In 2022, X (formerly Twitter) generated **** billion U.S. dollars in advertising revenue. This figure is expected to drop to *** billion U.S. dollars by 2027. The social platform is responsible for roughly one percent of the global ad revenue. Social network platform in transition Established in 2006, California-based platform X (formerly known as Twitter) ranked among the most popular social networks worldwide by number of monthly users as of late 2023. The company has undergone a profound transformation after Elon Musk's acquisition in October 2022. After the billionaire bought the platform, advertisers and marketers have closely observed every change regarding its features and policies. Due to many contradictory developments at Twitter, industry professionals have become increasingly more cautious with their investments. A prominent example was IPG - one of the world's top five advertisers - advising its customers to temporarily abstain from putting money into the platform. Another big advertiser who has also ceased ad investment in Walmart. Social media powerhouse: Facebook In the meantime, nearly half of the responding marketing professionals named Facebook the most important social media platform for their business. The social network giant's revenue amounted to *** billion dollars in 2022. Although the figure was roughly ** percent of Google's ad revenue, Meta stood further ahead of X in terms of money earned through selling ad spaces.

Twitter's ad business shrank both in 2023 and 2024, with global ad revenues falling to two billion dollars, according to the source's estimates. After the acquisition of Twitter by Elon Musk on October 27, 2022, the platform saw an exodus of users. December 2022 projections saw more than 30 million users leaving the platform by the end of 2024.

Twitter's global advertising revenue was forecast to decrease by nearly ** percent in 2023. After the acquisition of Twitter by Elon Musk on ****************, and Musk's announcement that the platform should become an "unbiased middle ground" for discussion, the platform saw a sharp increase in hate speech and racist content. Some *** thousand users deactivated their accounts only in the first week after Musk's acquisition. This led advertisers to turn away from the platform, fearing for their brands' safety and losing audiences. In 2022, the platform's ad revenue declined by over seven percent after growing by roughly ** percent one year before.

In 2021, Twitter generated more than 4.5 billion U.S. dollars in advertising service revenues, up from 3.2 billion U.S. dollars in the previous year. Additionally, the micro-blogging platform produced around 571 million U.S. dollars in data licensing revenue, up from 508 million U.S. dollars in 2020.

Advertising makes up 89% of its total revenue and data licensing makes up about 11%.

In 2021, Twitter accounted for *** percent of the global digital advertising revenue. After its acquisition by Elon Musk, the share was expected to fall to *** percent in 2022 and remain stable in 2023. In 2024, the value was projected to fall further to *** percent.

Since October 2022, when Twitter was purchased by Elon Musk, the platform has experienced a steep decline in advertising revenue. In November 2022, the revenue contracted by 57 percent compared to the value reported a month earlier. The growth rate continued to fluctuate between 57 percent and 72 percent until August 2023. On a global scale, X (formerly Twitter)'s ad revenue is expected to drop by rough 1.5 billion U.S. dollars in 2023.

Over the five years through 2025-26, industry revenue is forecast to expand at a compound annual rate of 20.3% to reach £12.5 billion. Social media platforms are integral to people's lives, offering ways to communicate, create and view content and share information. According to Ofcom, approximately 89% of UK internet users in 2023 used social media apps or sites. Teenagers and young adults are the biggest users. Advertising is the primary revenue source for social media platforms, although subscription-based services are gaining momentum as platforms seek to diversify their incomes. TikTok is the success story of the past five years, becoming the most downloaded app between 2020 and 2022, according to Apptopia. The short-form video platform has over 30 million monthly users in the UK in 2025. After Musk's takeover, X, formerly known as Twitter, adjusted its content moderation and allowed previously banned accounts to return. As a result, over 600 advertisers pulled their ads from the site because of fears their brand may be associated with malcontent. In response to falling ad revenue, X has introduced a subscription-based service which enables users to verify themselves and boosts the number of people who view their tweets. Meta-owned Facebook and Instagram have responded by introducing a similar service. In 2025, more social media platforms are using AI to boost user engagement. This improves click-through rates and drives higher advertising revenue. Industry revenue is expected to grow by 6.3% in 2025-26. Over the five years through 2030-31, social media platforms' revenue is projected to climb at an estimated 9.2% to reach £19.4 billion. Regulations relating to how data is collected, stored, and shared will force advertisers and platforms to rethink how they can target their desired demographics. The tightening of regulations will raise industry compliance costs, weighing on profit margin. Older age groups present a new revenue opportunity for social media platforms if they can bridge the gap between passive TV consumption and interactive digital engagement. Augmented Reality (AR) technology will move beyond filters to become standard for immersive product trials, interactive ads, and virtual meetups

Over the forecast period until 2030, the ad spending is forecast to exhibit fluctuations among the nine segments. The ad spending decreases only in the segment Print Advertising towards the end of the forecast period, while the remaining segments follow a positive trend. The absolute difference between 2020 and 2030 is ***** billion U.S. dollars. Find further statistics on other topics such as a comparison of the reach in China and a comparison of the reach in Brazil. The Statista Market Insights cover a broad range of additional markets.

