd Most Recent Mortgage Date - 2nd Most Recent Mortgage Interest Rate Type - Refinance Rate Type - Mortgage Purchase Interest Rate Type - Home Pool

Lifestyle and Interests: - Mail Order Buyer - Pets - Magazines - Reading
- Current Affairs and Politics
- Dieting and Weight Loss - Travel - Music - Consumer Electronics - Arts
- Antiques - Home Improvement - Gardening - Cooking - Exercise
- Sports - Outdoors - Womens Apparel
- Mens Apparel - Investing - Health and Beauty - Decorating and Furnishing

Political and Donor: - Donor Environmental - Donor Animal Welfare - Donor Arts and Culture - Donor Childrens Causes - Donor Environmental or Wildlife - Donor Health - Donor International Aid - Donor Political - Donor Conservative Politics - Donor Liberal Politics - Donor Religious - Donor Veterans - Donor Unspecified - Donor Community - Party Affiliation

Healthy Paws Pet Insurance Market size was valued at USD 6.87 Million in 2023 and is projected to reach USD 17.54 Million by 2031, growing at a CAGR of 14.3% during the forecast period 2024-2031.

Global Healthy Paws Pet Insurance Market Drivers

The market drivers for the Healthy Paws Pet Insurance Market can be influenced by various factors. These may include:

Increasing Pet Ownership and Humanization of Pets: The global trend of increasing pet ownership, coupled with the growing tendency to treat pets as family members, has driven significant demand for comprehensive pet healthcare solutions, bolstering the market for Healthy Paws Pet Insurance. As more households adopt pets and seek to offer them the best possible care, the necessity for veterinary insurance to manage potential health expenses grows.

Rising Veterinary Costs: Advances in veterinary medicine, while offering cutting-edge treatments, have significantly increased the cost of pet healthcare. This surge in expenses for surgeries, diagnostics, and routine care has heightened pet owners' awareness of the need for insurance coverage, thus driving growth in the pet insurance market, including companies like Healthy Paws.

Growing Awareness of Pet Health and Wellness: There is a rising awareness among pet owners regarding the importance of preventive care and timely treatment for their pets' well-being. As pet health knowledge becomes more widespread through social media and veterinary advocacy, more owners are inclined to seek insurance plans to ensure affordability and access to necessary treatments, directly benefiting Healthy Paws Pet Insurance.

Technological Advancements in Veterinary Care: Innovations in veterinary diagnostics and treatment options have revolutionized pet healthcare, making it more efficient but also more expensive. Healthy Paws Pet Insurance benefits from this trend as pet owners look to protect themselves from unforeseen high veterinary costs by investing in comprehensive insurance policies that cover these advanced treatments.

Increasing Chronic Conditions in Pets: Pets, like their human counterparts, are increasingly diagnosed with chronic conditions such as diabetes, arthritis, and cancer. The management of these illnesses typically involves significant financial outlays for continuous care and medications. This trend underscores the necessity for robust pet insurance options, thus driving demand for providers like Healthy Paws Pet Insurance.

Improved Insurance Claim Processing and Customer Service: Enhanced customer experience in the pet insurance industry, characterized by streamlined claim processes, user-friendly mobile apps, and superior customer service, has made policies more attractive. Companies like Healthy Paws that invest in these improvements witness increased enrollment as they offer greater convenience and reliability to pet owners.

Regulatory Support and Industry Standards: The establishment of clearer regulatory frameworks and industry standards is providing a more stable and trustworthy environment for the pet insurance market to thrive. Regulations that protect consumer rights and ensure transparency in insurance policies help in building consumer confidence, benefiting reputable providers such as Healthy Paws Pet Insurance.

Growing Popularity of E-Commerce and Digital Platforms: The increasing preference for online shopping and digital services has made it easier for pet owners to access and purchase pet insurance. Healthy Paws has leveraged these platforms effectively to market their insurance products, allowing for easier comparison of plans, more detailed information, and streamlined purchasing processes, further driving market expansion.

Expansion of Veterinary Networks: As more veterinary clinics and hospitals partner with pet insurance providers, the network of accessible care for insured pets expands. Healthy Paws Pet Insurance, with a broad network of participating vets, becomes a more attractive option for pet owners looking for widespread and quality veterinary care coverage.

Economic Resilience and Disposable Income: Even amidst economic fluctuations, the pet insurance market has shown resilience, with pet owners continuing to invest in their pets' health. An increase in disposable income, particularly among millennials who form a significant portion of pet owners, supports continued expenditure on pet insurance, ensuring sustained market growth for companies like Healthy Paws Pet Insurance.

