Artificial Intelligence
Advertising is a Jackpot for Data Monetization
5
Mins Read
September 9, 2022

Data monetization has been happening for far longer than we've had a term for it - from the random emails you get from a business to the credit card offers you get in the mail. Businesses are making a profit off of people's data, but also off of data records, analytics and findings from business trends and decisions. But, aided by new technology finding new data to sell is easier and it just so happens that advertising is at the top of sources of revenue for data-driven companies in the global data monetization market at 28%, gaining an average net margin of 33%.

What is Data Monetization?

Data monetization is the process of turning data into revenue. Direct data monetization is selling data in raw form to a third party. Indirect data monetization is selling insights from data vs. selling the data itself. Data-driven businesses are those that have turned data into a key asset and use it to drive their decision-making.

Why Advertising is a top revenue producer within data monetization?

Advertising is a top revenue producer because it is the most effective method to use data to make decisions that will lead to conversions. By understanding customer behavior, preferences, and intent, businesses can deliver more relevant and targeted advertising, which leads to increased sales and ROI.

You can use advertising data to understand consumers from a purchase habits standpoint and even a psychological aspect. For example, by analyzing advertising data based on product type advertised with a demographic data set overlaid, an analyst could understand what product types align best with each age group, gender, locality, race and more to give further insight into what audiences a new product should target off the bat. This process could save a new business or new product launch time and money in finding the right target audience for them.

How AI Can Help With Data Monetization

Artificial intelligence (AI) can help data-driven businesses in a few ways:

1. Automating the process of data collection, analysis and decision-making

2. Helping to identify new opportunities for monetization

3. Enabling better customer service and support

4. Enhancing marketing efforts

5. Generating  new insights from data

Advantages of Data Monetization

There are several advantages to data monetization:

1. Increased revenue: This is the most obvious advantage of data monetization. When done correctly, data monetization can provide a significant boost

to revenue.

2. Improved decision-making: Data monetization can help businesses make better decisions by providing access to data that would otherwise be unavailable. This improved decision-making can lead to increased profits and competitive advantage.

3. Better customer insights: Data monetization can provide quick, valuable insights into customer behavior. This information can be used to improve customer service, develop new products, and target marketing efforts.

4. Increased efficiency: Data monetization can help other businesses become more efficient by reducing the amount of time and resources spent on data collection and analysis.

Disadvantages of Data Monetization

There are also some disadvantages to data monetization that should be considered:

1. Privacy Concerns: One of the biggest concerns with data monetization is privacy. When businesses sell customer data, there is a risk that sensitive information could be released. This could lead to identity theft, fraud, and other privacy breaches.

2. Competitive Advantage: Another concern with data monetization is that it could give some businesses a competitive advantage over others. Those with access to more data will be able to make better decisions and gain a larger market share.

3. Market Consolidation: Data monetization could also lead to market consolidation. As some businesses gain a competitive advantage, they may acquire other businesses or merge with them. This could reduce competition and lead to higher prices for consumers.

4. Misuse of Data: Finally, there is a risk that data could be misused. Businesses could use data to make decisions that are not in the best interests of consumers or society. For example, they could use data to target marketing efforts at vulnerable groups such as children or the elderly.

Data monetization can be a great way for businesses to increase revenue and improve decision-making. However, there are also some risks that should be considered before embarking on a data monetization strategy.

Data Monetization and the Cookieless Future

Cookies are going to go away eventually, meaning companies who prioritize first-party data will have a leg up in filling data gaps and being able to monetize that data.

This shift will require businesses to change the way they monetize data. They will need to find new ways to collect and analyze data. Additionally, they will need to develop new products and services that are not reliant on cookies.

Data Monetization and Privacy Concerns

As mentioned above,  one of the biggest concerns with data monetization is privacy. When businesses sell customer data, there is a risk that sensitive information could be released. This could lead to identity theft, fraud, and other privacy breaches.

To mitigate these risks, businesses will need to take steps to protect the privacy of their customers. This includes ensuring that only data that is absolutely necessary is collected and that all data is anonymized. Additionally, businesses should have strict security measures in place to prevent unauthorized access to customer data.

How CatapultX Views Data Monetization

At CatapultX, we believe that data monetization can be a great way for businesses to increase revenue and improve decision-making. However, we also believe that businesses need to be aware of the risks involved.

We believe that data monetization should only be used if it is done in a way that is transparent and protects privacy.

Within our VisionOne platform, we're analyzing moments within our publishers videos to understand data surrounding attention, contextualization, brand safety and more. Our mission is to achieve the deepest understanding of video - including all of the data it can provide.

ai in advertising white paper cover page by catapultx

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