According to Cognitive Market Research, the global Online Advertising market size was USD 236.90 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 15.7% from 2024 to 2031. Market Dynamics of Online Advertising Market

Key Drivers for Online Advertising Market

Increasing internet and smartphone penetration is driving growth in the online advertising market

One of the most significant drivers of growth in the online advertising market is increasing internet penetration and the rising usage of mobile phones, due to growing digital dependency. With over 7 billion people worldwide using mobile phones, smartphones have become an essential part of daily life. This surge in mobile connectivity has transformed consumer behavior with individuals increasingly relying on smartphones for daily activities like shopping, entertainment and financial transactions. The convenience and portability of mobile devices have them a preferred medium for tapping into digital services which has led businesses to adopt mobile-first strategies to engage with consumers. This shift has led to an increase in mobile ad spending. Advertisers are no focusing on campaigns designed for smaller screens and shorter attention spans to reach a wider audience.

Advertisers are responding to this trend with mobile-first strategies, using vertical format videos, personalized in-app ads and location-based targeting to maximize engagement. The combination of high-screen time, constant connectivity, and real time data access makes mobile advertising one of the most effective tools in the global online advertising market.

Social Media Influence is fueling growth for online advertising

Social media platforms have become prominent channels of advertising, allowing business to reach specific target audiences and promote their products and services. Social media platforms such as Facebook, Instagram, Twitter have become major hubs for online advertising.

The rise of in-app advertising across these platforms with the growing popularity of video and interactive ad formats has further fueled the market growth. Such advertising also leverages data to optimize targeting and engagement, leading to more effective campaigns. Paid ads now dominate social feeds.

Key Restraints in the Market

Data privacy concerns to hinder growth in online advertising market

Mobile phones and other internet using devices have become a personal hub for information. With the increasing amount of sensitive data stored on these devices, privacy concerns have emerged as one of the most pressing issues. These concerns significantly hinder online advertising by leading to consumer distrust, ad avoidance and increased regulations that impact the effectiveness and reach of ad campaigns.

Consumers are becoming more aware of how their data is being collected and used under the context of online advertising, making them actively avoid interacting with ads and uninstalling apps they believe violate their privacy. This has also led to widespread adoption of ad-blocking technologies. This trend is largely driven by the growing desire to protect personal data. However, the same has had implications on advertisers. Regulatory development, such as the California Consumer Privacy Act, amid these concerns further add to the challenges faced by the mobile industry market. Strict data privacy laws have been implemented worldwide against the collection and use of consumer data for targeted advertising.

Opportunity

Adoption of AI as an opportunity in the mobile advertising industry

The adoption of artificial intelligence (AI) presents an opportunity for the online advertising segment by enhancing various tasks such as, campaign optimization audience targeting, creative component generation and so much more. AI-powered tools are automating tasks, enabling precise targeting and more personalized user experience, ultimately leading to effective and efficient advertising

For instance, AI powered creatives and copy ideation and generation are a game-changer in the mobile advertising landscape. The integration of AI into ad creation helps streamline the process along with enabling advertisers to conduct thorough testing. Introduction of the Online Advertising Market

Online advertising, otherwise known as digital marketing is a form of marketing that uses internet or online channels to promote products and services. It involves the creation ...

These are the key Twitter user statistics that you need to know.

