Machine learning is a field of computer science that studies how to learn from data and perform intelligent tasks. Machine learning has many applications in various fields, such as facial recognition, translation, fraud detection, product recommendation, and advertising. In this article, we will introduce how Facebook’s advertising works and is distributed through the use of machine learning.
1. What is Machine Learning?
Machine learning is a field of computer science that studies how to design and build algorithms capable of learning from data and optimizing predefined objectives. Machine learning can be considered a part of artificial intelligence, but it also has many applications in other fields such as statistics, mathematics, data science, engineering, and biology.
To better understand machine learning, we need to distinguish between its two main types:
- Supervised learning: This is when machine learning is trained using pairs of input data and desired output. The goal of supervised learning is to find a mapping rule between inputs and outputs so that when given a new input, the machine can predict the corresponding output.
- Unsupervised learning: This is when machine learning is provided only with input data without any desired outputs. The goal of unsupervised learning is to discover hidden structures or patterns in the data so that when given a new input, the machine can analyze or synthesize information from it.
Machine learning is a vast and rapidly developing field with many applications in life and industry. To learn machine learning well, you need foundational knowledge in mathematics, statistics, programming, and computer science. You also need to keep up with the latest trends and research in this field.
2. How Machine Learning works in Facebook’s ad distribution
Facebook has billions of users worldwide, each with different personal information, interests, behaviors, and interactions. To display ads tailored to each user, Facebook uses machine learning algorithms to analyze data and make decisions. Facebook leverages machine learning to understand users’ needs, preferences, and behaviors, thereby delivering the most relevant and optimized ads.
There are three main steps in Facebook’s ad distribution process using machine learning: auction, ranking, and allocation.
Auction
When a user visits Facebook, the system identifies available ad placements on the website or app. Then, it sends requests to advertisers registered to bid for those placements.
Each advertiser submits a bid, including the maximum price they are willing to pay per ad impression (cost per impression – CPM) and other campaign details. The system selects the highest bids to move on to the next step.
Ranking
At this stage, the system estimates the probability that the user will interact with the ad, such as clicking, sharing, commenting, or purchasing. To do this, it uses machine learning models trained on historical user and ad data.
Each model produces a score for each type of interaction, called the action rate. The system multiplies the action rate by the CPM to obtain a value score. This value measures the economic effectiveness of showing the ad to the user.
Allocation
In the final step, Facebook’s system compares the value scores of the ranked bids and selects the highest-value bids to display ads to the user. The system also considers other factors like content diversity, user comfort, and compliance with Facebook’s policies and guidelines.
Machine learning is a powerful tool that optimizes Facebook’s ad distribution efficiency, benefiting both advertisers and users. However, it also faces challenges such as protecting user privacy, ensuring algorithm fairness and transparency, and adapting to constant market and consumer demand changes.
3. Guide to running effective Facebook ads
Facebook Ads is an effective marketing tool that helps businesses reach their target customers on the Facebook platform. To run Facebook Ads effectively, you need to master the following steps:
Define Advertising Objectives
The advertising objective is the most important factor determining the success of the campaign. Therefore, first, you need to clearly identify what your advertising objective is. Do you want to increase reach, engagement, conversions, or sales?
The goal of increasing reach helps you show your ads to more people. The goal of increasing engagement helps you attract users’ attention and encourage them to interact with your ads, such as likes, comments, and shares. The goal of increasing conversions helps you drive users to take desired actions, such as subscribing to newsletters, filling out forms, or making purchases.
Set Up Target Audience
The target audience is the group of people you want your ads to reach. You can target your ads based on criteria such as geography, age, or interests. For example, regarding geography, you can target your ads by country, region, city, etc. Regarding age, you can target your ads by age range, gender, etc. Regarding interests, you can target your ads based on interests and behaviors.
Creating Ads
Your ads need to have attractive content that captures users’ attention. You should pay attention to basic elements such as the headline, image/video, and content. The headline should be short, concise, and convey the main message of the ad. The image/video should be sharp, eye-catching, and relevant to the ad content. The content should be engaging, concise, and provide useful information to users.
Setting Budget and Ad Schedule
You need to determine your advertising budget and schedule. The advertising budget is the amount of money you are willing to spend on your ads. The ad schedule is the time period during which you want your ads to be displayed.
Monitoring and Analyzing Results
After running your ads, you need to monitor and analyze the results to evaluate the effectiveness of the campaign. You can track metrics such as reach, engagement, and conversions. Based on the analysis, you can adjust your advertising campaign to achieve better results.
Machine learning plays an important role in Facebook’s ad distribution. This is a trend that cannot be ignored in today’s digital and competitive era. By using machine learning technology, Facebook can display ads to audiences who are more likely to be interested in your products or services.