In 2020, there were 41,977 firms in the United States with sales amounting to less than 5,000 U.S. dollars. Comparatively, there were more than 500,000 firms in the country with sales between 50,000 and 99,999 U.S. dollars.

Small business transactions and revenue data aggregated from several credit card processors, collected by Womply and compiled by Opportunity Insights. Transactions and revenue are reported based on the ZIP code where the business is located. Data provided for CT (FIPS code 9), MA (25), NJ (34), NY (36), and RI (44). Data notes from Opportunity Insights: Seasonally adjusted change since January 2020. Data is indexed in 2019 and 2020 as the change relative to the January index period. We then seasonally adjust by dividing year-over-year, which represents the difference between the change since January observed in 2020 compared to the change since January observed since 2019. We account for differences in the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align the holidays before performing the year-over-year division. Small businesses are defined as those with annual revenue below the Small Business Administration’s thresholds. Thresholds vary by 6 digit NAICS code ranging from a maximum number of employees between 100 to 1500 to be considered a small business depending on the industry. County-level and metro-level data and breakdowns by High/Middle/Low income ZIP codes have been temporarily removed since the August 21st 2020 update due to revisions in the structure of the raw data we receive. We hope to add them back to the OI Economic Tracker soon. More detailed documentation on Opportunity Insights data can be found here: https://github.com/OpportunityInsights/EconomicTracker/blob/main/docs/oi_tracker_data_documentation.pdf

This table includes current ratio, debt to equity ratio, interest coverage ratio, debt ratio, revenue to equity ratio, revenue to closing inventory ratio, current debt to equity, net profit to equity, net fixed assets to equity, gross margin, return on total assets, collection period for accounts receivable. Incorporated businesses only. Values are averages in current dollars unless otherwise stated.

This table includes total assets, total current assets, accounts receivable, closing inventory, other current assets, net tangible and intangible assets, long term assets, total liabilities, total current liabilities, current bank loans, other current liabilities, long term liabilities and total equity. Incorporated businesses only. Values are averages in current dollars unless otherwise stated.

In the wake of COVID-19 and associated lockdowns, small businesses in every state saw a negative change in their revenues when compared to revenues before the pandemic began. Businesses in states like New York, New Jersey, and Michigan saw some of the ******* declines in revenues. Small businesses in more rural states such as South Dakota, Montana and Nebraska also saw their revenues ******, but **** dramatically then in aforementioned states.

SB: AZ: OP: Total Revenue: Do Not Know data was reported at 6.700 % in 11 Apr 2022. This records an increase from the previous number of 6.300 % for 04 Apr 2022. SB: AZ: OP: Total Revenue: Do Not Know data is updated weekly, averaging 7.600 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 10.900 % in 21 Mar 2022 and a record low of 4.600 % in 15 Nov 2021. SB: AZ: OP: Total Revenue: Do Not Know data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S: Small Business Pulse Survey: by State: West Region: Weekly, Beg Monday (Discontinued).

Introduction

Small Business Statistics: To balance out every country's economy, small businesses are termed the backbone. Small businesses are types of corporations, partnerships, or sole proprietorships that are independently owned companies with fewer employees and lower revenue than large companies. Many small businesses are now utilising the internet and various digital tools to connect with customers, and many of them generate income by selling online.

This article includes several statistical analyses from different sources that will guide you in understanding the importance of small businesses' effectiveness in recent years.

The SME data warehouse is based on existing administrative data sources from Statistics Canada and Canada Revenue Agency. Data covers tax year 2001 to tax year 2006. The SME Data Warehouse contains a complete, up to date and unduplicated list of all businesses in Canada based on Statistics Canada's Business Register for tax years 2001-2006. This product currently produces data for Small and Medium Sized Enterprises (SMEs). SMEs are defined as enterprises with less than 250 employees and less than $50 million in total revenue.

This survey shows an outlook of small business owners on their company's revenue development over the next 12 months in the United States from 2016 to 2020, by quarter. In the fourth quarter of 2020, about ** percent of small business owners stated their revenue would increase a little/a lot until the fourth quarter of 2021.

