In December 2021, total retail sales in the United States grew by approximately 16.7 percent when compared to the same period in 2020. Many industries, including gasoline stations, clothing outlets, as well as hobby stores, experienced considerable growth in terms of sales compared to one year ago.

Sugarless gum generated sales amounting to approximately *** billion U.S. dollars in the United States for the 52 weeks that ended on December 26, 2021. Chocolate gift boxes had sales worth *** million U.S. dollars during that period.

This filtered view contains the spirits purchase information of Iowa Class “E” liquor licensees by product and date of purchase for calendar year 2021. The dataset can be used to analyze total spirits sales in Iowa of individual products at the store level.

Global retail sales were projected to amount to around **** trillion U.S. dollars by 2026, up from approximately **** trillion U.S. dollars in 2021. The retail industry encompasses the journey of a good or service. This typically starts with the manufacturing of a product and ends with said product being purchased by a consumer from a retailer. Retail establishments come in many forms such as grocery stores, restaurants, and bookstores. American retailers worldwide As a result of globalization and various trade agreements between markets and countries, many retailers are capable of doing business on a global scale. Many of the world’s leading retailers are American companies. Walmart and Amazon are examples of such American retailers. The success of U.S. retailers can also be seen through their performance in online retail. Retail in the U.S. The domestic retail market in the United States is a lucrative market, in which many companies compete. Walmart, a retail chain offering low prices and a wide selection of products, is the leading retailer in the United States. Amazon, The Kroger Co., Costco, and Target are a selection of other leading U.S. retailers.

Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

Retail Sales in the United States increased 0.60 percent in June of 2025 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.

1.Introduction

Sales data collection is a crucial aspect of any manufacturing industry as it provides valuable insights about the performance of products, customer behaviour, and market trends. By gathering and analysing this data, manufacturers can make informed decisions about product development, pricing, and marketing strategies in Internet of Things (IoT) business environments like the dairy supply chain.

One of the most important benefits of the sales data collection process is that it allows manufacturers to identify their most successful products and target their efforts towards those areas. For example, if a manufacturer could notice that a particular product is selling well in a certain region, this information could be utilised to develop new products, optimise the supply chain or improve existing ones to meet the changing needs of customers.

This dataset includes information about 7 of MEVGAL’s products [1]. According to the above information the data published will help researchers to understand the dynamics of the dairy market and its consumption patterns, which is creating the fertile ground for synergies between academia and industry and eventually help the industry in making informed decisions regarding product development, pricing and market strategies in the IoT playground. The use of this dataset could also aim to understand the impact of various external factors on the dairy market such as the economic, environmental, and technological factors. It could help in understanding the current state of the dairy industry and identifying potential opportunities for growth and development.

1. Citation

Please cite the following papers when using this dataset:

I. Siniosoglou, K. Xouveroudis, V. Argyriou, T. Lagkas, S. K. Goudos, K. E. Psannis and P. Sarigiannidis, "Evaluating the Effect of Volatile Federated Timeseries on Modern DNNs: Attention over Long/Short Memory," in the 12th International Conference on Circuits and Systems Technologies (MOCAST 2023), April 2023, Accepted

1. Dataset Modalities

The dataset includes data regarding the daily sales of a series of dairy product codes offered by MEVGAL. In particular, the dataset includes information gathered by the logistics division and agencies within the industrial infrastructures overseeing the production of each product code. The products included in this dataset represent the daily sales and logistics of a variety of yogurt-based stock. Each of the different files include the logistics for that product on a daily basis for three years, from 2020 to 2022.

3.1 Data Collection

The process of building this dataset involves several steps to ensure that the data is accurate, comprehensive and relevant.

The first step is to determine the specific data that is needed to support the business objectives of the industry, i.e., in this publication’s case the daily sales data.

Once the data requirements have been identified, the next step is to implement an effective sales data collection method. In MEVGAL’s case this is conducted through direct communication and reports generated each day by representatives & selling points.

It is also important for MEVGAL to ensure that the data collection process conducted is in an ethical and compliant manner, adhering to data privacy laws and regulation. The industry also has a data management plan in place to ensure that the data is securely stored and protected from unauthorised access.

The published dataset is consisted of 13 features providing information about the date and the number of products that have been sold. Finally, the dataset was anonymised in consideration to the privacy requirement of the data owner (MEVGAL).

