Why search for gold when you have a gold mine? Confused, don’t be! Your customer data is like a gold mine.
Converting data into a revenue-generating stream is tricky but essential for your company’s economic growth. Follow our complete guide to monetize your data and outperform your competitors.
Plenty of customer data is easily accessible from websites, mobile apps, online transactions, social media platforms and more. Hence, data monetization is trending like never before. Also, the rise in the volume of user information has led to a boom in the data market.
According to a study, the value of the global data monetization market is estimated to reach $3,70,969 by 2023.
So, more and more businesses are getting involved with data monetization.
First, let us understand the meaning of customer data and data monetization, later we’ll get into a detailed discussion on how to monetize your data.
What is Customer Data?
In simple terms, any information about your customers, such as contact details, region, buying habits, website visits, etc. refers to customer data. This data is a static asset unless you turn it into a strategic asset for your business.
Once you transform this customer data into a strategic asset, you’ll see the wealth it can bring. You can monetize your data with monetization platforms and create revenue streams.
What is Data Monetization?
The process of generating money from the available data is called data monetization. Your customer data can be used as a revenue-generating asset or as a cost-saving opportunity. You can either go for direct or indirect monetization depending on your business when it’s required to monetize your data.
Direct monetization refers to the process of directly converting your data into revenue for your business.
You can monetize directly by selling your products in your website or app, by selling your data segments or through your own PPC ads as well. Direct monetization means monetizing directly from your own sources.
Indirect monetization refers to the process of indirectly monetizing by sharing the derived data insights, publishing ads of partnered brands, and so on. Here, you’ll indirectly monetize your data. Indirect monetization helps you profit through indirect sources.
However, low-quality data is a matter of concern in data monetization efforts. It is essential to process the data gathered from users before monetizing it.
Otherwise, the result may not be as expected by you. For in-depth understanding, let us dig into different types and sources of data.
Types of Customer Data
There are four main types of customer data:
Identity Data: Personal information such as name, phone number, address, date of birth, etc. which indicates the identity of the customers is identity data.
Quantitative Data: Online activities such as website visits, online transactions, social media activities, product visits, online queries of the customers constitute quantitative data.
Descriptive Data: Gathering information about customers’ lifestyle, career details, education details, family details refer to descriptive data.
Qualitative Data: Data generated from user ratings for a product or service, personal opinions expressed in a survey, etc. is qualitative data.
Raw data is not as profitable as the segmented data. It’s crucial to categorize and evaluate which of your data has the potential to generate money. Then, plan to monetize your data. We have discussed a lot about customer data so far, next we’ll discuss the sources of customer data.
Sources to Gather Your Customer Data
A data source is a location from where you can collect all the data. There are a wide variety of sources to gather customer information; they are:
Websites, browsers, online ads, mobile apps, online and offline surveys, social media platforms (Facebook, Twitter, etc.), customer service records, online stores and purchase data, online transactions, web analytics, CRM systems, customer reviews and ratings, online communities, email subscription, online campaigns, internal data (official information) and many more.
You may question, why should we accumulate so much of customer data?
The answer is simple, data is the main ingredient to analyse and target your audience for customer data monetization, and without that, you won’t be successful in the data industry.
Hence, there is a considerable need for collecting customer data and to monetize your data. Furthermore, you will understand why you need customer data for digital marketing.
Need for Customer Data
Customer data will tell you exactly what your customers want. You need this data to create a superior customer experience. Hence, gathering user information is one of the most critical steps in data marketing.
You can use customer data for targeting and retargeting your audience as well. It will not only maximize profits but also increase customers for you.
Hence, there is a growing demand for customer data across the world.
It wouldn’t be wrong to say that customers are the new market-makers. You can only sell a product when there is a demand for it.
So, how will you know which product has more demand? That’s when you need customer data. Analyzing customer data plays a crucial role in data monetization. Hence, data is wealth for all businesses.
Value of Customer Data
Data is the shortest path to make additional revenue for your business. Surprisingly, some companies are generating billions of revenue by monetizing their customer data. But, not all businesses are thriving in effective utilization of their resources.
Commercializing data is one of the essential means to extract maximum value out of your data. Some of the high-performers are not only enterprising their customer data but are also using it as a competitive advantage. Hence, the customer data is most valuable for all data-focused businesses.
So far, we have discussed the importance of customer data. Further, you’ll learn how to prepare and monetize your data.
Here Are the Detailed Steps for Customer Data Monetization
How to Prepare Your Data for Monetization?
Data marketing requires high-quality data. The profitability factor is more for processed data when compared to raw data.
So, it’s crucial to sort your data inventory before you get to monetize your data.
Transforming your static asset into a strategic asset is not that easy. First, you have to identify whether your data is suitable for internal or external monetization.
The process of leveraging customer data to optimize the products and services within an organisation is internal data monetization.
Monetize your data by selling your customer data externally to brands or advertisers, which creates additional revenue for your business. The process of monetizing the customer data externally for revenues is called external data monetization.
Later, categorize your customer data, analyse it and prepare market-ready data segments. Before you get into the marketing part, know how to classify and process the data you have. Once you finish segmenting the data, you can go ahead to monetize your data.
There are different ways to classify the data, and one crucial method is data segmentation.