Nonemployer Statistics is an annual series that provides statistics on U.S. businesses with no paid employees or payroll, are subject to federal income taxes, and have receipts of $1,000 or more ($1 or more for the Construction sector). This program is authorized by the United States Code, Titles 13 and 26. Also, the collection provides data for approximately 450 North American Industry Classification System (NAICS) industries at the national, state, county, metropolitan statistical area, and combined statistical area geography levels. The majority of NAICS industries are included with some exceptions as follows: crop and animal production; investment funds, trusts, and other financial vehicles; management of companies and enterprises; and public administration. Data are also presented by Legal Form of Organization (LFO) (U.S. and state only) as filed with the Internal Revenue Service (IRS). Most nonemployers are self-employed individuals operating unincorporated businesses (known as sole proprietorships), which may or may not be the owner's principal source of income. Nonemployers Statistics features nonemployers in several arts-related industries and occupations, including the following: Arts, entertainment, and recreation (NAICS Code 71) Performing arts companies Spectator sports Promoters of performing arts, sports, and similar events Independent artists, writers, and performers Museums, historical sites, and similar institutions Amusement parks and arcades Professional, scientific, and technical services (NAICS Code 54) Architectural services Landscape architectural services Photographic services Retail trade (NAICS Code 44-45) Sporting goods, hobby, and musical instrument stores Sewing, needlework, and piece goods stores Book stores Art dealers Nonemployer Statistics data originate from statistical information obtained through business income tax records that the Internal Revenue Service (IRS) provides to the Census Bureau. The data are processed through various automated and analytical review to eliminate employers from the tabulation, correct and complete data items, remove anomalies, and validate geography coding and industry classification. Prior to publication, the noise infusion method is applied to protect individual businesses from disclosure. Noise infusion was first applied to Nonemployer Statistics in 2005. Prior to 2005, data were suppressed using the complementary cell suppression method. For more information on the coverage and methods used in Nonemployer Statistics, refer to NES Methodology. The majority of all business establishments in the United States are nonemployers, yet these firms average less than 4 percent of all sales and receipts nationally. Due to their small economic impact, these firms are excluded from most other Census Bureau business statistics (the primary exception being the Survey of Business Owners). The Nonemployers Statistics series is the primary resource available to study the scope and activities of nonemployers at a detailed geographic level. For complementary statistics on the firms that do have paid employees, refer to the County Business Patterns. Additional sources of data on small businesses include the Economic Census, and the Statistics of U.S. Businesses. The annual Nonemployer Statistics data are available approximately 18 months after each reference year. Data for years since 2002 are published via comma-delimited format (csv) for spreadsheet or database use, and in the American FactFinder (AFF). For help accessing the data, please refer to the Data User Guide.

This table includes percent of profitable businesses; total revenue, total expenses, and net profit (profitable businesses); total revenue, total expenses, and net loss (non-profitable businesses). All businesses only. Values are averages in current dollars unless otherwise stated.

This dataset represents the percent change in net revenue of open small businesses in North Carolina counties calculated as a seven-day moving average, which is seasonally adjusted and indexed to January 4-31 2020. The data obtained from the Opportunity Insights data repository in Github includes the daily percentage change in net revenue of open small businesses compared to January 2020 levels. The data is then aggregated as a rolling 7-day average. Twenty-two of North Carolina’s 100 counties are represented in this dataset, none of which are non-CBSA (outside of both metropolitan and micropolitan areas). Additionally, only one county is identified as having high pre-existing unemployment, and two as having lower median income. As a result, the dataset disproportionately represents relatively prosperous metropolitan centers and does not represent other regions of the state.

This table includes total expenses, cost of sales (direct expenses), wages and benefits, purchases, materials and sub-contracts, opening inventory, closing inventory, operating expenses (indirect expenses), labour and commissions, amortization and depletion, repairs and maintenance, utilities and telephone and telecommunication, rent, interest and bank charges, advertising and promotion, delivery and shipping and warehouse, insurance, other indirect expenses, net profit or loss. All incorporation statuses. Values are averages in current dollars unless otherwise stated.

SB: AZ: OP: Total Revenue: 125,001-200,000 data was reported at 13.300 % in 11 Apr 2022. This records an increase from the previous number of 9.500 % for 04 Apr 2022. SB: AZ: OP: Total Revenue: 125,001-200,000 data is updated weekly, averaging 15.000 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 15.000 % in 10 Jan 2022 and a record low of 8.200 % in 21 Mar 2022. SB: AZ: OP: Total Revenue: 125,001-200,000 data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S: Small Business Pulse Survey: by State: West Region: Weekly, Beg Monday (Discontinued).

📊 Coffee Shop Financial Dataset (Synthetic, 2022–2023)

📝 Overview

This dataset simulates the financial records of a small-town coffee shop over a two-year period (Jan 2022 – Dec 2023).
It was designed for data science, bookkeeping, and analytics projects — including financial dashboards, revenue forecasting, and expense tracking.

