In this blog are the latest Facebook advertising statistics that show how effective Facebook ads are now and what’s likely to happen in the future.

According to the source's analysis based on a total of ***** million impressions, the leading type of campaign on Facebook was brand awareness, with over ** percent of shares. Traffic followed second, with **** percent of the total.

36.8% of the entire world’s population uses Facebook at least once per month.

This fileset contains a series of screenshots taken from our facebook advertising account. A few days ago we noticed that some negative "SEO" tactics, for lack of a better term, were having a negative impact on the performance of ads and fan engagement on the facebook page that we've been building.

I developed a custom software package, which utilizes nueural networks I've developed, to identify a target demographic, and suggest advertising content for said target demographic.

After a short training period we were able to create advertisemsents on facebook that averaged a cost of 0.01 cents per like. We also had a fan page engagement of nearly 4 times that of major brands like Wal-Mart.

Shortly after we began to obtain success we started noticing problems with our page. Since we have a stalker issue, we determined that the issues with our page were likely related to him.

We assued this because we had a disproportinately high number of spammy, negative, and inapporpriate comments on our posts. Offline harassment of our staff by the stalker also increased significantly during this time.

Curiously, we believe that the incident with the stalker allowed us to ascertain some interesting observations about Facebook's algorithims, which I've outlined below.

We believe, after reseraching this issue, that Facebook's algorithims suffer from the following issues:

1. They are easily gamed. We think that Facebook's algorithims are hypersensitive to negative comments being made on a post, and conversely likely positive ones as well. If a post is hidden, the comments are negative, or if a user interacts with the post negatively in some way, then Facebook's algorithims will "punish" your page.

2. We think that a series of scripted fake bot accounts would easily cause the issues that we've been expriencing.

As you can see from the data provided, over 90% of our likes come from paid facebook advertisement, therefore we do not have a significant number of fake accounts on our page brought in by third party advertising because we didn't do any of that.

Moreover, we did not send any of our fans obtained via mailing lists, or offline contact to our facebook page, those fans participate with us via email and/or through our private Google+ community.

So it is safe to say that our problems have not been caused by purchasing a large amount of fake likes from any third party vendor.

In addition, because our likes were gained very quickly, at a rate of about 2.5k likes a day, we do not believe that we have suffered from changes in the general demographic of our Facebook fan base over time.

Yet almost immediately after we started expericing trolling issues with our page, we also noticed a dip in the number of fans our posts were shown to by Facebook, and the performance of our ads began to go down, even though the content on our page had not changed.

We attributed this to holes in Facebook's algorithims, and potentially to the excessive use of fake bot accounts by Facebook itself.

We cannot prove the latter satement, but there have been similar reports before. Reference - http://www.forbes.com/sites/davidthier/2012/08/01/facebook-investigating-claims-that-80-of-ad-clicks-come-from-bots/

This article from Forbes outlines how one startup company repoted that up to 80% of their Facebook likes were fake bot accounts even though they paid for advertising directly through Facebook.

Our reserach suggests that Facebook's advertising platform functions as follows: - An advertiser pays for likes with Facebook, and the quality of the content on their page is initially assessed by those who are liking the page, but once the page obtains a following, we believe that the quality of the content is assessed by how many people like the posts on the page directly after they are posted.

If a post gets hidden, marked as spammed, skipped over, whatever, then we beleive that Facebook kicks that post out of the newsfeeds. If this happens to a significant number of posts on the page, then we believe that Facebook places the page on an advertising black-list.

Once on this black-list ads will begin to perform poorly, and content will drop out of newsfeeds causing even the most active page to go silent.

We tested this by posting pictures of attractive blond women, which with our demographic would have normally obtained a large number of likes and we struggled to get even 10 likes at over 20k page likes when we would have previosuly obtained almost 100 likes without boosting at only 5k page likes.

Why this probably isn't seen more often: In most cases this probably takes a while to occur as pages become old and fans grow bored, but in our case, because we have a stalker trolling our page with what appears to be hundres of scripted bot accounts, the effect was seen immediately.

Our data suggests that it became a tug of war between our stalker's army of fake bot accounts (making spammy comments, hiding our posts from newsfeeds, etc) and the real fans that actually like our page (who were voting our conent up - i.e. liking it, etc).

