Gain a competitive edge with our comprehensive Advertising Dataset, designed for marketers, analysts, and businesses to track ad performance, analyze competitor strategies, and optimize campaign effectiveness.

Dataset Features

Sponsored Posts & Ads: Access structured data on paid advertisements, including post content, engagement metrics, and platform details. Competitor Advertising Insights: Extract data on competitor campaigns, influencer partnerships, and promotional strategies. Audience Engagement Metrics: Analyze likes, shares, comments, and impressions to measure ad effectiveness. Multi-Platform Coverage: Track ads across LinkedIn, Instagram, Facebook, TikTok, Twitter (X), Pinterest, and more. Historical & Real-Time Data: Retrieve historical ad performance data or access continuously updated records for real-time insights.

Customizable Subsets for Specific Needs Our Advertising Dataset is fully customizable, allowing you to filter data based on platform, ad type, engagement levels, or specific brands. Whether you need broad coverage for market research or focused data for ad optimization, we tailor the dataset to your needs.

Popular Use Cases

Targeted Advertising & Audience Segmentation: Refine ad targeting by analyzing competitor content, audience demographics, and engagement trends. Campaign Performance Analysis: Measure ad effectiveness by tracking engagement metrics, reach, and conversion rates. Competitive Intelligence: Monitor competitor ad strategies, influencer collaborations, and promotional trends. Market Research & Trend Forecasting: Identify emerging advertising trends, high-performing content types, and consumer preferences. AI & Predictive Analytics: Use structured ad data to train AI models for automated ad optimization, sentiment analysis, and performance forecasting.

Whether you're optimizing ad campaigns, analyzing competitor strategies, or refining audience targeting, our Advertising Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

This dataset provides a comprehensive view of the online advertising performance for "Company X" over a three-month period in 2020. Here's an overview of its components and potential analyses you can perform:

Dataset Components: Day: Date of the advertising campaign. Campaign: Specific group targeting variable set by Company X. User Engagement: Level of user interaction with the ads. Banner: Ad size served by "Advert Firm A". Placement: Publisher space where ads are served (websites/apps). Displays: Number of ads shown by "Advert Firm A". Cost: Price paid to serve the ads to the publisher. Clicks: Number of times users clicked on the ads. Revenue: Amount

This dataset simulates advertising campaign data used for optimizing content distribution strategies. It contains user-level engagement data, providing insights into ad performance across various demographic and behavioral attributes. The dataset is designed for use with evolutionary algorithms (such as Shuffled Frog Leaping Algorithm with Dueling Deep Q-Networks) to optimize ad dissemination strategies for improved ROI and user engagement. The primary target column, ROI_Category, classifies the return on investment (ROI) into three categories: Low, Medium, and High.

Key Features:

user_id: Unique identifier for each user. timestamp: Date and time when the ad interaction occurred. device_type: Type of device used for interaction (Mobile, Desktop, Tablet). location: Geographical location of the user (e.g., USA, UK, Canada). age_group: Age group of the user (e.g., 18-24, 25-34). gender: Gender of the user (Male, Female). ad_id: Unique identifier for the advertisement. content_type: Type of content in the ad (Text, Image, Video). ad_topic: Category or subject of the advertisement (e.g., Fashion, Electronics). ad_target_audience: Targeted audience for the ad (e.g., Tech Enthusiasts, Fitness Lovers). click_through_rate: The rate at which users click the ad (CTR). conversion_rate: The rate at which clicks result in desired actions (e.g., purchase). engagement_level: Type of user interaction with the ad (e.g., Liked, Shared, Commented). view_time: Time spent viewing the ad (in seconds). cost_per_click: The cost paid by the advertiser per click. ROI_Category: Categorized return on investment (ROI), classified as Low, Medium, or High

To demonstrate discovery, measurement, and mitigation of bias in advertising, we provide a dataset that contains synthetic generated data for users who were shown a certain advertisement (ad). Each instance of the dataset is specific to a user and has feature attributes such as gender, age, income, political/religious affiliation, parental status, home ownership, area (rural/urban), and education status. In addition to the features we also provide information on whether users actually clicked on or were predicted to click on the ad. Clicking on the ad is known as conversion, and the three outcome variables included are: (1) The predicted probability of conversion, (2) Predicted conversion (binary 0/1) which is obtained by thresholding the predicted probability, (3) True conversion (binary 0/1) that indicates whether the user actually clicked on the ad.

A comprehensive dataset providing up-to-date insights into the global advertising industry in 2026, including total ad spend, digital advertising dominance, social media growth, mobile and video advertising trends, programmatic adoption, connected TV expansion, and ROI benchmarks across key marketing channels.