The dataset contains 5 CSV files representing different business accounts:
1. checking_account_main.csv - Daily sales deposits (hot drinks, cold drinks, pastries, sandwiches) + operating expenses
2. checking_account_secondary.csv - Monthly transfers between accounts + payroll funding
3. credit_card_account.csv - Weekly credit card expenses (supplies, utilities, vendor charges) and payments
4. gusto_payroll.csv - Payroll data for 3 employees + 1 contractor
5. gusto_payroll_bc.csv - Payroll data for 3 full-time employees + 1 contractor + 1 seasonal employee, with actual tax breakdown for the province of British Columbia, Canada

📂 File Details

checking_account_main.csv

• date
• description
• category (Sales, Utilities, Rent, Supplies, etc.)
• amount (positive = inflow, negative = outflow)
• balance

checking_account_secondary.csv

• date
• description
• amount
• balance

credit_card_account.csv

• date
• vendor
• category (Supplies, Marketing, Utilities, etc.)
• amount (negative = charge, positive = payment)
• balance

gusto_payroll.csv

• date
• employee_id
• employee_name (Owner, Barista 1, Barista 2, Contractor)
• role (Owner, Barista, Manager, Contractor)
• gross_pay

gusto_payroll_bc.csv

This file simulates bi-weekly payroll data for a small coffee shop in British Columbia, Canada, covering January 2022 – December 2023.
It reflects realistic Canadian payroll structure with federal and provincial tax breakdowns, CPP, EI, and additional factors.

Columns: - date → Pay date (bi-weekly schedule)
- employee_id → Unique identifier for each employee
- employee_name → Owner, Barista 1, Barista 2, Manager, Contractor, plus a seasonal Barista (June–Aug 2022)
- role → Role within the coffee shop (Owner, Barista, Manager, Contractor)
- gross_pay → Total earnings before deductions (wages + tips + reimbursements)
- federal_tax → Federal income tax withheld
- provincial_tax → British Columbia income tax withheld
- cpp_employee → Employee CPP contribution
- ei_employee → Employee EI contribution
- other_deductions → Placeholder for possible deductions (e.g., garnishments, union dues)
- net_pay → Take-home pay after deductions
- tips → Declared tips (taxable, included in gross pay)
- travel_reimbursement → Non-taxable reimbursement for travel expenses (if applicable)
- cpp_employer → Employer portion of CPP contributions
- ei_employer → Employer portion of EI contributions

Notes: - Payroll data is synthetic but modeled on Canadian payroll rules (2022–2023 rates).
- A seasonal barista employee is included (employed June 1 – Aug 31, 2022).
- Travel reimbursements are non-taxable and recorded separately.
- This file allows users to practice payroll accounting, deductions analysis, and tax reconciliation.

📈 Business Context

• The coffee shop experiences higher sales September–February (holiday season & winter drinks).
• Sales dip March–June due to seasonality in a small town.
• Pastries are sourced from a local bakery, while sandwiches are made in-house.
• Payroll includes 3 employees (baristas, manager) and 1 independent contractor.

🎯 Possible Use Cases

• Build a financial health dashboard
• Forecast revenue and expenses
• Create a profit & loss statement
• Test SQL queries for accounting workflows
• Explore data visualization with Python, R, or BI tools
• Educational projects for small business analytics

📜 License

This dataset is released under the MIT License, free to use for research, learning, or commercial purposes.

⭐ If you use this dataset in your project or notebook, please credit and share your work, it helps the community!

📷 Photo Credits: freepik

This table includes total number of businesses and total revenue (all incorporated statuses); sales of goods and services, and other revenues (incorporated businesses only). Values are averages in current dollars unless otherwise stated.

In August 2024, the U.S. Small Business Optimism Index amounted to 91.2. This is a slight decrease from a value of 93.7 in the previous month. The index consists of 10 indicators derived from questions addressing small business owners: Plans to create employment; plans to make capital outlays; plans to increase inventories; expect economy to improve; expect real sales higher; current inventory; current job openings; expected credit conditions; now a good time to expand; earnings trends.

In 2024, the average profit made by SMEs in the UK amounted to approximately 11,000 British pounds, with SMEs that employed between 50 and 249 people making a median profit of around 243,000 pounds.

Etsy is an e-commerce platform focused on small businesses and artisans which sell handmade or vintage items. It started life in Brooklyn, New York and quickly expanded throughout the US and into...

SB: AK: OP: Total Revenue: 50,001-125,000 data was reported at 13.700 % in 11 Apr 2022. This records a decrease from the previous number of 18.600 % for 28 Mar 2022. SB: AK: OP: Total Revenue: 50,001-125,000 data is updated weekly, averaging 23.700 % from Nov 2020 (Median) to 11 Apr 2022, with 44 observations. The data reached an all-time high of 30.300 % in 20 Sep 2021 and a record low of 11.800 % in 04 Jan 2021. SB: AK: OP: Total Revenue: 50,001-125,000 data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S: Small Business Pulse Survey: by State: West Region: Weekly, Beg Monday (Discontinued).