Graph and download economic data for All Employees, Retail Trade (USTRADE) from Jan 1939 to Feb 2026 about establishment survey, retail trade, sales, retail, employment, and USA.

Graph and download economic data for Average Weekly Hours of All Employees, Retail Trade (AWHAERT) from Mar 2006 to Feb 2026 about establishment survey, hours, retail trade, sales, retail, employment, and USA.

In November 2024, preliminary numbers suggested that there were approximately ***** million people employed in the retail industry in the United States, up from ***** million employed in the same period a year earlier.

Graph and download economic data for Average Hourly Earnings of All Employees, Retail Trade (CEU4200000003) from Mar 2006 to Feb 2026 about establishment survey, earnings, hours, retail trade, wages, sales, retail, employment, and USA.

As of the fourth quarter of 2025, there were approximately *** million people employed in the wholesale and retail sector in the UK, compared with ****million in the first quarter of 2000.

Graph and download economic data for All Employees: Retail Trade in San Francisco-Oakland-Fremont, CA (MSA) (SMU06418604200000001SA) from Jan 1990 to Dec 2025 about San Francisco, retail trade, CA, sales, retail, employment, and USA.

The Dataset

The dataset contains data from 33,110 culture survey questionnaires in a large retail store chain. This data can be used to identify the influence of various personal and sociodemographic characteristics of a person on his values at work, job satisfaction, and others.

Each record contains: - answers to 62 questionnaire questions; - answers to 5 questions about employee values; - sociodemographic information (age, gender, marital status, dependents, and financial obligations); - respondent's job position and working period in the company.

Background of the used psychodiagnostic methodology

The study uses the MBTI-like test of the Menteora service as its baseline test.

In addition to the basic 60 questions of the methodology, the respondents were asked two additional: - How much do you like what you are doing at work now? - My work gives me a sense of fulfillment.

Additional questions allow you to create models that can predict the level of engagement and predisposition to work in a retail store chain of a Menteora respondent.

Content

retail_salespeople_statistic.csv

Primary datafile with answers to questionnaire questions.

Fileds: - q1-q62: answers to Menteora questions: - 1 — if the first answer is selected - 2 — for the second answer; - q63-q67: questions about employee values with multiple choice options; - q68-q74: sociodemographic information.

For more information on the content of the questions, see the attached schema.

questionnaire_schema.json

JSON array with position (starts with 1) and text of each question in the questionnaire. Each question has a subarray of answers with position (starts with 1) and answers text.

Graph and download economic data for All Employees: Retail Trade in California (SMU06000004200000001) from Jan 1990 to Dec 2025 about retail trade, CA, sales, retail, employment, and USA.

This statistic shows the projected number of workers in the retail industry in the United States in 2019 and 2026, by size of firm. By 2026, the retail industry in the U.S. is projected to have more than **** million workers at firms employing 10,000 people or more.

This statistic shows the number of employees of the wholesale trade industry in Canada from 2008 to 2024, by age group. There were around 468,800 wholesale trade employees aged between 25 and 54 years in Canada in 2024.

Graph and download economic data for Unemployment Rate - Wholesale and Retail Trade, Private Wage and Salary Workers (LNU04032235) from Jan 2000 to Feb 2026 about wholesale, salaries, workers, retail trade, 16 years +, wages, sales, household survey, retail, unemployment, private, rate, and USA.

This dataset bundle combines employee performance data and retail footfall patterns to help analyze and optimize workforce scheduling. It is ideal for projects involving staff scheduling algorithms, retail demand forecasting, shift optimization, and workforce satisfaction analysis.

The two datasets together allow for linking employee availability and satisfaction with real-world footfall trends — a common problem in retail operations research and HR analytics.

🧑‍💼 Dataset 1 — Employee List (employee_list.csv)

📋 Description

This dataset contains information about employees, their preferred shifts, and how effective they are (measured via satisfaction scores or number of people they can serve). Each row represents an employee–shift combination along with a performance score.

📊 Columns

Employee Name: Unique identifier for each employee (e.g., Employee_01).

Shift Assigned: The shift assigned — can be Morning, Afternoon, or Evening.

Adjusted Score: Satisfaction or performance score for that employee during the given shift (represents number of people satisfied or served).

💡 Potential Uses

Identify which shifts yield the best performance.

Understand employee satisfaction and workload balance.

Input for scheduling or optimization algorithms (e.g., constraint solvers).

Train models to predict employee performance based on shift history.

🏪 Dataset 2 — Retail Footfall Data (Retail_footfall_data.csv)

📋 Description

This dataset captures customer footfall and staffing metrics for a retail store across different shifts and days. It provides real-world-like conditions for optimizing scheduling, estimating labor costs, and balancing staff against demand.

📊 Columns

Date: Date of the observation (DD/MM/YY).

Shift: The time slot of the shift (e.g., 6:00, 12:00, 18:00).