For example, you want to sell cricket-themed apparel, but you are advertising it to users who are interested in soccer. Do you think you’ll get enough buyers? No! First, identify customers who actively follow cricket, sort your target audience and then market your products to them. The profitability factor is more when you are strategically reaching your customers.
Likewise, your customer data needs to undergo segmentation process, for you to monetize your data and extract maximum value from it.
What is Data Segmentation?
Data segmentation is the process of categorizing data according to specific guidelines and parameters. Segmenting the data helps in finding the high-opportunity groups that improve marketing experiences. Classifying raw data into different segments is an essential factor to monetize your data.
The primary step of data segmentation is sorting data into different groups. They are:
It is a marketing approach which focuses on serving customers in some geographical regions. The target audience is categorized based on a city, country, state, etc.
Demographic segmentation method will categorise data based on age, gender, educational qualification, religion, caste, income and so on.
The psychographic aspects of consumers, such as hobbies, interests, values, opinions, activities constitute psychographic segmentation.
The marketing method which stresses on consumer behaviour. Here the aspects like brand loyalty, response to a product, user experience, frequency of usage, etc. come under behavioural segmentation.
Analyzing the segmented data is your next obvious step. Customer data analysis is as vital as data segmentation. You will recognize the potential of your customer data through data analytics. It will pave a path to monetize your data effectively.
What is Data Analytics?
The process of analyzing data to boost productivity and revenue-generating opportunities for a business is data analytics. Data analysis is carried out through qualitative and quantitative techniques such as Factor Segmentation, K-Means Clustering, Two-Step Cluster Analysis and Latent Class Cluster Analysis. Data analytics is one of the emerging fields in the business world today.
Role of Data Analytics in Customer Data Monetization
Data analytics plays a huge role in adding incremental value to your customer data. Analyzing your data helps you in outperforming your competitors. There is a 35-40% increase in companies who are entering into data analytics and data monetization when compared to 2018.
Till now, we have discussed everything about customer data. Now you are ready to monetize your data. The next fundamental question is, where do you sell your customer data?
Where to Sell Customer Data?
Data market is where you can sell or buy the customer data. Some prefer a centralized data market while some go for decentralized data market.
Centralized Market – Customer data is stored and marketed under one centralized organisation. Here the buyers and sellers trade under one centralized system.
Decentralized Market – The marketers form different networks to create their marketplace without any centralized system.
Apart from these, there are platforms like Audienceplay, Acxiom, Lotame, etc. which deal with customer data monetization. You can trust these platforms to segment your data, extend your audience segments or to monetize your data segments. They not only help you in segmenting your data but also assist in mapping your audience across the online environment. Ultimately, their goal is to monetize your data.
The data market is where you can monetize your data to accomplish significant economic growth for your business. No doubt, you have a higher opportunity to generate revenue through customer data monetization, but there are some risks as well.
Since your customer data is a revenue-generating asset, it is continuously under threat. So, you should give utmost importance to data security.
What is Data Security and Why is it Important For You?
Data security or information security is a process of protecting customer data from unauthorized access. You should give the utmost prominence to data security while you monetize your data.
Data security is one of the most emerging fields in the IT industry. There is a lot of scope in the field to develop various techniques and methods to strengthen data security. Here are some data security mechanisms which are very useful in data security.
Data Security Mechanisms
Authentication: Here, the user needs to prove the identity to the server. And if the user fails, the access is denied. Fingerprints, user names, passwords, face recognition, etc. are some primary authentication measures.
Authorization: In the security method, only the user who has the permission will be able to access the data. You will grant or deny permission for a particular user who can access your data.
Risk Assessments: It is the process of analyzing which of your data is under a severe threat and then understanding the intensity of data security it requires. This data security measure is instrumental in protecting highly sensitive data. Risk assessments are critical when you monetize your data.
Encryption:Encrypting user data will prevent hackers from acquiring any useful information from your data. The stolen data will become entirely useless for the attackers due to the encryption.
Masking: It is a process of masking the original data from hackers. In case of any data breach, the hacker won’t get the original data.
Tokenization: It is the process of replacing sensitive data to insensitive data. So, even stolen or hacked data will not have any value.
Hashing: Converting input data into shorter alphanumeric characters is hashing. The output generated after the conversion is called a hash. The hash value masks the original data, and it can be decoded only by referring to a database or a hash table. So, hashing is one of the most prominent data security mechanisms which is used to protect the original data from being tampered.
Know all about hashing here: https://www.audienceplay.com/blog/hashing/
Securing your data is as important as the data itself. So, implement these data security measures to protect it from any external or internal sources. Once the data is secure, there is no question of turning back. You are ready to monetize your data.
In this data-driven world, any information you gather can accelerate your economic growth. The trick is to utilize it efficiently. Your customer data is the key to your business’s success. Using that key to open the doors for new revenue streams will push your company to the top. However, you, as the owner of data, should learn how to monetize your data effectively.
Today, the data industry is one of the trending fields that has a great future. Hence, all sorts of businesses are venturing into data market. So, don’t let your data go waste, begin to monetize your data today.
Our guide will surely enlighten you about the importance of customer data monetization. What are you waiting for? It’s your chance to make it big in the data industry. Venture into data monetization and see what it can do for you!