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 more than 26 thousand advertising account and more than 211 thousand ad campaigns, interactions were the most used Facebook ad objective globally in January and February 2024. Traffic came second, with 32.6 percent.

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

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Auto-generated structured data of Windsor.ai Documentation - Facebook Ads (Meta) Field Reference from table Fields

Auto-generated structured data of Windsor.ai Documentation - Facebook Ads (Meta) Field Reference from table Available options

As of February 2025, the Philippines had the highest potential Facebook ad reach rate in the Asia-Pacific region, amounting to around ***** percent of the adult population. In comparison, Facebook ads in Japan had a potential reach of about **** percent among the population aged 18 years and over.

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.

This dataset contains detailed Facebook advertising data for the political party Sumar and its leader Yolanda Díaz for the period from 9 January to 21 July 2023. This timeframe includes the campaign and pre-campaign periods of the 2023 Spanish general election. The dataset provides a comprehensive overview of the party's advertising strategies on Facebook, including unique ad IDs from Facebook's ad library, average cost per ad, dates, ad text, links, ad categories and estimated reach segmented by age, gender and geography. The dataset also includes information on the languages used in the ads, providing insights into the party's targeting and communication approaches during this crucial election period.

Among the countries presented in the data set, the United States had the highest cost-per-click (CPC) for Facebook ads as of February 2025, with **** U.S. dollars. The lowest value belonged to India, with ** U.S. cents. Facebook CPC CPCs vary depending on the advertising campaign’s objective. If the aim is as simple as gaining post engagement, then CPCs are the least expensive. However, the more complex the objective, the higher the cost-per-click gets. The most expensive is app installs, which means that advertisers need to pay *** U.S. dollars per click that leads to customers installing apps, compared to **** U.S. dollars for post engagement. Brand awareness, page likes, reach and conversions are in the middle of the spectrum.

Election Facebook’s Ad Metrics 2024: Trump vs. Harris

A key event of 2024 is the U.S. presidential election. This project focuses on analyzing how Donald Trump and Kamala Harris use advertising to win votes, exploring their strategies, actions, and effectiveness.

Here is the Dataset i have used in the analytic:

File name: trump.zip and harris.zip (Original Data)

The files were downloaded from the Facebook Ad Library. The data focuses on two primary accounts: Trump and Harris, which had the highest number of advertisements and the largest ad spend. These accounts promoted two types of campaigns: presidential campaigns and victory funds. However, I will concentrate solely on the presidential campaigns. Date Range: Based on my research, presidential campaigns typically begin about a year before the election. Therefore, I collected data starting from February 25, 2023, the date Harris announced her candidacy to compete with Trump, up to the current date, December 7, 2024.

File name: Trump-Harris add-id.csv (Processed Data)

This is the main data of the "Election Facebook’s Ad Metrics 2024: Trump vs. Harris"

File name: AD-Tech-Analytic-Project-DashBoard.pbix

Power BI chart imported data from Trump-Harris add-id.csv (Processed Data) and some others

File name: 6state trump data.csv, datamichigan.csv, data nevada.csv

Data that filters from Trump-Harris add-id.csv (Processed Data) have been used in AD-Tech-Analytic-Project-DashBoard.pbix

As of February 2025, India was the leading country in Asia in regard to Facebook advertising reach. The country had a Facebook advertising audience of approximately ***** million users. Indonesia followed, with about ***** million users reached.

The ability to run targeted advertisements on popular social media platforms, such as Facebook, has enabled researchers to obtain quickly demographically and geographically diverse samples in response to research opportunities, at a very low cost. A shortcoming of using Facebook is that it employs algorithms to optimize ad delivery by favouring users who are most likely to click on them and, as a result, the characteristics of the end samples are likely to differ from the underlying population. The paper provides a short guide for those interested in recruiting survey participants through Facebook ads and suggestions on improving the characteristics of the end samples, especially on variables for which the ad targeting is less efficient. Empirically, the paper compares a Facebook ads sample to a gold standard (the European Social Survey) and provides open access to the replication data. The paper concludes with suggestions about the suitability of Facebook ads data for different types of research projects.

Dataset

This dataset was created by Ahmed Sherif

Released under Apache 2.0

Contents

The Facebook Users by Country Data (Cleaned) dataset is a collection of information on Facebook users from different countries. The dataset contains five columns of data, which are named as follows:

• Names: This column contains the names of the countries for which the data is collected.
• Users: This column provides the number of Facebook users in millions for each respective country.
• Facebook_Users: This column shows the percentage of the total population of each country that uses Facebook.
• Date_of_Data: This column indicates the date on which the data was collected and compiled.
• Population: This column represents the total population of each country.

How you can use this Dataset?

The Facebook Users by Country Data (Cleaned) dataset can be used in several ways. Here are some potential use cases:

• Market Research: Marketers can use this dataset to identify markets with the highest concentration of Facebook users. This information can be used to target Facebook ads to specific regions, optimize social media campaigns, and determine which markets to expand into.

• Business Strategy: Businesses can use this dataset to identify potential markets for their products or services. By analyzing Facebook usage rates in different countries, businesses can identify countries with high engagement rates and target those markets.

• Social Media Analysis: Researchers can use this dataset to analyze social media behavior in different countries. By comparing Facebook usage rates across different countries, researchers can identify cultural and social differences that affect social media behavior.

Access our extensive Facebook datasets that provide detailed information on public posts, pages, and user engagement. Gain insights into post performance, audience interactions, page details, and content trends with our ethically sourced data. Free samples are available for evaluation. Over 940M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:

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

This dataset contains a) script and data to replicate the analysis b) an additional file providing exemplary script to access the API of the Facebook Ad Library.

Among the countries presented in the dataset, Facebook’s highest advertising cost-per-mille (CPM) was in the United States, valued at ** U.S. dollars. For comparison, the lowest CPM, *** U.S. dollars, was recorded in India. What are other Facebook advertising costs and metrics? Cost-per-click (CPC) is another popular metric when it comes to advertising on the social platform. Globally, the average CPC on Facebook stood at ** cents at the end of 2024. This means that campaigns aiming at app installs, lead generation and product catalog sales are the most expensive, whereas campaigns targeting post engagement, messages and video views are on the opposite side of the spectrum. How does Facebook compare with other social media among marketers? The majority of marketers indicate that Facebook is the most important social platform for their business, with ** percent of respondents using the platform, compared to ** percent on LinkedIn. However, with recent data breaches, Facebook has seen some decrease in growth. Its position is still strong enough that marketers increase their spending on the social network. However, Instagram seems to be overtaking the older platform, and more industry professionals are planning to increase investments in the photo sharing platform than in Facebook.