Author: Víctor Yeste. Universitat Politècnica de Valencia.The object of this study is the design of a cybermetric methodology whose objectives are to measure the success of the content published in online media and the possible prediction of the selected success variables.In this case, due to the need to integrate data from two separate areas, such as web publishing and the analysis of their shares and related topics on Twitter, has opted for programming as you access both the Google Analytics v4 reporting API and Twitter Standard API, always respecting the limits of these.The website analyzed is hellofriki.com. It is an online media whose primary intention is to solve the need for information on some topics that provide daily a vast number of news in the form of news, as well as the possibility of analysis, reports, interviews, and many other information formats. All these contents are under the scope of the sections of cinema, series, video games, literature, and comics.This dataset has contributed to the elaboration of the PhD Thesis:Yeste Moreno, VM. (2021). Diseño de una metodología cibermétrica de cálculo del éxito para la optimización de contenidos web [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/176009Data have been obtained from each last-minute news article published online according to the indicators described in the doctoral thesis. All related data are stored in a database, divided into the following tables:tesis_followers: User ID list of media account followers.tesis_hometimeline: data from tweets posted by the media account sharing breaking news from the web.status_id: Tweet IDcreated_at: date of publicationtext: content of the tweetpath: URL extracted after processing the shortened URL in textpost_shared: Article ID in WordPress that is being sharedretweet_count: number of retweetsfavorite_count: number of favoritestesis_hometimeline_other: data from tweets posted by the media account that do not share breaking news from the web. Other typologies, automatic Facebook shares, custom tweets without link to an article, etc. With the same fields as tesis_hometimeline.tesis_posts: data of articles published by the web and processed for some analysis.stats_id: Analysis IDpost_id: Article ID in WordPresspost_date: article publication date in WordPresspost_title: title of the articlepath: URL of the article in the middle webtags: Tags ID or WordPress tags related to the articleuniquepageviews: unique page viewsentrancerate: input ratioavgtimeonpage: average visit timeexitrate: output ratiopageviewspersession: page views per sessionadsense_adunitsviewed: number of ads viewed by usersadsense_viewableimpressionpercent: ad display ratioadsense_ctr: ad click ratioadsense_ecpm: estimated ad revenue per 1000 page viewstesis_stats: data from a particular analysis, performed at each published breaking news item. Fields with statistical values can be computed from the data in the other tables, but total and average calculations are saved for faster and easier further processing.id: ID of the analysisphase: phase of the thesis in which analysis has been carried out (right now all are 1)time: "0" if at the time of publication, "1" if 14 days laterstart_date: date and time of measurement on the day of publicationend_date: date and time when the measurement is made 14 days latermain_post_id: ID of the published article to be analysedmain_post_theme: Main section of the published article to analyzesuperheroes_theme: "1" if about superheroes, "0" if nottrailer_theme: "1" if trailer, "0" if notname: empty field, possibility to add a custom name manuallynotes: empty field, possibility to add personalized notes manually, as if some tag has been removed manually for being considered too generic, despite the fact that the editor put itnum_articles: number of articles analysednum_articles_with_traffic: number of articles analysed with traffic (which will be taken into account for traffic analysis)num_articles_with_tw_data: number of articles with data from when they were shared on the media’s Twitter accountnum_terms: number of terms analyzeduniquepageviews_total: total page viewsuniquepageviews_mean: average page viewsentrancerate_mean: average input ratioavgtimeonpage_mean: average duration of visitsexitrate_mean: average output ratiopageviewspersession_mean: average page views per sessiontotal: total of ads viewedadsense_adunitsviewed_mean: average of ads viewedadsense_viewableimpressionpercent_mean: average ad display ratioadsense_ctr_mean: average ad click ratioadsense_ecpm_mean: estimated ad revenue per 1000 page viewsTotal: total incomeretweet_count_mean: average incomefavorite_count_total: total of favoritesfavorite_count_mean: average of favoritesterms_ini_num_tweets: total tweets on the terms on the day of publicationterms_ini_retweet_count_total: total retweets on the terms on the day of publicationterms_ini_retweet_count_mean: average retweets on the terms on the day of publicationterms_ini_favorite_count_total: total of favorites on the terms on the day of publicationterms_ini_favorite_count_mean: average of favorites on the terms on the day of publicationterms_ini_followers_talking_rate: ratio of followers of the media Twitter account who have recently published a tweet talking about the terms on the day of publicationterms_ini_user_num_followers_mean: average followers of users who have spoken of the terms on the day of publicationterms_ini_user_num_tweets_mean: average number of tweets published by users who spoke about the terms on the day of publicationterms_ini_user_age_mean: average age in days of users who have spoken of the terms on the day of publicationterms_ini_ur_inclusion_rate: URL inclusion ratio of tweets talking about terms on the day of publicationterms_end_num_tweets: total tweets on terms 14 days after publicationterms_ini_retweet_count_total: total retweets on terms 14 days after publicationterms_ini_retweet_count_mean: average retweets on terms 14 days after publicationterms_ini_favorite_count_total: total bookmarks on terms 14 days after publicationterms_ini_favorite_count_mean: average of favorites on terms 14 days after publicationterms_ini_followers_talking_rate: ratio of media Twitter account followers who have recently posted a tweet talking about the terms 14 days after publicationterms_ini_user_num_followers_mean: average followers of users who have spoken of the terms 14 days after publicationterms_ini_user_num_tweets_mean: average number of tweets published by users who have spoken about the terms 14 days after publicationterms_ini_user_age_mean: the average age in days of users who have spoken of the terms 14 days after publicationterms_ini_ur_inclusion_rate: URL inclusion ratio of tweets talking about terms 14 days after publication.tesis_terms: data of the terms (tags) related to the processed articles.stats_id: Analysis IDtime: "0" if at the time of publication, "1" if 14 days laterterm_id: Term ID (tag) in WordPressname: Name of the termslug: URL of the termnum_tweets: number of tweetsretweet_count_total: total retweetsretweet_count_mean: average retweetsfavorite_count_total: total of favoritesfavorite_count_mean: average of favoritesfollowers_talking_rate: ratio of followers of the media Twitter account who have recently published a tweet talking about the termuser_num_followers_mean: average followers of users who were talking about the termuser_num_tweets_mean: average number of tweets published by users who were talking about the termuser_age_mean: average age in days of users who were talking about the termurl_inclusion_rate: URL inclusion ratio

