Data-driven business models have seen unprecedented growth and their rise has raised awareness about the importance of data. Many people are aware that they are the product of any free online service. Today, most people are well aware of the value of their data.
Why is it so valuable to have our data?
“It’s all in grabbing the user’s attention and anticipating their behaviour.”
Online service providers can reap the benefits from advertising revenue if they have access to user attention and data. These two dimensions are so vital that most of their services can be accessed for free.
They have an audience to show ads to if they can capture user attention. The prediction of user behavior can be made by combining user attention and user data. This is simplified: What are the chances that a user will click on this ad if I present it to them? They can use user data to better nudge users into clicking on ads. This means that they can generate more revenue.
How much is my personal data actually worth?
There are many ways to answer this question:
- Divided by users, the market capitalization
- Willingness to pay online for services
- To estimate the amount of ads viewed online, time spent
Each valuation method has its limits. One method was underexplored. Divide the advertising revenue by Active users. This method is more precise than the commonly used market cap divided by users approach, as many companies mentioned also have other sources.
These are the results
In 2020, the average user’s data worth is $242.17
Google:
Google clearly has the best way to monetise users. YouTube ads are responsible for the strong growth in advertising revenue since 2016. Alphabet, Google’s parent company, currently receives $5 billion in advertising revenue. This is only a fraction of the $147 billion they make from Google Ads Platform.
Facebook:
Facebook and Instagram have been able to increase their revenue from users. Their acquisition of Instagram has significantly benefited their ability reach targeted users with ad content. Their user base exceeds 3 billion and their data collection is highly sensitive. Access to large amounts of social data, including user messages (Whatsapp), news and other content viewed, friends interacted with (Facebook), and analysis of user faces and images (Instagram). Facebook is an expert in forecasting user behaviours.
Twitter:
Advertising and data licensing are Twitter’s main revenue streams. Both revolve around the monetisation user data. They have made about $10 per user since they started in the advertising industry. The gaps between Amazon, Google, and Facebook are still very evident.
Spotify:
Spotify’s revenue is primarily generated by premium subscribers. However, advertising accounts are growing in importance. The annual monetisation of free users is between $3.50 and $4.50.
Reddit:
Reddit is the least profitable site on our list. However, they have 430 million active monthly users. This will allow them to focus more on it. Reddit’s latest valuation of $6B shows investors that they see the potential to monetise these 430 million users. Targeting data is based on groups and interests.
Amazon:
Amazon was initially a marketplace. This means that most of their revenue was generated from fees. Amazon is a market leader in many areas, including cloud, streaming, logistics and… Ads are the most lucrative stream, with 64% growth in 2020. They are able to monetise users because of the user attention they have gained through their marketplace and entertainment services. They are expected to be able quadruple their advertising revenues by 2026.
Snapchat:
Snapchat faces strong competition in the advertising market. This highlights the monopolistic nature platforms and data monetisation model. They have strong user attention (265 millions, daily active users). Because they have less data, their targeting capabilities are weaker.
Although we wanted to include Linkedin and Tiktok in our study, because both companies are privately owned, we couldn’t find enough data to compare them.
It is also important to remember that these numbers are global averages. A user’s data value heavily depends on their shopping habits and purchasing power.
In the past, users were blindly exploited. This is slowly changing with the increasing awareness of users. Search engines and social media platforms have become more privacy-friendly. Online platforms’ monopolistic tendencies will make it difficult to change. We believe that user awareness and regulatory changes can be more effective than disrupting a market. We look forward to the future transformation.