If you look at the graph of page likes in the figures provided - you can see that the darker purple are the fans we obtained via facebook advertising, well over 90%. We believe that the light purple (the "organic" fans) is mostly comprised of our stalker's fake drone accounts. We have less than 20 family members and friends liking our page, when we began this experiment we asked them not to interact with our page or the content.

In conclusion: We still have a lot more work to do, but it is highly likely that many Facebook likes are either scripted bots, and/or that Facebook's "weighting" algorithims are very suceptible to gaming via negative "SEO" tactics. Conversely, they are likely sensitive to gaming via positive "SEO" tactics as well.

Of course we cannot say for certain where the Facebook accounts that like a page come from without acess to their internal systems, but the evidence does strongly suggest that Facebook might be plagued with a large quantity of bot accounts, and that their algorithim has to be sensitive to actions from live users, so that the quality of the content can be easily ascertained. Otherwise it would be pretty easy for an advertiser to game Facebook's system by paying for, and getting, a large quantity of likes for content that is not appealing to any significant group of people.

Again we have to reiterate that we have no solid proof of this, but our data strongly suggests that this is the case.

We have reported the issues to Facebook, but interestingly, after we made it clear that we were going to analyze and investigate the issues with our page, we have been suddenly and incessently plagued with a never ending stream of "technical difficulties" related to our advertising account.

If you'd like to collaborate on this project, please feel free to email me at Jamie@ITSmoleculardesign.com.

Facebook probably needs no introduction; nonetheless, here is a quick history of the company. The world’s biggest and most-famous social network was launched by Mark Zuckerberg while he was a...

During a January 2025 global survey among marketers, 61 percent reported plans to increase their organic use of LinkedIn for marketing purposes in the following 12 months. YouTube and Instagram followed, respectively, mentioned by 60 and 55 percent of the respondents intending to use them more. According to the same survey, Facebook was the most important social media platform for marketers worldwide.

During a 2025 global survey, approximately 48 percent of responding business-to-consumer (B2C) marketers said Facebook was the most important social media platform. Among business-to-business (B2B) professionals, LinkedIn ranked first, selected by 53 percent. According to the same study, YouTube and LinkedIn were the social media in which most global marketers planned to increase their investments throughout that year.

UPDATED 08/12/2013: The editor of Indie Review Magazine, spoke with Facebook on 08/12/2013, and it was confirmed that the technical difficulities with the advertising account have been resolved.

They will be assisting in an investigation to handle the troll problem with the magazne's page, and the other difficulties the page has been experiencing as a direct result of the stalker's harassment.

Attached you will find screenshots of various ads that we've released on Facebook.

The conclusion: The software predicted a performance for all of the ads pictured of 0.01 - 0.03. Prior to having major issues with negative "SEO" tactics on our facebook page the software's predictions for advertising perforamnce was extremely accurate.

After we began experiencing the troll problem, the advertisements began to perform in a very unpredicatble, sporadic, and oftentimes schizophrenic fashion.

The same ad, with the swimsuit model, showed a sustained performance of 0.08 earlier in the day, and later in the evening, after a series of technial difficulties on Facebook's end (with our page) the perforamance of the ad shot down to 0.19.

We took video of the ads from the moment they began to run until we paused them after the money started to deplete at an alarming rate, and what we found was shocking.

In the first 30 minutes our page was growing at a rate of around 3 likes a second (which is what is expected for the predicted growth rate of the ad - 0.01 to 0.03). This rate of growth had been sustained for days in the past with a very similar ad.

Then suddenly the ad performance plunged to dismal numbers that do not accurately reflect the rate at which our likes were initially gained. Not on the specific day in question nor in the past (with the same or similar ad and page content).

At this time, we have paused all of our facebook ads and plan to thoroughly analyze this data.

As stated in a previous article, which is linked below, we cannot comment directly on the internal workings of Facebook's advertising platform as we do not have access to that system - but our data highly suggests that if someone is using bot accounts they can significantly impact page performance.

We have been relying heavily on our custom software pagacke to anaylze the sitaution, and with the help of my neural networks we were able to identify patterns which revealed problem areas and allowed us to adjust our advertising strategy so that our page would be less suspectible to negative SEO tactics.