In the second quarter of 2025, the revenue of X, formerly Twitter, decreased to *** million U.S. dollars. The majority of the social network’s revenue is generated via advertising, followed by data licensing and other revenue. X company information X ranks among the biggest social networks worldwide. As of February 2025, the company reported a potential ad reach of *** million users worldwide. In 2024, the platform's annual revenue was estimated at *** billion U.S. dollars. The company has only been able to report a positive net income in 2018 and 2019, revealing a struggle to monetize users. X marketing and advertising Social media advertising spending in the United States is constantly growing. In 2025, the social media ad spend per U.S. internet user was estimated at *** U.S. dollars, and this figure is projected to sharply increase to over *** U.S. dollars by 2030. Along with Instagram, X is a popular marketing channel, and some brands and companies have made a name for themselves for being entertaining on the platform.

Discover the booming global internet ad spending market! Our comprehensive analysis reveals a $500 billion market in 2025, projected to grow at a 12% CAGR through 2033. Learn about key drivers, trends, restraints, and regional insights, including the dominance of major players like Google and Facebook.

The US has historically been the target country for Twitter since its launch in 2006. This is the full breakdown of Twitter users by country.

This is the breakdown of Twitter users by age group.

In 2024, YouTube's advertising revenue accounted for approximately 13.66 percent of Google's total revenue. That year, the video platform's annual ad revenues amounted to 36.1 billion U.S. dollars, up from the 31.5 billion U.S. dollars in the previous year. YouTube creators Video content creators on YouTube have been evolving with the platform since its creation. In 2020, it was estimated that YouTube supported over 800 thousand jobs worldwide, almost half of which referred to creators located in the United States. Apart from sharing a portion of YouTube advertising revenues, the most popular video creators can decide to license their existing content libraries for a limited amount of time in exchange for their advertising revenues. As YouTube ranked among the leading ad-selling companies worldwide in 2021, the recent success of financing companies focusing on user-generated video content does not come as a surprise. Digital video ads In 2021, global spending for online video advertisement surpassed 61 million U.S. dollars and is expected to reach approximately 90 million U.S. dollars by 2024. Video ads can engage users across multiple devices, with a 2021 survey of app developers worldwide seeing over 40 percent of respondents considering full-screen videos the most effective ad format to acquire new app users.

The platform is male-dominated with 68.1% of all Twitter users being male. Just 31.9% of Twitter users are female.

Twitter is ranked as the 12h most popular social media site in the world. The platform currently has 611 million active monthly users.

The Short Drama Purchase Channel Service market is experiencing robust growth, driven by increasing smartphone penetration, rising disposable incomes, and a surge in popularity of short-form video content. The market, estimated at $5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $15 billion by 2033. Key drivers include the expanding reach of social media platforms like Twitter, Meta, and Kuaishou, which are actively integrating short drama content into their ecosystems and leveraging targeted advertising to monetize this emerging market segment. The preference for easily consumable entertainment, particularly amongst younger demographics, further fuels demand. While data privacy concerns and the potential for content moderation challenges represent restraints, the market's overall trajectory remains positive. The segment breakdown reveals a strong preference for personal use, with the advertising delivery service model currently leading in terms of revenue generation. Further segmentation highlights the significant role of data analysis and optimization services in tailoring content and improving user engagement. Geographical analysis indicates a strong presence in the Asia Pacific region, particularly in China and India, driven by their large populations and rapidly evolving digital landscapes. North America and Europe also represent significant markets, with continued growth potential in both regions. Competition is fierce, with established tech giants such as Twitter, Meta, Baidu, and NetEase vying for market share alongside innovative, agile companies like Xinxin Information Technology and Kuaishou. The future success of players within this market will depend on their ability to effectively leverage data, create compelling content, and navigate the evolving regulatory landscape. Innovative monetization strategies and effective audience targeting will play a critical role in determining market leadership in the years to come.