Pandemics such as Covid-19 pose tremendous public health communication challenges in promoting protective behaviours, vaccination, and educating the public about risks. Segmenting audiences based on attitudes and behaviours is a means to increase the precision and potential effectiveness of such communication. The present study reports on such an audience segmentation effort for the population of England, sponsored by the United Kingdom Health Security Agency (UKHSA) and involving a collaboration of market research and academic experts. A cross-sectional online survey was conducted between 4 and 24 January 2022 with 5525 respondents (5178 used in our analyses) in England using market research opt-in panel. An additional 105 telephone interviews were conducted to sample persons without online or smartphone access. Respondents were quota sampled to be demographically representative. The primary analytic technique was k means cluster analysis, supplemented with other techniques including multi-dimensional scaling and use of respondent ‐ as well as sample-standardized data when necessary to address differences in response set for some groups of respondents. Identified segments were profiled against demographic, behavioural self-report, attitudinal, and communication channel variables, with differences by segment tested for statistical significance. Seven segments were identified, including distinctly different groups of persons who tended toward a high level of compliance and several that were relatively low in compliance. The segments were characterized by distinctive patterns of demographics, attitudes, behaviours, trust in information sources, and communication channels preferred. Segments were further validated by comparing the segmentation variable versus a set of demographic variables as predictors of reported protective behaviours in the past two weeks and of vaccine refusal; the demographics together had about one-quarter the effect size of the single seven-level segment variable. With respect to managerial implications, different communication strategies for each segment are suggested for each segment, illustrating advantages of rich segmentation descriptions for understanding public health communication audiences. Strengths and weaknesses of the methods used are discussed, to help guide future efforts.

GapMaps GIS Data sourced from Applied Geographic Solutions includes over 40k Demographic variables across topics including estimates & projections on population, demographics, neighborhood segmentation, consumer spending, crime index & environmental risk available at census block level.

This factsheet breaks down Camden’s population by looking at health conditions, and then by their age, sex, ethnicity, and deprivation. Understanding the size and characteristics of each segment helps us plan healthcare resources and service delivery effectively for each group, as well as the population in general.

Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

Social Media Analytics Market Outlook

The global market size of social media analytics was valued at approximately $5.2 billion in 2023 and is projected to reach around $21.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 17.1% over the forecast period. This remarkable growth can be attributed to the increasing importance of data-driven decision making in modern business strategies. The expansion of social media platforms and the corresponding surge in user-generated data have driven the need for advanced analytics tools to make sense of this information, thereby acting as a significant growth factor for the market.

One of the primary growth factors for the social media analytics market is the increasing adoption of data analytics by organizations to gather meaningful insights from vast amounts of unstructured social media data. Companies across various sectors are now leveraging social media analytics to understand customer behavior, preferences, and trends, which in turn helps in refining marketing strategies and improving customer experience. The proliferation of smartphones and internet penetration has further fueled the frequency and volume of social media interactions, providing a more extensive dataset for analytics.

Another key driver is the integration of artificial intelligence (AI) and machine learning (ML) technologies with social media analytics platforms. These advanced technologies are enabling more accurate sentiment analysis, demographic segmentation, and predictive analytics. AI and ML algorithms can process large datasets more efficiently, allowing businesses to quickly respond to market changes and consumer demands. Moreover, the development of sophisticated natural language processing (NLP) tools is enhancing the capability of social media analytics to understand and interpret human language, making sentiment analysis more precise and actionable.

The increasing demand for personalized marketing is also significantly contributing to the growth of the social media analytics market. Brands are now focusing on delivering highly personalized content to their target audiences to enhance engagement and conversion rates. Social media analytics provides detailed insights into individual user profiles, preferences, and behaviors, enabling marketers to create more targeted and effective campaigns. The shift towards influencer marketing is another trend driving the market, as businesses seek to measure the impact and ROI of their influencer partnerships through analytics.

Social Networking Sites have become integral to the way individuals and businesses interact and communicate. These platforms provide a space for users to share content, connect with others, and engage in discussions. The rise of social networking sites has significantly contributed to the volume of data available for analysis, offering businesses a wealth of information to understand consumer behavior and preferences. As these sites continue to evolve, they are increasingly being used as tools for marketing, brand building, and customer engagement. The ability to analyze data from social networking sites allows companies to tailor their strategies and improve their offerings, ultimately enhancing customer satisfaction and loyalty.

From a regional perspective, North America dominates the social media analytics market, with a substantial share attributed to the early adoption of advanced technologies and the presence of major social media platforms. The Asia Pacific region is expected to witness the fastest growth during the forecast period, driven by the expanding user base of social media platforms and increasing investments in digital marketing. The European market is also growing steadily, supported by stringent data privacy regulations that are compelling organizations to adopt more robust analytics solutions. Latin America and the Middle East & Africa are emerging markets with significant growth potential due to increasing internet penetration and social media usage.

