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.

This dataset contains the full responses from a structured survey conducted in Colombia (2024) aimed at analyzing the relationships between perceived brand ethics, trust, service quality, customer experience, perceived value, brand engagement, and loyalty. The study includes socio-demographic segmentation by educational level and focuses on the consumer perception of Alpina®, a leading brand in the Latin American food industry.

Our People data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

Our comprehensive data enrichment solution includes a variety of data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences.

1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc.
2. Demographics - Gender, Age Group, Marital Status, Language etc.
3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc
4. Persona - Consumer type, Communication preferences, Family type, etc
5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc.
6. Household - Number of Children, Number of Adults, IP Address, etc.
7. Behaviours - Brand Affinity, App Usage, Web Browsing etc.
8. Firmographics - Industry, Company, Occupation, Revenue, etc
9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc.
10. Auto - Car Make, Model, Type, Year, etc.
11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

People Data Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

People Data Use Cases:

360-Degree Customer View: Get a comprehensive image of customers by the means of internal and external data aggregation.

Data Enrichment: Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment

Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity.

Advertising & Marketing: Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

Using Factori People Data you can solve use cases like:

Acquisition Marketing Expand your reach to new users and customers using lookalike modeling with your first party audiences to extend to other potential consumers with similar traits and attributes.

Lookalike Modeling

Build lookalike audience segments using your first party audiences as a seed to extend your reach for running marketing campaigns to acquire new users or customers

And also, CRM Data Enrichment, Consumer Data Enrichment B2B Data Enrichment B2C Data Enrichment Customer Acquisition Audience Segmentation 360-Degree Customer View Consumer Profiling Consumer Behaviour Data

Here's the schema of People Data: person_id first_name last_name age gender linkedin_url twitter_url facebook_url city state address zip zip4 country delivery_point_bar_code carrier_route walk_seuqence_code fips_state_code fips_country_code country_name latitude longtiude address_type metropolitan_statistical_area core_based+statistical_area census_tract census_block_group census_block primary_address pre_address streer post_address address_suffix address_secondline address_abrev census_median_home_value home_market_value property_build+year property_with_ac property_with_pool property_with_water property_with_sewer general_home_value property_fuel_type year month household_id Census_median_household_income household_size marital_status length+of_residence number_of_kids pre_school_kids single_parents working_women_in_house_hold homeowner children adults generations net_worth education_level occupation education_history credit_lines credit_card_user newly_issued_credit_card_user credit_range_new
credit_cards loan_to_value mortgage_loan2_amount mortgage_loan_type
mortgage_loan2_type mortgage_lender_code
mortgage_loan2_render_code
mortgage_lender mortgage_loan2_lender
mortgage_loan2_ratetype mortgage_rate
mortgage_loan2_rate donor investor interest buyer hobby personal_email work_email devices phone employee_title employee_department employee_job_function skills recent_job_change company_id company_name company_description technologies_used office_address office_city office_country office_state office_zip5 office_zip4 office_carrier_route office_latitude office_longitude office_cbsa_code
office_census_block_group
office_census_tract office_county_code
company_phone
company_credit_score
company_csa_code
company_dpbc
company_franchiseflag
company_facebookurl company_linkedinurl company_twitterurl
company_website company_fortune_rank
company_government_type company_headquarters_branch company_home_business
company_industry
company_num_pcs_used
company_num_employees
company_firm_individual company_msa company_msa_name
company_naics_code
company_naics_description
company_naics_code2 company_naics_description2
company_sic_code2
company_sic_code2_description
company_sic...

The present study, focused on pilgrimages as part of religious tourism, aimed to achieve the following objectives: Identify the motivations of the demand for religious tourism focused on pilgrimages; analyze the segmentation of the demand; identify the relationship between demand segments with satisfaction and loyalty; and establish the sociodemographic aspects that characterize demand segments. The study was conducted during the Pilgrimage of the Christ of Miracles in Lima, Peru. The sample was taken on-site from 384 tourists. The statistical techniques used were factor analysis and the k-means clustering method. The results reveal five motivational dimensions: Religious Experience, Belief Experience, Escape, Touristic Experience, and Shopping. Three attendee segments were also identified: Believers, related to belief experience; Religious, related to religious experience; and Passive, tourists with low motivations. The Religious segment had the highest satisfaction and loyalty levels among these groups. Sociodemographic differences were also found in the demand segments. The findings will contribute to management guidelines for destination administrators with religious events and provide insights into academic literature.