UPDATE: 08/10/2013 Facebook will be speaking with the editor of Indie Review Magazine, they indicated that there were experiencing technical difficulties. These technical difficulties have been impacting our page for days, thus we've halted our experimentation and will update with another figshare article, once more information has been obtained.

Reference: 1. http://www.forbes.com/sites/davidthier/2012/08/01/facebook-investigating-claims-that-80-of-ad-clicks-come-from-bots/ 2. Previous figshare article: http://figshare.com/articles/Potential_Issues_with_FB_Advertising_Algorithms_/767331

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In 2024, Meta (formerly Facebook Inc) generated over 160 billion U.S. dollars in ad revenues. Advertising accounts for the vast majority of the social network's revenue. Facebook advertising revenue – additional information Facebook’s business model heavily relies on ads, as the majority of social network’s revenue comes from advertising. In 2020, about 97.9 percent of Facebook's global revenue was generated from advertising, whereas only around two percent was generated by payments and other fees revenue. Facebook ad revenue stood at close to 86 billion U.S. dollars in 2020, a new record for the company and a significant increase in comparison to the previous years. For instance, the social network generated almost seven billion U.S. dollars in ad revenue in 2013, about 10 billion less than the 2015 figure. Facebook's average revenue per user also significantly increased in the same time span, going from 6.81 U.S. dollars in 2013 to 32.03 U.S. dollars in 2020. The U.S. and Canada are important markets for Facebook, considering the average revenue per user (ARPU) in these two countries is far above the global average. Facebook’s ARPU in the U.S. and Canada was 41.41 U.S. dollars in the last quarter of 2019, while the global average was 8.52 U.S. dollars. In Europe, Facebook’s average revenue per user was 13.21 U.S. dollars during the same time period. In terms of segments, mobile is the most promising advertising form for the company. In 2018, Facebook’s mobile advertising revenue already accounted for 92 percent of the social network’s total advertising revenue. Facebook’s mobile advertising revenue grew from an estimate of 13 billion U.S. dollars in 2015 to 50.6 billion U.S. dollars in 2018.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16190527%2F53f929ff911508241fa2b6808c9d885f%2FFacebookAdsBidding-1200x630-1.jpg?generation=1696942877786519&alt=media" alt="">

Subject:

Facebook recently introduced a new bidding system called "average bidding"(test group) alongside the existing "maximum bidding"(control group) system. These bidding systems determine which ads get displayed to users based on how much advertisers are willing to pay.

With "maximum bidding," advertisers specify the maximum amount they are willing to pay for each impression. For example, an advertiser might say, "I'm willing to pay a maximum of $10 for each impression."

With "average bidding," advertisers specify an average amount they are willing to pay for impressions. For instance, they might say, "On average, I'm willing to pay $6 for each impression."

Here's the key point: In this dataset, we've gathered the results of these two bidding strategies over the last 40 days to see which one is more effective at getting their ads displayed to the target audience.

Business Challenge: Unleashing the Power of Facebook Advertising

As a forward-thinking company poised to make waves in the realm of Facebook advertising, we're on a mission to unearth the most advantageous approach for our brand. Our burning questions:

1. Maximize Clicks and Purchases: Which strategy will propel us toward our goal of skyrocketing clicks and driving purchases?
2. Battle of Titans: Is there a discernible and statistically significant difference between the two bidding options?

Enter the AB Test: Today, we embark on a journey of data-driven discovery, where the clash of titans—Average Bidding versus Maximum Bidding—will be meticulously dissected and evaluated. We're on a quest for insights that will define our Facebook advertising strategy's future, using data as our compass and innovation as our weapon.

The outcome of this AB Test will not just answer our questions but will be the harbinger of a glorious era in our Facebook advertising endeavors. Stay tuned for a transformation that will leave a mark on the digital advertising landscape.

Features:

• Impression: Number of impressions per ad.
• Click: Numbers of clicks per ad.
• Purchase: The number of products purchased after the click.
• Earnings: Earning after purchase.

The attached figures will show how Facebook's algorithims are sensitive to negative SEO tactics.

Indie Review Magazine obtained the majority of their likes via paid advertising through Facebook.

They achieved ad performance in both international and US markets of 0.01 to 0.03 cents a like on average. However, the magazine is suffering from a very serious troll sitaution.