Component Analysis

The social media analytics market can be segmented by component into software and services. The software segment comprises tools and platforms used to collect, analyze, and visualize social media data. These solutions range from basic sentiment analysis tools to comprehensive analytics platforms that offer real-time moni

Customer360Insights

The Customer360Insights dataset is a synthetic collection meticulously designed to mirror the multifaceted nature of customer interactions within an e-commerce platform. It encompasses a wide array of variables, each serving as a pillar to support various analytical explorations. Here’s a breakdown of the dataset and the potential analyses it enables:

Dataset Description

• Customer Demographics: Includes FullName, Gender, Age, CreditScore, and MonthlyIncome. These variables provide a demographic snapshot of the customer base, allowing for segmentation and targeted marketing analysis.
• Geographical Data: Comprising Country, State, and City, this section facilitates location-based analytics, market penetration studies, and regional sales performance.
• Product Information: Details like Category, Product, Cost, and Price enable product trend analysis, profitability assessment, and inventory optimization.
• Transactional Data: Captures the customer journey through SessionStart, CartAdditionTime, OrderConfirmation, OrderConfirmationTime, PaymentMethod, and SessionEnd. This rich temporal data can be used for funnel analysis, conversion rate optimization, and customer behavior modeling.
• Post-Purchase Details: With OrderReturn and ReturnReason, analysts can delve into return rate calculations, post-purchase satisfaction, and quality control.

Types of Analysis

• Descriptive Analytics: Understand basic metrics like average monthly income, most common product categories, and typical credit scores.
• Predictive Analytics: Use machine learning to predict credit risk or the likelihood of a purchase based on demographics and session activity.
• Customer Segmentation: Group customers by demographics or purchasing behavior to tailor marketing strategies.
• Geospatial Analysis: Examine sales distribution across different regions and optimize logistics. Time Series Analysis: Study the seasonality of purchases and session activities over time.
• Funnel Analysis: Evaluate the customer journey from session start to order confirmation and identify drop-off points.
• Cohort Analysis: Track customer cohorts over time to understand retention and repeat purchase patterns.
• Market Basket Analysis: Discover product affinities and develop cross-selling strategies.

This dataset is a playground for data enthusiasts to practice cleaning, transforming, visualizing, and modeling data. Whether you’re conducting A/B testing for marketing campaigns, forecasting sales, or building customer profiles, Customer360Insights offers a rich, realistic dataset for honing your data science skills.

Curious about how I created the data? Feel free to click here and take a peek! 😉

📊🔍 Good Luck and Happy Analysing 🔍📊

Organic Fast Food Market size was valued at USD 182.5 Billion in 2023 and is projected to reach USD 548.2 Billion by 2031, growing at a CAGR of 13.5% during the forecast period 2024-2031.

Global Organic Fast Food Market Drivers

The market drivers for the Organic Fast Food Market can be influenced by various factors. These may include:

Growing Health Consciousness: With an increasing number of consumers becoming more health-conscious and aware of the link between diet and well-being, there is a strong preference for organic ingredients, which are free from synthetic pesticides, fertilizers, and GMOs. The modern lifestyle, which emphasizes healthier habits and cleaner eating, has significantly boosted the demand for organic fast food. Environmental Awareness: Rising awareness about environmental sustainability and the ecological impact of conventional farming practices is driving consumers towards organic fast food. Organic farming is viewed as more environmentally friendly as it promotes biodiversity, reduces pollution from nitrogen run-off, and conserves water resources. Clean Label Trend: The clean label trend, characterized by demands for transparency in food labeling and minimal ingredient lists, aligns closely with organic fast food offerings. Consumers are increasingly seeking out products with understandable, natural ingredients, propelling the market forward. Innovation in Organic Offerings: Continuous innovation within the organic fast food sector, including new product launches and the introduction of varied cuisines, keeps the market dynamic. With companies leveraging creative combinations of ingredients and flavors, organic fast food appeals to a broader audience including younger demographics and food enthusiasts. Government Support and Regulations: Many governments are actively promoting organic farming and consumption through subsidies, certifications, and awareness programs. These regulations help to assure consumers about the authenticity and benefits of organic products, thereby fostering market growth. Expanded Distribution Channels: The expansion of distribution channels, including the rise of organic fast food chains, online delivery platforms, and mobile food trucks, makes it increasingly convenient for consumers to access organic fast food. Enhanced availability contributes significantly to the market expansion. Socio-Economic Changes: Changes in socio-economic conditions, such as increased disposable incomes and a growing middle class in many parts of the world, have led to greater spending on premium food options, including organic fast food. Consumers are more willing to invest in food that is perceived to be of higher quality and healthier. Influence of Social Media: Social media plays a crucial role in driving trends in the food industry, and organic fast food is no different. Platforms like Instagram and TikTok are filled with influencers and nutritionists advocating for organic diets and highlighting the benefits of organic fast food, thus influencing consumer preferences. Corporate Social Responsibility (CSR): Many companies are incorporating organic fast food into their CSR initiatives, aiming to showcase their commitment to sustainability and health. This strategic alignment not only enhances their corporate image but also drives consumer trust and loyalty towards organic options. Technological Advancements: Technological advancements in food production, preservation, and supply chain management have enabled the scalability of organic fast food. Innovations such as precision farming and blockchain for traceability ensure quality and authenticity, making organic fast food more reliable and appealing to consumers.