Footfall: Number of customers who entered the store during that shift.

Required_Staff: Estimated number of employees required based on demand.

Available_Employees: Number of employees actually available.

Wage_per_Hour_Rs: Hourly wage for the employees (in Indian Rupees).

Shift_Duration_Hours: Duration of each shift (default 6 hours).

Max_Hours_Per_Week_Per_Employee: Maximum allowed working hours per employee per week (default 48 hours).

Assigned_Staff: Number of employees assigned to that shift.

💡 Potential Uses

Analyze correlation between footfall and staff availability.

Forecast future staffing needs based on customer trends.

Optimize labor distribution to minimize overstaffing or understaffing.

Simulate cost-efficiency and shift adjustments using scheduling models.

🔗 Suggested Combined Use

Both datasets can be used together for:

Workforce Optimization Models – match employee availability and satisfaction to footfall-based staffing requirements.

Predictive Scheduling Systems – forecast employee performance under different demand scenarios.

AI-driven Staffing Tools – build models that auto-schedule employees to maximize satisfaction and customer service.

This statistic depicts the total number of employees in the retail industry in the United States in 2023, by role. In 2023, there were **** million people employed as cashiers in the United States.

Graph and download economic data for All Employees, Nonstore Retailers (DISCONTINUED) (CES4245400001) from Jan 1990 to Dec 2022 about establishment survey, retail trade, sales, retail, employment, and USA.

Australia Employment: Retail Trade data was reported at 1,353.914 Person th in Nov 2025. This records an increase from the previous number of 1,315.720 Person th for Aug 2025. Australia Employment: Retail Trade data is updated quarterly, averaging 1,182.159 Person th from Nov 1984 (Median) to Nov 2025, with 165 observations. The data reached an all-time high of 1,375.433 Person th in Feb 2023 and a record low of 685.385 Person th in Feb 1985. Australia Employment: Retail Trade data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G: Employment: by Industry.

View monthly updates and historical trends for Germany Retail Employment. Source: Federal Statistical Office of Germany. Track economic data with YCharts …

This statistic shows the number of employees of the retail trade industry in Canada from 2008 to 2024. There were approximately 2.2 million retail trade employees in Canada in 2024, a slight decrease compared to the previous year.

Graph and download economic data for Indexes of Aggregate Weekly Payrolls of All Employees, Retail Trade (CES4200000017) from Mar 2006 to Feb 2026 about payrolls, establishment survey, retail trade, sales, retail, employment, indexes, and USA.

📘 Dataset Overview This dataset provides a comprehensive view of employee-level HR data from a retail company, including demographics, compensation, job roles, satisfaction scores, performance metrics, and attrition indicators. It is designed to help explore trends in workforce management, employee engagement, and retention strategies.

This structured data is ideal for those working in people analytics, HR tech, organizational development, and machine learning applications for attrition prediction.

📊 Data Description Each row represents an individual employee, with attributes spanning multiple dimensions:

Column Name Description EmployeeID Unique identifier for each employee Age Age of the employee Gender Gender of the employee Department Department where the employee works JobRole Specific job title within the department Education Level of education (e.g., Bachelor, Master) MonthlyIncome Monthly salary in USD HourlyRate, DailyRate, MonthlyRate Standardized compensation rates Date_of_Joining Date when the employee joined the company OverTime Whether the employee works overtime Attrition Indicates if the employee has left the company YearsAtCompany, YearsInCurrentRole Tenure information YearsSinceLastPromotion, YearsWithCurrManager Career growth and stability metrics EnvironmentSatisfaction, JobSatisfaction, WorkLifeBalance Engagement indicators TrainingTimesLastYear Number of training sessions attended PerformanceRating Manager-assigned performance score Onboarding_Status Indicates if candidate was hired, rejected, or pending

Usage & Potential Applications This dataset can be used in multiple scenarios, including:

🧠 Machine Learning Models:

Attrition prediction (binary classification)

Compensation forecasting

Employee segmentation (clustering)

📊 Data Visualization & BI Dashboards:

Power BI / Tableau dashboards with KPIs like Attrition Rate, Retention Rate, Avg. Tenure

Building HR scorecards by department/job role

📚 Educational Purposes:

Ideal for teaching Power BI, DAX, Pandas, or HR analytics in courses

Step-by-step project learning for Kaggle competitions

🏢 Business Case Simulations:

Workforce planning

Onboarding effectiveness analysis

Promotion pipeline analysis

🧭 Ethical Note This dataset is synthetic or anonymized for public use. It is not linked to any real organization or individuals and should be used solely for educational, research, or development purposes. Users should ensure that models or insights derived from this dataset are not directly applied in real-life HR decisions without proper validation using actual company data.

As of the third quarter of 2025, there were approximately *****million men employed in the wholesale and retail sector in the UK, compared with *****million women.