A violent stalker - who has also been sending employees death threats and threatening messages/etc on social media sites - began targeting the magazine's facebook page as soon as it obtained some success.

You can see from the graphs that the organic likes (the light purple) increased as the paid likes increased, but decreased disproportionatly to the paid likes.

Thus, a massive decline in the organic likes directly preceeded a steady decline in paid page likes, which was a direct result of plumuting ad performance (because the "ranking" algorithims at Facebook, disproportionately value page un-likes). As a result it is possible for negative SEO firms and/or individuals to game the system.

As a result of these negative SEO tactics the magazine has noted ad performance which ranges from 0.02 cents per like and swiftly changing to greater than 4 dollars a like. This is what they refer to as the "money dump".

Slowly over time, the stalker has built up greater than one thousand fake scripted accounts, that he usses to automatically unlike their page whenever a promising post is made.

We suspect and our data highly suggests that Facebook's content ranking algorithims are especially sensitive to this tactic, thus it is possible that there are many pages out there who are suffering from dismal ad performance which may be directly related to sitatuions out of their control.

Negative SEO tactics emloyed by a competitor or in the case of Indie Review Magazine, a stalker, can have a very significant negative impact on the performance of an advertising campaign.

Without acess to Facebook's ranking algorithims we cannot say for certain what is going on behind the scenes at Facenook, but it is obvious from our data that Facebook's algorithims are very suceptible to negative SEO tactics.

If you would like to contact me regarding this reserach, you may email me at Jamie@ITSmoleculardesign.com.

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Post ID Post Content & URL Date Posted Hashtags Number of Comments Number of Shares Likes & Reaction Counts (by type) Video View Count Page Name & Category Page Followers & Likes Page Verification Status Page Website & Contact Info Is Sponsored Post Attachments (Images/Videos) External Link Data And much more

The Ad Serving & Retargeting Services market is experiencing robust growth, driven by the increasing adoption of digital advertising and the need for precise audience targeting. The market, estimated at $50 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $150 billion by 2033. This expansion is fueled by several key factors: the rising popularity of programmatic advertising, which automates the buying and selling of ad inventory, leading to increased efficiency and cost-effectiveness; the growing sophistication of retargeting technologies, allowing advertisers to re-engage users who have previously interacted with their brand; and the proliferation of connected devices, expanding the reach of digital advertising campaigns. Key players like Facebook, Google, and The Trade Desk are at the forefront of innovation, continually developing advanced targeting capabilities and data analytics solutions to enhance campaign performance and improve return on investment (ROI) for their clients. However, the market also faces certain challenges. Data privacy concerns and increasing regulations, such as GDPR and CCPA, are imposing restrictions on data collection and usage, impacting the effectiveness of retargeting strategies. Furthermore, ad fraud remains a significant problem, leading to wasted ad spend and eroding advertiser confidence. To navigate these challenges, companies are investing heavily in fraud detection technologies and adopting privacy-preserving solutions, such as federated learning and differential privacy. The market segmentation is expected to be further diversified as niche players emerge, focusing on specific industry verticals and advanced technologies like AI-powered targeting and contextual advertising. Growth in the Asia-Pacific region is projected to be significantly high, driven by the increasing internet and smartphone penetration in developing economies.

In a survey fielded in late 2022 among global advertising, marketing, and media agencies it was found that ** percent of respondents believed that image ads of Facebook were extremely successful. The same was true for short video ads. Messenger ads were found not successful at all by **** percent of responding agencies.

In a November 2019 survey, U.S. retailers were asked about the single social platform they were spending the most money on advertising. According to the results, ** percent of responding retailers in the country were devoting major parts of their budgets to Facebook ads and further ** percent said the same about Instagram.