This forms part of Camden’s Joint Strategic Needs Assessment, focussing on the demographics of our population. This data shows breakdowns of Camden’s population by health conditions, age and sex, and by Camden ward, as supplementary information of the 2015 Camden population segmentation profile (https://opendata.camden.gov.uk/Health/Camden-Demographics-Population-Segmentation-2015/v6fr-wght). It provides the number of people, percentage of the whole population (prevalence) and Camden average for each breakdown. It only focuses on the population aged 18 and over and doesn’t show breakdowns for those diagnosed with learning disability or those aged under 65 who are diagnosed with dementia due to small numbers.

This note provides only a brief overview of the main points of the PSM and it should be read in conjunction with the PRISM Demand Model User Manual and with other PRISM technical documents, such as the model validation and forecasting reports, published by TfWM, which can be accessed at the following website:https://www.tfwm.org.uk/strategy/data-insight/transport-modelling/about-prism/prism-reports and the technical reports which cover the fundamentals of the model's structure, which can be found by searching for PRISM 2011 on RAND's website, such as with the following link:https://www.rand.org/search.html?query=PRISM%202011

Uncover lifestyle patterns with geo-precision: 401M verified profiles across 7 Asian countries for segmentation and KYC. Our demographic datasets include rich geo-spatial attributes that power hyper-local segmentation, regional risk scoring, and location-driven behavioral insights.

Percentage of responses in the range 0-6 for 'Happy Yesterday' by LSOA in the First ONS Annual Experimental Subjective Wellbeing survey, April 2011 - March 2012

The Department for Communities and Local Government (DCLG) has estimated the expected wellbeing of residents at Lower-layer Super Output Area (LSOA) level. The purpose is to illustrate the likely degree of variation between neighbourhoods.

These are modelled estimates for local areas based on national findings from the ONS Annual Population Survey 2011-2012. They are not the actual survey responses of people living in those areas [1]. As such, DCLG encourage local areas to test these expected findings against their own local knowledge and data.

DCLG used CACI’s ACORN geo-demographic segmentation to estimate the likely wellbeing characteristics of each neighbourhood. Analysis of the APS provided a national profile of wellbeing by ACORN Type, with estimates of average subjective wellbeing and low subjective wellbeing for each of the 56 Types. The national profile was then applied to localities, to reflect their composition according to ACORN Type [2].

The method presumes the national profile of wellbeing for the ACORN types is broadly the same in each local authority. For all of the subjective wellbeing measures, DCLG tested this assumption broadly held across the nine regions. As a result, DCLG made a minimal number of adjustments to the profiles for life satisfaction, worthwhile, and happy yesterday, and determined that the method was not robust for modelling anxiety [3].

Feedback on the neighbourhood estimates and requests for further details of the methodology can sent to wellbeing@communities.gsi.gov.uk.

In October, DCLG will be producing wellbeing profiles to enable users to apply the same methodology using geo-demographic classifications: Experian’s MOSAIC and ONS’s Output Area Classification (OAC).

[1] This is because sample sizes from the APS do not permit reliable estimates of subjective wellbeing below the 90 unitary authorities and counties reported in the First ONS Annual Experimental Subjective Well-being Results.

[2] ACORN is a segmentation based on shared characteristics of people’s life-stage, income, profession and housing, as well as characteristics of places including whether they are urban, suburban or rural. Each respondent on the APS had been classified into one ACORN Type, based on the full postcode in which they live – approximately 16 addresses.) ACORN provided estimates of the population in each ACORN Type in each LSOA and local authority district.

[3] These adjustments were made only where there was reliable evidence (based on samples of more than 100 respondents) from APS that the national wellbeing ACORN profile was substantially different from the regional one, and where the implications for neighbourhood maps would be highly geographically clustered.