Targeted Advertising Statistics: As of reports in recent days, targeted advertisement has become much more popular over the world as these are the form of digital advertisements. This kind of online advertisement forms depends on the internet as well as on Artificial intelligence and ads are focused on customer’s preferences and interests. By the end of 2022, the targeted advertising industry growth has experienced d growth rate of $209.9 billion. These Targeted Advertising Statistics include several insights from different aspects that will provide a better idea of why Targeted Advertisement is the best ad today. Editor’s Choice The spending on targeted advertising in 2022 has resulted in $4.25 billion Companies across the world spent around $521 billion approximately per year on Targeted ads. As of 2022, across the global digital ad market, 28.6% was earned by the targeted ads market of Google. The targeted ads allowed in generating Facebook’s 99% of revenue. Targeted ads revenue generated by Google was $147 billion. Yearly $117 billion in revenue is generated from targeted ads from overall Meta’s. Targeted advertisement attracted 37% of social media users for buying a product. By the end of 2022, the targeted market has experienced a growth of 15% from last year resulting in $602 billion. By the end of 2026, the advertising budget for social media is going to grow by 11.76%.

In 2025, print advertising spending in the United States will amount to an estimated 8.98 billion U.S. dollars, down from 9.61 billion dollars a year earlier. The value was forecast to continue to decline throughout the decade, barely surpassing seven billion dollars by 2029. Find other insights concerning similar markets and segments, such as a comparison of ad spending in the United States and a comparison of average revenue per user (ARPU) in the United States.The Statista Market Insights cover a broad range of additional markets.

The Sales and Advertising dataset typically contains historical data related to sales performance, advertising spend, and marketing efforts across different channels. It includes features such as advertising budget allocation across platforms (TV, radio, online, print), sales revenue, target audience demographics, campaign start and end dates, and geographic regions. This dataset is valuable for analyzing the impact of advertising strategies on sales, conducting A/B testing, optimizing marketing budgets, and forecasting future sales trends. It is commonly used in machine learning and data analysis for tasks like regression modeling, customer segmentation, and ROI measurement.

This dataset compiles the records of food advertising violations issued by the municipal health bureaus and the Food and Drug Administration. The information displayed is limited to the written document. However, this dataset may be subject to subsequent revisions, and does not necessarily indicate that the products in question are illegal. Please review with caution.

The ad spending in the advertising market in Canada was modeled to stand at 23.3 billion U.S. dollars in 2024. Following a continuous upward trend, the ad spending has risen by 9.79 billion U.S. dollars since 2017. Between 2024 and 2030, the ad spending will rise by 4.95 billion U.S. dollars, continuing its consistent upward trajectory.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Advertising.

OMD – part of the Omnicom Group – won the highest-spending advertising pitch in the United States in 2024, a sales presentation for GAP with media spending of 590 million U.S. dollars. Publicis Media – controlled by the Publicis Groupe – ranked second with a 450-million-dollar pitch for Hershey's.

On September 30, 2020, AB 323 (Ch. 341, Stats. 2020) was passed and chaptered into law thereby establishing the requirement for DGS to post on its Internet website purchases related to marketing and outreach advertising materials for every state office, officer, department, division, bureau, board, and commission identified in GC 11000, and including the California State University. These purchases must be further disaggregated to show placement of marketing and outreach advertising materials targeting communications with specific ethnic communities including but not limited to Latino, African American, Asian-Pacific Islander, Indigenous, Middle Eastern and LGTBQIA communities as outlined by Public Contract Code 11800-11804.

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.

This data set is extracted from the records of drug advertising handled by the health bureaus of various counties and cities. The displayed fields are limited to those open to the system. However, this data set may be subject to subsequent revisions and discretion, and does not necessarily mean that the products of the subject of the disposal are illegal. Please use caution when referring to it.

Discover key social media advertising statistics, including ad spend, ROI, platform performance, audience targeting, and trend insights!

The general taxonomy contains a default scope of data related topics, based on the user's browser and mobile app activity through last 30 days. There are classical Demographic, purchase interests, intentions.

How you can use our data?

There are two main areas where you can use our data: • marketers - targeting online campaigns With our high-quality audience data, you can easily reach specific audiences across the world in programmatic campaigns. Show them personalized ads adjusted to their specific profiles. • ad tech companies - enriching 1st party data or using our raw data by your own data science team

The latest Facebook statistics show that the platform is growing – especially when it comes to advertising. These are the latest Facebook advertising statistics you need to know.

People think of paid advertising as the holy grail of digital marketing. The truth is that paid ads can deliver excellent results for your business very quickly. Here are some digital marketing statistics about paid advertising to keep in mind.

Complete dataset containing costs, performance and Search Engine Advertising benchmarks.

This data set contains monthly data (for 36 months) on sales and advertising expenditures for a dietary weight control product.