File

Period

Number of Samples (days)

product 1 2020.xlsx

01/01/2020–31/12/2020

363

product 1 2021.xlsx

01/01/2021–31/12/2021

364

product 1 2022.xlsx

01/01/2022–31/12/2022

365

product 2 2020.xlsx

01/01/2020–31/12/2020

363

product 2 2021.xlsx

01/01/2021–31/12/2021

364

product 2 2022.xlsx

01/01/2022–31/12/2022

365

product 3 2020.xlsx

01/01/2020–31/12/2020

363

product 3 2021.xlsx

01/01/2021–31/12/2021

364

product 3 2022.xlsx

01/01/2022–31/12/2022

365

product 4 2020.xlsx

01/01/2020–31/12/2020

363

product 4 2021.xlsx

01/01/2021–31/12/2021

364

product 4 2022.xlsx

01/01/2022–31/12/2022

364

product 5 2020.xlsx

01/01/2020–31/12/2020

363

product 5 2021.xlsx

01/01/2021–31/12/2021

364

product 5 2022.xlsx

01/01/2022–31/12/2022

365

product 6 2020.xlsx

01/01/2020–31/12/2020

362

product 6 2021.xlsx

01/01/2021–31/12/2021

364

product 6 2022.xlsx

01/01/2022–31/12/2022

365

product 7 2020.xlsx

01/01/2020–31/12/2020

362

product 7 2021.xlsx

01/01/2021–31/12/2021

364

product 7 2022.xlsx

01/01/2022–31/12/2022

365

3.2 Dataset Overview

The following table enumerates and explains the features included across all of the included files.

Feature

Description

Unit

Day

day of the month

-

Month

Month

-

Year

Year

-

daily_unit_sales

Daily sales - the amount of products, measured in units, that during that specific day were sold

units

previous_year_daily_unit_sales

Previous Year’s sales - the amount of products, measured in units, that during that specific day were sold the previous year

units

percentage_difference_daily_unit_sales

The percentage difference between the two above values

%

daily_unit_sales_kg

The amount of products, measured in kilograms, that during that specific day were sold

kg

previous_year_daily_unit_sales_kg

Previous Year’s sales - the amount of products, measured in kilograms, that during that specific day were sold, the previous year

kg

percentage_difference_daily_unit_sales_kg

The percentage difference between the two above values

kg

daily_unit_returns_kg

The percentage of the products that were shipped to selling points and were returned

%

previous_year_daily_unit_returns_kg

The percentage of the products that were shipped to selling points and were returned the previous year

%

points_of_distribution

The amount of sales representatives through which the product was sold to the market for this year

previous_year_points_of_distribution

The amount of sales representatives through which the product was sold to the market for the same day for the previous year

Table 1 – Dataset Feature Description

1. Structure and Format

4.1 Dataset Structure

The provided dataset has the following structure:

Where:

Name

Type

Property

Readme.docx

Report

A File that contains the documentation of the Dataset.

product X

Folder

A folder containing the data of a product X.

product X YYYY.xlsx

Data file

An excel file containing the sales data of product X for year YYYY.

Table 2 - Dataset File Description

1. Acknowledgement

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 957406 (TERMINET).

References

[1] MEVGAL is a Greek dairy production company

Sweden Retail Sales Index: 2021=100: Volume: Not in Stores data was reported at 86.000 2021=100 in Aug 2024. This records an increase from the previous number of 80.600 2021=100 for Jul 2024. Sweden Retail Sales Index: 2021=100: Volume: Not in Stores data is updated monthly, averaging 34.200 2021=100 from Jan 1991 (Median) to Aug 2024, with 404 observations. The data reached an all-time high of 128.900 2021=100 in Nov 2021 and a record low of 6.400 2021=100 in Jul 1995. Sweden Retail Sales Index: 2021=100: Volume: Not in Stores data remains active status in CEIC and is reported by Statistics Sweden. The data is categorized under Global Database’s Sweden – Table SE.H001: Retail Sales Index: 2021=100.

Electric Vehicle Sales: Tesla: Tesla Model 3 data was reported at 52,520.000 Unit in Mar 2025. This records a decrease from the previous number of 57,928.000 Unit for Dec 2024. Electric Vehicle Sales: Tesla: Tesla Model 3 data is updated quarterly, averaging 53,251.000 Unit from Mar 2021 (Median) to Mar 2025, with 17 observations. The data reached an all-time high of 58,423.000 Unit in Sep 2024 and a record low of 20,700.000 Unit in Mar 2021. Electric Vehicle Sales: Tesla: Tesla Model 3 data remains active status in CEIC and is reported by Cox Automotive. The data is categorized under Global Database’s United States – Table US.RA007: Electric Vehicle Sales: by Brand and Model.

Key information about Romania Retail Sales Growth

• Romania Retail Sales grew 3.2 % YoY in Jan 2025, compared with a 7.8 % increase in the previous month.
• Romania Retail Sales Growth YoY data is updated monthly, available from Jan 2001 to Jan 2025, with an average growth rate of 6.3 %.
• The data reached an all-time high of 42.0 % in Apr 2021 and a record low of -19.4 % in Apr 2020.
• In the latest reports, Car Sales of Romania recorded 170,718.0 units in Dec 2023, representing a growth of 13.3 %.

CEIC calculates monthly Retail Sales: Excl. Motor Vehicles Growth from monthly Retail Trade Turnover Volume Index. The National Institute of Statistics provides Retail Trade Turnover Volume Index with base 2021=100. Retail Sales: Excl. Motor Vehicles Growth prior to January 2006 is calculated from Retail Trade Turnover Index with base 2005=100.

