This dataset explores the relationship between advertising expenditures across various channels (TV, radio, and newspaper) and sales performance. It provides insights into how different types of advertising spending impact product sales, allowing for data-driven analysis of marketing effectiveness. This dataset is commonly used for linear regression analysis to determine the influence of each advertising channel on sales outcomes.

Dataset Overview:

TV Advertising Spend: Amount spent on TV advertisements for a given period. Radio Advertising Spend: Amount spent on radio advertisements. Newspaper Advertising Spend: Amount spent on newspaper advertisements. Sales: Total sales generated within the same period, serving as the target variable. Columns:

TV: Advertising budget allocated to TV in thousands of dollars. Radio: Advertising budget allocated to radio in thousands of dollars. Newspaper: Advertising budget allocated to newspapers in thousands of dollars. Sales: Product sales in thousands of units, which is the outcome variable to be predicted. Possible Use Cases:

Marketing Spend Analysis: Determine which advertising channel has the greatest impact on sales. Sales Prediction: Use linear regression to predict sales based on advertising spend across different channels. Channel Effectiveness: Compare the effectiveness of each advertising channel and optimize future marketing budgets. Business Strategy: Identify trends in sales based on historical advertising spending to inform business decisions. This dataset is ideal for students, data analysts, and marketing professionals interested in understanding the impact of advertising on sales performance. It offers a simple structure suitable for exploratory data analysis (EDA), regression modeling, and predictive analysis in marketing.

Per Local Law 83 of 2021, the Mayor's Office of Ethnic and Community Media is required to report annually on each agency's full advertising spend across all media categories, including ethnic and community (ECM), mainstream, out-of-home, social media, etc. This dataset reflects the raw data that MOECM received from City Agencies on their annual advertising spend. For more information, please visit the MOECM website.

Sales Prediction Dataset The dataset provided contains information about the advertising expenditures of a company on various platforms (TV, Radio, newspapers) and the corresponding sales of a product. Here's an explanation of the dataset:

1. TV: This column represents the amount of money spent on advertising the product on television. TV advertising is a traditional and widely used medium for reaching a broad audience.

2. Radio: This column indicates the advertising expenditure on radio. Radio advertising is known for its ability to target specific demographics and local audiences.

3. Newspaper: This column shows the advertising cost spent on newspaper advertising. Newspaper advertising is often used for targeting specific geographic regions or demographics.

4. Sales: This column represents the number of units sold corresponding to the advertising expenditures on TV, Radio, and newspapers.

Questions: 1. What is the average amount spent on TV advertising in the dataset? 2. What is the correlation between radio advertising expenditure and product sales? 3. Which advertising medium has the highest impact on sales based on the dataset? 4. Plot a linear regression line that includes all variables (TV, Radio, Newspaper) to predict Sales, and visualize the model's predictions against the actual sales values. 5. How would sales be predicted for a new set of advertising expenditures: $200 on TV, $40 on Radio, and $50 on Newspaper? 6. How does the performance of the linear regression model change when the dataset is normalized? 7. What is the impact on the sales prediction when only radio and newspaper advertising expenditures are used as predictors?

NOTE: For annually updated, granular ad spend data, please visit Local Law 83 - City Agency Advertising Spend dataset. Fiscal Year 2022 spans over two administrations. The first half of the fiscal year (FY22, Q1 and Q2) was per Executive Order 47. The second half of the fiscal year (FY22, Q3 and Q4) was per Local Law 83. To learn more about the differentiation and review the FY2022 annual report click here To see the agency spend for FY22 broken down by administration click here

This dataset contains information on how much money is spent by verified advertisers on political advertising across Google Ad Services. In addition, insights on demographic targeting used in political ad campaigns by these advertisers are also provided. Finally, links to the actual political ad in the Google Transparency Report (https://adstransparency.google.com) are provided. Data for an election expires 7 years after the election. After this point, the data are removed from the dataset and are no longer available.

Update frequency: Daily

Dataset source: Transparency Report: Political Advertising on Google

Terms of use:

See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/transparency-report/google-political-ads

For more information see: The Political Advertising on Google Transparency Report at https://adstransparency.google.com

The supporting Frequently Asked Questions at https://support.google.com/transparencyreport/answer/9575640?hl=en&ref_topic=7295796

The operating expenses by North American Industry Classification System (NAICS) which include all members under industry expenditures, for advertising and related services, annual (percent), for five years of data.

This dataset provides information on advertising expenditures reported by Government of Canada (GC) institutions, from fiscal year 2015/2016 and is updated annually following the publication of the Annual Report on Government of Canada Advertising Activities. The information is broken down by fiscal year, GC institution, expenditures for activities involving the Agency of Record, and expenditures for activities involving media placement made directly with media suppliers by GC institutions. For more information on the content of this dataset, consult the supporting documentation and data dictionary. For more information on GC advertising activities and expenditures, consult the Annual Reports on Government of Canada Advertising Activities: https://www.canada.ca/en/public-services-procurement/services/communication/government-advertising/annual-reports.html#reports

Total advertising spend for Queensland Government departments

This dataset contains information on how much money is spent by verified advertisers on political advertising across Google Ad Services. In addition, insights on demographic targeting used in political ad campaigns by these advertisers are also provided. Finally, links to the actual political ad in the Google Transparency Report are provided. Data for an election expires 7 years after the election. After this point, the data are removed from the dataset and are no longer available. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

The data on gross agency advertising spending across Canada is aggregated by Guideline powered by Standard Media Index in conjunction with agency partners. This data allows for a real-world view into agency advertising spend by product category, ad revenue to media publishers and digital platforms. The data available accounts for over 94% of national agency spend within the media ecosystem. Contained within this dataset is the gross agency advertising spending by media type and market. This represents only a portion of the total advertising market within Canada from calendar years 2018-2023.