The Ad Tech market is experiencing robust growth, driven by the increasing adoption of digital advertising across various industries and the continuous evolution of programmatic advertising. The market, estimated at $400 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $1.2 trillion by 2033. This expansion is fueled by several key factors, including the escalating demand for targeted advertising, the proliferation of mobile devices and connected TVs, and the rising sophistication of data analytics used to optimize ad campaigns. Key players like Google, Facebook, Amazon, and others are investing heavily in research and development, leading to innovative ad formats, improved targeting capabilities, and enhanced measurement solutions. The market is segmented by delivery method (web-based, cloud-based, on-premise) and target customer (large enterprises and SMEs). Cloud-based solutions are experiencing significant traction due to their scalability, flexibility, and cost-effectiveness, while large enterprises represent a substantial revenue stream due to their higher ad spending. Geographic distribution shows a strong presence in North America and Europe, but the Asia-Pacific region demonstrates significant growth potential given its burgeoning digital population and increasing internet penetration. However, challenges such as increasing regulatory scrutiny regarding data privacy and the need for greater transparency in ad measurement pose potential restraints to market growth. The competitive landscape is highly concentrated, with a few major players dominating the market. However, the emergence of innovative startups and specialized ad tech companies is fostering competition and driving innovation. The market's future trajectory will be significantly influenced by the ongoing evolution of artificial intelligence (AI) and machine learning (ML) in ad targeting and optimization, as well as advancements in cross-device tracking and identity resolution. Furthermore, the increasing importance of addressing ad fraud and brand safety will shape industry practices and technological developments. To maintain competitive advantage, ad tech companies are focusing on delivering robust analytics, improving campaign performance, and ensuring compliance with evolving data privacy regulations. This necessitates a continuous adaptation to the changing technological landscape and consumer behavior.

Much research has examined how crime rates vary across urban neighborhoods, focusing particularly on community-level demographic and social characteristics. A parallel line of work has treated crime at the individual level as an expression of certain behavioral patterns (e.g., impulsivity). Little work has considered, however, whether the prevalence of such behavioral patterns in a neighborhood might be predictive of local crime, in large part because such measures are hard to come by and often subjective. The Facebook Advertising API offers a special opportunity to examine this question as it provides an extensive list of “interests” that can be tabulated at various geographic scales. Here we conduct an analysis of the association between the prevalence of interests among the Facebook population of a ZIP code and the local rate of assaults, burglaries, and robberies across 9 highly populated cities in the US. We fit various regression models to predict crime rates as a function of the Facebook and census demographic variables. In general, models using the variables for the interests of the whole adult population on Facebook perform better than those using data on specific demographic groups (such as Males 18-34). In terms of predictive performance, models combining Facebook data with demographic data generally have lower error rates than models using only demographic data. We find that interests associated with media consumption and mating competition are predictive of crime rates above and beyond demographic factors. We discuss how this might integrate with existing criminological theory.

The global social advertising and social media marketing market is experiencing robust growth, driven by the increasing penetration of smartphones and internet access worldwide, coupled with the escalating adoption of social media platforms. The market, currently valued at approximately $450 billion in 2025 (estimated based on typical market size for this sector), is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This growth is fueled by several key factors. Firstly, businesses are increasingly recognizing the effectiveness of targeted advertising on social media platforms like Facebook, Instagram, and TikTok to reach specific demographics and achieve higher conversion rates compared to traditional marketing strategies. Secondly, the continuous evolution of social media algorithms and advertising tools provides businesses with more sophisticated targeting capabilities and performance measurement metrics. Thirdly, the rising popularity of influencer marketing, where brands collaborate with social media personalities to promote their products or services, further contributes to the market's expansion. Finally, the integration of e-commerce functionalities within social media platforms simplifies the purchase process for consumers, boosting sales and strengthening the overall market. However, the market faces certain challenges. Data privacy concerns and regulatory changes are forcing companies to adopt more transparent and user-centric data handling practices. Furthermore, the increasing sophistication of ad-blocking technologies and the rising cost of advertising on premium social media platforms present hurdles for businesses. Despite these challenges, the market is expected to maintain its strong growth trajectory, driven by innovation in advertising formats (e.g., short-form video ads, augmented reality experiences), and the continuous expansion of social media user bases globally, particularly in emerging markets. Segmentation within the market reflects this, with Social Advertising continuing to dominate, but Social Media Marketing growing significantly due to its more nuanced and relationship-building approach. Leading companies like Facebook, Google, and Microsoft are continuously innovating and investing in their respective platforms to maintain their competitive edge in this dynamic and lucrative market.

These are the raw results of a survey examining the attitudes of Hong Kong students towards the use of targeted promotion on Facebook. It was conducted by librarians at City University of Hong Kong and Hong Kong Baptist University from 20-26 Jan 2017. A total of 1,131 responses were received.