This table presents information about developments in production and turnover in industry (excl. construction), SIC 2008 sections B - E. The data can be divided by a number of branches according to Statistics Netherlands' Standard Industrial Classification of all Economic Activities 2008 (SIC 2008). Developments are presented as percentage changes compared to a previous period and by means of indices.

Developments in turnover and volume are published in two formats. Firstly, in the form of year-on-year changes relative to the same period in the preceding year. These figures are shown both unadjusted and adjusted for calendar effects. The second format pertains to period-on-period changes, for example quarter-on-quarter. Period-on-period changes are calculated by applying seasonal adjustment.

Data available from: January 2005

Status of the figures: The monthly figures of 2025 are provisional, the other figures are definitive.

The figures of a calendar year will become definite no later than six months after the end of that calendar year. Until then, the figures in this table will be “provisional” and can still be adjusted as a result of delayed response. Once definitive figures have been published, Statistics Netherlands will only revise the results if significant adjustments and/or corrections are necessary.

Changes as of 10 June 2025 The figures for April 2025 have been added. The figures of the 4 most recent present months in the data may have been adjusted. As an exception, the unadjusted figures for SBI21 and SBI24 have been revised for the entire year 2024. The calendar and seasonally adjusted figures for the most recent 16 months may have changed due to the annual update of the seasonal adjustment models.

Changes as of 13 May 2025: In the previous version, a small amount of data was incorrectly displayed. In this version, that has been corrected.

When will new figures be published? As a rule, monthly statistics are published six to eight weeks after the end of the reporting month. Quarterly statistics are published on the last working day of the second month after the quarter. For production figures see link in section 3.

This statistic shows the projected sales value of sustainable products in the United States from 2019 to 2021. The sales of sustainable products in the U.S. is projected to have a value between ***** and ***** billion U.S. dollars in 2021.

Retail Sales Data shared will cover Categories Products, Orders, Suppliers and Employees

Overview: You're a marketing analyst and you've been told by the expected to be. You need to analyze the data set to understand this problem and propose data-driven solutions.

Key information about Lithuania Retail Sales Growth

• Lithuania Retail Sales grew 1.5 % YoY in Jan 2025, compared with a 7.8 % increase in the previous month.
• Lithuania Retail Sales Growth YoY data is updated monthly, available from Jan 1999 to Jan 2025, with an average growth rate of 5.4 %.
• The data reached an all-time high of 34.9 % in Apr 2021 and a record low of -26.2 % in Nov 2009.
• In the latest reports, Car Sales of Lithuania recorded 47,382.0 units in Dec 2019, representing a growth of 30.7 %.

CEIC calculates monthly Retail Sales: Excl. Motor Vehicles Growth from monthly Real Retail Trade Index. Statistics Lithuania provides Real Retail Trade Index with base 2021=100.

In 2021, Allegheny County Economic Development (ACED), in partnership with Urban Redevelopment Authority of Pittsburgh(URA), completed the a Market Value Analysis (MVA) for Allegheny County. This analysis services as both an update to previous MVA’s commissioned separately by ACED and the URA and combines the MVA for the whole of Allegheny County (inclusive of the City of Pittsburgh). The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

This MVA utilized data that helps to define the local real estate market. The data used covers the 2017-2019 period, and data used in the analysis includes:

• Residential Real Estate Sales
• Mortgage Foreclosures
• Residential Vacancy
• Parcel Year Built
• Parcel Condition
• Building Violations
• Owner Occupancy
• Subsidized Housing Units

The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

Please refer to the presentation and executive summary for more information about the data, methodology, and findings.

Sweden Retail Sales Index: 2021=100: Value: excl Fuel data was reported at 95.400 2021=100 in Feb 2025. This records a decrease from the previous number of 100.500 2021=100 for Jan 2025. Sweden Retail Sales Index: 2021=100: Value: excl Fuel data is updated monthly, averaging 63.350 2021=100 from Jan 1991 (Median) to Feb 2025, with 410 observations. The data reached an all-time high of 128.000 2021=100 in Dec 2024 and a record low of 30.800 2021=100 in Feb 1993. Sweden Retail Sales Index: 2021=100: Value: excl Fuel data remains active status in CEIC and is reported by Statistics Sweden. The data is categorized under Global Database’s Sweden – Table SE.H001: Retail Sales Index: 2021=100.

Ireland Retail Sales Value Index: Seasonally Adjusted (sa) data was reported at 125.500 2021=100 in Feb 2025. This records an increase from the previous number of 124.400 2021=100 for Jan 2025. Ireland Retail Sales Value Index: Seasonally Adjusted (sa) data is updated monthly, averaging 120.100 2021=100 from Jan 2021 (Median) to Feb 2025, with 50 observations. The data reached an all-time high of 125.500 2021=100 in Feb 2025 and a record low of 77.600 2021=100 in Jan 2021. Ireland Retail Sales Value Index: Seasonally Adjusted (sa) data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s Ireland – Table IE.H002: Retail Sales Value Index: 2021=100: Seasonally Adjusted.