The summary statistics by North American Industry Classification System (NAICS) which include: operating revenue (dollars x 1,000,000), operating expenses (dollars x 1,000,000), salaries wages and benefits (dollars x 1,000,000), and operating profit margin (by percent), of all NAICS under advertising, public relations, and related services (NAICS 5418), annual, for five years of data.

Report covers advertising during period: 1/7/2023 - 30/06/2024 Final expenditure figures may be subject to adjustment. Media expenditure information may change following reconciliation of advertising placements at the completion of advertising

This dataset lists Government of Canada institutions by total amount spent by each year on advertising activities with and without the Agency of Record.

For more information please see visit the Government of Canada Advertising site.

Data set extracts from the Department of Health Annual Report for the 2020-21 financial year.\r Details of government advertising expenditure for 2020–21 (campaigns with a media spend of $100,000 or greater) ($ thousand)

This dataset provides information on the advertising practices of a large sample (844) of UK firms. Questionnaire data are recorded in the dataset under 91 variables (quantitative response categories) and all qualitative responses have been given numerical values according to the coding frames included in the user guide. The questionnaires used for the survey were sent to the Advertising Managers of 5234 firms. Each questionnaire was divided into three sections plus a supplementary question. The first question (q.1) asks simply whether the firm advertises or not. Responses to the rest of the first section (q.2 to q.5) deal with non-advertisers whose managers were asked about the reasons for not advertising and about any future plans to advertise. The second section is for advertisers (entitled 'About Your Advertising') and comprises the bulk of the questionnaire (q.6 to q.12). Managers who stated in question 1 that their firm does advertise were asked in this section about the level, motivation and content of their firm's advertising. In the light of the rapid growth in importance of the Internet, several questions ask specifically about the current and future levels of internet advertising. The final question in this section asks for the manager's conjectured advertising response to a series of hypothetical questions concerning trading conditions and rival companies. All respondents were asked to complete section three (q.13 to q.17) entitled 'About Your Company'. Here managers were asked to categorise their main product line or service within a particular sector of the economy and to list the geographical market at which their main product line is aimed. They are also asked to rank the most important modes of competition for their main product line and to identify the number of competitors for this product. Following this section managers are asked (q.18) to provide data on total advertising expenditure for up to ten financial years.

Information released in the Department of Education and Training's Annual Report 2019-20 on government advertising expenditure: Campaigns with a media spend of $100,000 or greater.

Analyzing Customer Spending Habits to Improve Sales Performance

A Cross-Country Study

By Vineet Bahl [source]

About this dataset

This Sales Data dataset offers a unique insight into the spending habits of customers from various countries across the globe. With detailed information on customer age, gender, product category, quantity, unit cost and price, as well as revenue generated through sales of products listed in this dataset, you can explore and discover patterns in consumer behavior. Analyze shifts in consumer trends with qualitative data like customer age and gender to know what drives customers’ decisions when shopping online or offline. Compare different markets to analyze pricing strategies for new product launches or promotional campaigns. Also with this dataset you can gain valuable insights about the changes in consumer demand for specific products over time – find out which Products had better margin or however see how different promotions impacted overall sales performance from different categories and sub-categories! Analyzing consumer behavior is key to success when it comes to commerce business models so this Sales Data offers powerful ways into understanding your customer base better!

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How to use the dataset

This dataset presents a great opportunity to actively analyze customer spending habits on products and services to improve sales performance. The data contains information about the date of purchase, year, month, customer age, gender, country, state and product category. Further analysis can reveal insights into different customer segments based on their demographic characteristics such as age and gender as well as location (country & state).

The dataset also includes 3 additional columns at the end: quantity purchased in each transaction, unit cost and unit price for each product or service purchased which can be used to determine if customers are purchasing items in bulk or buying more expensive items than usual. Likewise any discrepancies between the unit cost & price can help establish whether discounts were applied during those transactions which could potentially point towards loyalty or reward programs being put in place for returning customers. Lastly the final column shows total revenue generated from those purchases which we can use to identify any patterns whereby certain groups of customers show higher purchasing power than others based on their spends (unit cost & quantity combination) over various periods/months/years of sales interactions with them.

In summary this dataset allows us to explore numerous dimensions related to ascertaining superior sales performance by studying how its various attributes play out together when it comes down to driving profitability through improved customer acquisition strategies as well increasing purchase rates from existing ones minus any discounts available in-between!

Research Ideas

• Analyzing customer demographics by countries and states to better target future marketing campaigns.

• Tracking changes in customers’ spending habits over time for different product categories.

• Identifying which product categories have the highest average revenue per sale to help prioritize resources for those products or services

Acknowledgements

If you use this dataset in your research, please credit the original authors.

Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: SalesForCourse_quizz_table.csv | Column name | Description | |:---------------------|:--------------------------------------------------| | Date | Date of the sale. (Date) | | Year | Year of the sale. (Integer) | | Month | Month of the sale. (Integer) | | Customer Age | Age of the c...

Out of the 30 European countries presented in the data set, *******was the fastest growing digital advertising market, reporting an annual growth rate of **** percent in 2024. ****** and ********followed with **** percent and **** percent, respectively. On average, the expenditure in the 30 countries grew by ** percent.

Note: Figures for previous years in relation to advertising expenditure have been updated from previous Annual Reports, following a review of coding.

Information released in the Department of Education and Training's Annual Report 2018-19 on 'Government Advertising Expenditure: Campaigns with a media spend of $100,000 or greater 2018-19' Information released in the Department of Education and Training's Annual Report 2018-19 on 'Government Advertising Expenditure: Campaigns with a media spend of $100,000 or greater 2018-19'