1) Data Introduction • The Consumer Behavior and Shopping Habits Dataset is a tabular collection of customer demographics, purchase history, product preferences, shopping frequency, and online and offline purchasing behavior.

2) Data Utilization (1) Consumer Behavior and Shopping Habits Dataset has characteristics that: • Each row contains detailed consumer and transaction information such as customer ID, age, gender, purchased goods and categories, purchase amount, region, product attributes (size, color, season), review rating, subscription status, delivery method, discount/promotion usage, payment method, purchase frequency, etc. • Data is organized to cover a variety of variables and purchasing patterns to help segment customers, establish marketing strategies, analyze product preferences, and more. (2) Consumer Behavior and Shopping Habits Dataset can be used to: • Customer Segmentation and Target Marketing: You can analyze demographics and purchasing patterns to define different customer groups and use them to develop customized marketing strategies. • Product and service improvement: Based on purchase history, review ratings, discount/promotional responses, etc., it can be applied to product and service improvements such as identifying popular products, managing inventory, and analyzing promotion effects.

Segments and demographic variables predicting Covid-19 protective behaviors.

Created with a 500 meter side hexagon grid, we undertook a regression analysis creating a correlation matrix utilising a number of demographic indicators from the Local Insight OCSI platform. This dataset is showing the distribution of the metrics that were found to have the strongest relationships, with the base comparison metric of Indices of Deprivation 2019 income deprivation affecting older people. This dataset contains the following metrics: IoD 2019 Income Deprivation Affecting Older People (IDAOPI) Score (rate) - The Indices of Deprivation (IoD) 2019 Income Deprivation Affecting Older People Index captures deprivation affecting older people defined as those adults aged 60 or over receiving Income Support or income-based Jobseekers Allowance or income-based Employment and Support Allowance or Pension Credit (Guarantee) or Universal Credit (in the 'Searching for work', 'No work requirements', 'Planning for work', 'Working with requirements' and 'Preparing for work' conditionality groups) or families not in receipt of these benefits but in receipt of Working Tax Credit or Child Tax Credit with an equivalised income (excluding housing benefit) below 60 per cent of the national median before housing costs. Asylum seekers aged 60 and over are not included in the Income Deprivation Affecting Older People Index. Rate calculated as = (ID 2019 Income Deprivation Affecting Older People Index (IDAOPI) numerator)/(ID 2019 Older population aged 60 and over: mid 2015 (excluding prisoners))*100.Pension Credit claimants who are single - Shows the proportion of people receiving Pension Credit who are single (as a % of all of pensionable age). Pension Credit provides financial help for people aged 60 or over whose income is below a certain level set by the law. Rate calculated as = (Pension Credit claimants, single)/(Population aged 65+)*100.Pension Credit claimants, Guarantee Element - Shows the proportion of people of retirement age receiving Pension Credit Guarantee Element. Pension Credit provides financial help for people aged 60 or over whose income is below a certain level set by the law. The Guarantee Element is payable to tops up incomes that are below a minimum threshold. Rate calculated as = (Pension Credit claimants, Guarantee Element)/(Population aged 65+)*100.Working-age DWP benefit claimants aged 50 and over - Shows the proportion of people aged 50-64 receiving DWP benefits. DWP Benefits are benefits payable to all people who need additional financial support due to low income, worklessness, poor health, caring responsibilities, bereavement or disability. The following benefits are included: Bereavement Benefit, Carers Allowance, Disability Living Allowance, Incapacity Benefit/Severe Disablement Allowance, Income Support, Jobseekers Allowance, Pension Credit and Widows Benefit. Figure are derived from 100% sample of administrative records from the Work and Pensions Longitudinal Study (WPLS), with all clients receiving more than one benefit counted only by their primary reason for interacting with the benefits system (to avoid double counting). Universal Credit (UC) and Personal Independence Payment (PIP) started to replace the benefits included in this measure from April 2013 when new Jobseeker's Allowance and Disability Living Allowance claimants started to move onto the new benefits in selected geographical areas. This rollout intensified from March 2016 onwards to capture all of the other Working age DWP Benefits. As UC and PIP are not included in this measure it no longer represent a complete count of working age people receiving DWP Benefits. As a result the measure was discontinued in November 2016. Rate calculated as = (Working-age DWP benefit claimants aged 50 and over) /(Population aged 50+)*100.People with numeracy skills at entry level 1 or below (2011) (%) - Shows the proportion of people with numeracy skills at entry level 1 or below. The Skills for Life Survey 2011 was commissioned by the Department for Business Innovation and Skills. The survey aimed to produce a national profile of adult literacy, numeracy and Information and Communication Technology (ICT) skills, and to assess the impact different skills had on people's lives. Each figure is a mean estimate of the number of adults with each skill level (or who do / do not speak English as a first language). The survey was conducted at regional level as a part interview part questionnaire. The interview comprised a background questionnaire followed by a pre-assigned random combination of two of the three skills assessments: literacy, numeracy and ICT. The background questionnaire was designed to collect a broad set of relevant demographic and behavioural data. This demographic data was used to model the information down to neighbourhood level using the neighbourhood characteristics of each MSOA to create a likely average skill level of the population within each MSOA. survey. Respondents who completed the questions allocated to the literacy and numeracy assessments were assigned to one of the five lowest levels of the National Qualifications Framework: Entry Level 1 or below; Entry Level 2; Entry Level 3; Level 1; or Level 2 or above. Each figure is a mean estimate of the number of adults with each skill level (or who do / do not speak English as a first language).IoD 2015 Housing affordability indicator -Social Grade (N-SEC): 8. Never worked and long-term unemployed - Shows the proportion of people in employment (aged 16-74) in the Approximated Social grade (N-SEC) category: 8. Never worked and long-term unemployed. An individual's approximated social grade is determined by their response to the occupation questions in the 2011 Census. Rate calculated as = (Never worked and long-term unemployed (census KS611))/(All usual residents aged 16 to 74 (census KS611))*100.Female healthy life expectancy at birth - Female healthy life expectancy at birth. Healthy life expectancy (HLE) is the average number of years that an individual might expect to live in "good" health in their lifetime. The 'good' health state used for estimation of HLE was based on self-reports of general health at the 2011 Census; specifically those reporting their general health as 'very good' or 'good' were defined as in 'Good' health in this context. The HLE estimates are a snapshot of the health status of the population, based on self-reported health status and mortality rates for each area in that period. They are not a guide to how long someone will actually expect to live in "good" health, both because mortality rates and levels of health status are likely to change in the future, and because many of those born in an area will live elsewhere for at least part of their lives.Sport England Market Segmentation: Pub League Team Mates - Shows the proportion of people living in the area that are classified as Pub League Team Mates in the Sports Market Segmentation tool developed by Sport England. The Pub League Team Mates classification group are predominantly aged 36-45 are a mix of married/single child and childless and likely to be engaged in a vocational job. For more details about the characteristics of this group see http://segments.sportengland.org/pdf/penPortrait-9.pdf. Sports Market Segmentation is a web-based tool developed by Sport England to help all those delivering sport to better understand their local markets and target them more effectively.IoD 2010 Income Domain, score - The Indices of Deprivation (IoD) 2010 Income Deprivation Domain measures the proportion of the population in an area experiencing deprivation relating to low income. The definition of low income used includes both those people that are out-of-work, and those that are in work but who have low earnings (and who satisfy the respective means tests). The domain forms part of the overall Index of Multiple Deprivation (IMD) 2010. The IMD 2010 is the most comprehensive measure of multiple deprivation available. Drawn primarily from 2008 data and presented at small area level, the IMD 2010 is a unique and invaluable tool for measuring deprivation nationally and across local areas. The concept of multiple deprivation upon which the IMD 2010 is based is that separate types of deprivation exist, which are separately recognised and measurable.People over the age of 65 with bad or very bad health - Shows the proportion of people over the age of 65 that reported to have bad or very bad health. Figures are self-reported and taken from the 2011 Census. Rate calculated as = (Bad or very bad health (census LC3206)/(Population aged 65+)*100

Food festivals have been a growing tourism sector in recent years due to their contributions to a region’s economic, marketing, brand, and social growth. This study analyses the demand for the Bahrain food festival. The stated objectives were: i) To identify the motivational dimensions of the demand for the food festival, (ii) To determine the segments of the demand for the food festival, and (iii) To establish the relationship between the demand segments and socio-demographic aspects. The food festival investigated was the Bahrain Food Festival held in Bahrain, located on the east coast of the Persian Gulf. The sample consisted of 380 valid questionnaires and was taken using social networks from those attending the event. The statistical techniques used were factorial analysis and the K-means grouping method. The results show five motivational dimensions: Local food, Art, Entertainment, Socialization, and Escape and novelty. In addition, two segments were found; the first, Entertainment and novelties, is related to attendees who seek to enjoy the festive atmosphere and discover new restaurants. The second is Multiple motives, formed by attendees with several motivations simultaneously. This segment has the highest income and expenses, making it the most important group for developing plans and strategies. The results will contribute to the academic literature and the organizers of food festivals.