Dataset for opinion poll #1. This dataset is in Spanish. It contains the full responses from an opinion poll conducted in Panama (2025) aimed at analyzing the opinions of Panamanians on how Panamanians, from a sense of identity and belonging, recognize the Panama Canal as a Nation's heritage, and a national political factor of power, in the exercise of geostrategic and geopolitical domination of the United States of America in the Latin American and Caribbean region, from a point of transit and logistics of global importance. This opinion is taken from the first statements of the newly elected president of the United States of America, Donald Trump. The dataset includes socio-demographic segmentation by age and province.

The present study, focused on pilgrimages as part of religious tourism, aimed to achieve the following objectives: Identify the motivations of the demand for religious tourism focused on pilgrimages; analyze the segmentation of the demand; identify the relationship between demand segments with satisfaction and loyalty; and establish the sociodemographic aspects that characterize demand segments. The study was conducted during the Pilgrimage of the Christ of Miracles in Lima, Peru. The sample was taken on-site from 384 tourists. The statistical techniques used were factor analysis and the k-means clustering method. The results reveal five motivational dimensions: Religious Experience, Belief Experience, Escape, Touristic Experience, and Shopping. Three attendee segments were also identified: Believers, related to belief experience; Religious, related to religious experience; and Passive, tourists with low motivations. The Religious segment had the highest satisfaction and loyalty levels among these groups. Sociodemographic differences were also found in the demand segments. The findings will contribute to management guidelines for destination administrators with religious events and provide insights into academic literature.

This article examines the geographic variability of labour markets in the Chilean regions of Antofagasta and La Araucanía, emphasizing their structural similarities and differences. An inter- and intraregional perspective is applied to identify common and specific elements in both territories, drawing on multivariate sociodemographic, contractual, and occupational data. Through factorization and cluster analysis, typological systems of labour segmentation are constructed for each region, located at opposite ends of the country. The results reveal the heterogeneity of regional labour matrices, encompassing both regular and protected employment as well as unregulated, temporary, informal, and precarious arrangements. The study also considers the role of urban and rural contexts in shaping productive activities and labour conditions. While extractive industries represent a shared feature of Chile’s productive matrix, the findings show unequal segmentation systems across regions. These differences highlight persistent gender inequalities in access to decent and protected work, along with differentiated patterns of labour insertion for Indigenous peoples and migrants across urban and rural areas. The analysis contributes to understanding regional labour dynamics and underscores the need for territorially differentiated policies that acknowledge the structural diversity of employment conditions in northern and southern Chile.

The purpose of this study was to assess the likelihood of consumer adoption of plant-based and cultivated meat in South Africa as a pathway to a healthy, sustainable, and equitable food supply. We recruited a large sample of South Africans representative across age (18–61), gender, race, and income to participate in an online survey. Participants responded to a range of measures including adoption indicators, estimated yearly intake, motivators for purchasing, desired product characteristics, preferred species, and sociodemographics. We found a high degree of openness to both products. For plant-based meat, 67% were highly likely to try and 59% were highly likely to purchase. For cultivated meat, 60% were highly likely to try and 53% were highly likely to purchase. The highest acceptance was amongst the younger generations: 60% of born-frees, 62% of millennials, and 53% of Gen X were highly likely to purchase plant-based meat and 55% of born-frees, 55% of millennials, and 46% of Gen X were highly likely to purchase cultivated meat. For the general population, we observed that future meat intake was estimated to be split equally among the three meat categories (conventional, cultivated, and plant-based). We found early adopters (those highly likely to purchase) to be quite similar in attitudinal and sociodemographic characteristics in comparison to the general population. The study findings suggest that both plant-based and cultivated meat could be viable market-based options for improving the food system in South Africa, as consumers across all segments of society, and especially amongst the younger population, indicated broad acceptance.