Decoding Data Monetisation

Organisations today are generating large amounts of data, and many have started realizing that there are several non-traditional ways of utilizing this data to create measurable economic benefits for the company. Data monetisation is all about generating new revenue streams using data-driven products, either indirectly, by extracting actionable insights from big data to improve the overall performance of the business, or directly, through the sale of insights and data to third parties. Whichever way is more feasible for an organization, monetisation depends solely on the available data being valuable. It must be unique and actionable for the buyer, or it should be de-duplicated and cleansed for maximum data quality.

Data is one of the most valuable assets an organization has today. Still, in order to optimize data value and establish new revenue streams, it is essential first to develop a relevant strategy for data monetisation.

What is a Data Monetisation Strategy?

Implementing improper techniques for data monetisation without proper strategy and compliance in place can attract hefty fines, increase cybersecurity risks, and deal a blow to the organization’s reputation that may not be the easiest to get over. Regardless of whether it is done for optimizing overall operations and performance or to generate revenue from insight sales, having an effective data monetisation strategy in place is of prime importance. The top aspects of your data monetisation strategy should cover:

•    Optimised extraction of insights from big data.
•    Roadmap for the establishment of a solid IT infrastructure with provisions for a centralized data store, advanced analytics, and relevant Business Intelligence tools.
•    Analysing legal risks, data protection barriers, problems of data availability, competitive barriers, data delivery methods, etc.
•    Defining the physical, technical, and logistical conditions for transforming expansive datasets into new revenue streams.
•    Change management to ensure enterprise-wide adaption of the data-driven business model.

Types of Data Monetisation

Getting started with data monetisation does not mean that you start turning over the data you have to third parties. There are several approaches for utilizing data, which can broadly be classified into two categories – direct data monetisation and indirect data monetisation.

Direct Data Monetisation

More than simply selling raw data to third parties, direct data monetisation encompasses much more. The term direct here refers to the direct conversion of data into revenue. While you can consider selling raw data, there are a lot of complexities related to data privacy that you must contend with. A thorough understanding of the policies and legal requirements for the sale and exchange of data, not only for India but for every country where you plan to monetize data directly. Data privacy has taken center stage in recent times, and even a small breach can be extremely detrimental to your reputation.

You will find companies that are ready to buy big data for big bucks but that doesn’t mean you need to sell all your data to them. Based on their requirements, you can provide these businesses access to select data segments or to your analytical insights gleaned from the data.

Direct data monetisation creates a new revenue stream for your business and once you have analyzed what data you want to sell and to whom, you must now deliberate on the ‘how’. How will you deliver the data? Some of the commonly opted-for options in direct data monetisation include:

• API Creation: A popular delivery option is developing an application that enables customers to access your data through internal APIs. You can also develop external APIs to allow third-party software interactions with your data, where you retain control over what data is accessible.
• Direct Sales: Big data can be licensed for use by other businesses, or you can opt to sell your data through brokers. The data here can be pre-segmented or raw.
• Selling Analytics and Insights: Businesses can benefit more from data that has already been analyzed as compared to raw data. Here, data monetisation can also include subscription services for analytics reports.
• Data Trading: Another way to utilize data is by trading it to obtain benefits for your business or your clients. For example, you can barter select data insights for free services or favorable terms for your customer base.

Indirect Data Monetisation

Sometimes, businesses have enough data, but the data may be too valuable to sell to third parties. While that does eliminate direct data monetisation as an option, data can act as a strategic asset, helping you get deeper customer insights and recognize new opportunities for revenue generation. This is indirect data monetisation, where you can harness the insights provided by the data to affect changes that generate a quantifiable impact. Indirect monetisation can help transform analytics from an expense to an investment. It enables companies to optimize operations, reduce costs, and enhance revenues, which indirectly monetizes data.

Some popular ways of indirect data monetisation include:

• Identify New Customer Segments or Business Categories: Data can offer you insight regarding customer segments, which are not among your target customers at present but might benefit from your products or services.

• New Service/Product/Market Development: Identify gaps in the market, discover end-customer needs that have not yet been addressed, and utilise the knowledge to back the launch of new services or products or to even expand your reach into a new market.

• Enhance Your Offerings: Find out about the secondary problems that your customers generally face and work towards solving them by making targeted enhancements in your service or product, whether it is about a price adjustment or something as simple as adding a ‘Similar Products’ recommendation section on your website.

• Optimise Costs: Data analytics can provide you with the information you need to understand where you can cut costs by streamlining your overall operations. This can include tasks like reducing unnecessary inventory, upgrading worn out business tools, etc.

• Improve Efficiency: Data insights will help you monitor the efficiency and productivity of your employees, processes, and operations, which will help you optimise the allocation of resources.

Get Your Business Ready for Data Monetisation

Data monetisation has a lot to offer. However, before organisations may begin their journey to monetize data there are several key aspects that they need to take care of first to ensure they can get the maximum value out of their data.

Data Evaluation: Before you can start monetizing your data, you need to understand what data you have, its applications, and what value it holds for relevant buyers. A basic analysis of your dataset to identify its format and type, and to determine its potential monetary value must be performed.

Optimize Your Data with Metadata: Business data has a lot of information that may be gleaned but given the sheer amounts of data that are available today, it can get quite arduous for potential buyers to find what they are looking for. This is where metadata comes in. Metadata gives meaning to the information and includes information about your data, like its quality, language, theme, description, etc., making it easier for customers to search for relevant datasets. Metadata is crucial for data monetisation, and a comprehensive metadata framework to map concepts must be developed.

Opportunity Identification: Some market research is required to determine what your prospective data buyers need. Understand where, why, and how your customers need data, so you can structure your data monetisation strategy around it.

Have an IT Infrastructure in Place: Rather than trying to adapt your new data monetisation strategy to the existing infrastructure, build a dedicated IT infrastructure to suit data monetisation requirements. This can help avoid issues with bandwidth, data storage, and security as well as processing needs, and ensure that you have a data environment that is secure, governable, accessible, and scalable.

Shape a booming data monetisation strategy mining digital gold. We can help you collect, correlate, and blend your data, with actionable insights. Utilize our expertise in enterprise data architecture optimisation for flawless data monetisation. Let’s talk

Ankur has 9+ years of exp. with Big Data and AWS Technologies in various domains (Banking, Telecom, Mobile Panel, US Survey, Click Streaming and Data Streaming, Cookie Panel Data, Google -Adwords and Analytics for Digital Marketing, Television Media, Logistic Industry) for Data Warehouse and Product Development.