There is money in data, and the market is set to grow rapidly. Everyone agrees on that. Despite its huge commercial potential, however, companies and consumers often find it difficult to define data monetisation in a precise way.
In essence, data monetisation involves repackaging a company’s own data and third party data so that they can be sold in some form to other customers. The data is organised in categories such as age, location, or gender. The purchasers are either end-users or data aggregators, which are companies that compile information from various databases for data processing, before reselling them. Private companies or governmental organisations ultimately use this information to obtain a more refined understanding of their customers’ behaviour. With this information, they boost the success rate of their policies or commercial decisions, and hence their overall performance.
Of all the companies that can monetise their data, the best positioned are telecom operators. To do so, they must take important strategic choices with regard to big data products, customer segments and pricing, and decide how they sell data and provide after-sales support.
Telecom operators have several natural advantages over their peers. The greatest is the breadth and quality of the information they possess. Due to their frequent interaction with customers, and near-continuous data on the whereabouts of phones, they hold richer information on customer profiles, locations, and communications usage than potential competitors such as over-the-top content providers.
There are three main ways to monetise data. The first way is through raw data. This could involve selling the raw, anonymized, information on its own, or after aggregating it with data purchased from such third parties as market research organisations or data analytics specialists. Alternatively, telecom operators can sell these data through online marketplaces or through an interface (application programming interfaces—APIs), which both allow the buyer to obtain specific information in the desired format.
The second way is by using applications. Telecom operators can provide a platform for third parties to host their own data and gain access to the operator’s information. Clients can then build their own applications on the platform to profit from these data, perhaps through the targeting and segmentation of subscribers. Telecom operators can also develop their own applications that manipulate the data and help clients accordingly. For example, relevant applications could enable public transport authorities to plan and manage their services based on real-time traffic information.
The third is to monetise data through providing analytics services. In this approach, telecom operators sell the services of their own specialist data scientists and consulting professionals to clients.
Many telecom operators throughout the world are already capitalising on the opportunities afforded by data monetization. For example, Singtel has used anonymised data on customer profile, behaviour, and location to help clients in Singapore identify the most productive positioning for their billboard adverts, and the most favourable timing of digital adverts for various products. Similarly, Telefonica has worked with retail operators to make the most of offerings and promotions in stores, and determine the optimum location for new branches.
In the GCC too, operators have started monetising their data. For example, STC and Zain are building big data analytics solutions to tackle specific use cases for other companies. As governments have placed big data at the heart of their modernisation agenda, big data’s impact on the regional economy and the opportunity for telecom operators are both only likely to grow.
For GCC telecom operators to seize this opportunity, they must each settle on the most appropriate way to monetise data, either selecting one particular path or a combination. Thus far, operators have tended to start by providing data APIs and developing applications to meet their clients’ specific commercial goals. However, some have branched out to become end-to-end service providers, offering a one-stop shop of raw data, solutions, and other services.
Before finalising their plans for data monetization, telecom operators must be able to answer a list of important questions regarding the value proposition, business model, and go-to-market strategy. What type of datasets should be offered? Should the data be sold directly to clients or to aggregators? Should a dedicated business unit be established for data monetization? What pricing system should be adopted? Which industries should be targeted? What type of sales and after sales channels should be used for the product?
The issue of privacy is crucial. This has been an ongoing discussion, especially given recent high profile data leakages from technology companies. So before any company, and specifically a telecom operator, takes advantage of the data monetisation opportunity, it must understand that consent and anonymity are at the heart of big data applications. For their part, telecom subscribers should be aware that their data are being gathered, and they must also approve the use of their data by third parties. Furthermore, data must be anonymised so that subscribers’ identities are concealed from third parties.
Once telecom operators have successfully grappled with these and other issues, they can then set about exploiting their natural advantages in monetising data, a commodity that is set to be increasingly valued throughout the GCC economy over the coming years.