We explore the future of customer data monetization for mobile operators, from advertising, to sophisticated customer engagement and adjacent revenue growth.

The Future of Customer Data Monetisation

By Mike Greening & Tim Heal

Customer data monetisation business models are still in the early stages. Mobile operators are currently working to understand how data monetisation can both support the core business and bring in adjacent revenues. In this viewpoint we set out a vision for the next level of data monetisation, in which MNOs use customer data to strategically reposition themselves to capture adjacent revenues.


In response to downward pressure on revenues and margins, mobile operators around the world have been considering revenue opportunities in areas adjacent to their core businesses, such as mobile advertising, applications, mHealth and M2M, and less commonly, in more distant areas such as electricity and gas, home and travel insurance, or consumer electronics hardware.

 “Data monetisation” is an umbrella term which covers the additional revenue that an operator can generate from the information it holds on its customers. Monetisation can be internal to the operator’s business, via upselling services, reducing churn and supporting customer care. It can also be external, providing intelligence to support commercial opportunities such as mobile advertising, or through packaging and selling the data for insight.

Last year, Cartesian discussed opportunities in data monetisation for operators.[1] To date, customer data monetisation has focussed on two areas: mobile advertising, and customer insight and upselling. We now see a greater potential for operators to leverage customer data: he next level of data monetisation will help enable operators to strategically reposition themselves and to generate adjacent revenues and profits that are meaningful in comparison to those of the core business.

Current Situation


Operators face a number of challenges in securing future profitability. ARPUs are falling in most developed markets or are flat in others. Revenues from data (handset and mobile broadband) have partially mitigated the shortfall in voice, but overall revenues and margins are trending downwards.

The move to LTE continues to drain operator cash reserves, both in terms of rolling out across the network, and in bidding for spectrum. While some players (notably EE in the UK) have put a stake in the ground to charge a premium for LTE services, prices will continue to face competitive pressure.

Regulators are also continuing to maintain or strengthen the competitive environment for telecoms services, notably seen in falls in mobile termination and wholesale access rates across Europe.

Figure 1: Global ARPU Trends (US Dollars)

Global ARPU Trends (US Dollars)

The so-called “over-the-top” threat from Apple, Google, Facebook, Skype, Whatsapp, and many other providers continues to grow, and operators have struggled to claim their share of OTT revenue.

Operators have started to make investments in adjacent areas such as mobile advertising, online TV, M2M and mHealth, and some have set up business units to explore wider opportunities (e.g. Telefonica Digital, Orange Horizons, Telenor Innovation, SingTel’s Digital Life, etc.). However, adjacent revenues to date have been insufficient to offset declines in the core business, and thus operators have focussed on cost reduction to maintain margin performance.

Strategic Assets

Despite all of these challenges, operators possess unique strategic assets which will help secure their continued relevance and success:

  1. Retail relationships with millions of customers. According to the GSMA there are now more than 3 billion unique mobile users in the world, and more than 6 billion mobile subscriptions.
  2. A variety of tools and channels to communicate with their customers, including SMS, mobile portals, applications, the handset, TV for MSOs and of course email and traditional contact centres.
  3. Direct and trusted billing relationships with customers.
  4. Access to a huge amount of customer data, including personal profile data; network data such as location and travel patterns; data from value added services such as mobile content consumption, email and social media usage, app usage, as well as financial information such as monthly phone spend.

Data Monetisation Today

Data monetisation for most operators has to date meant the leveraging of the fourth strategic asset: mining and analysing the customer data, selling insights, and pushing targeted ads to customers.

O2 UK is a key player. Its O2 More platform takes in customer information, such as basic profile data, network location, and customer preferences, and serves up targeted advertising to customers via SMS and rich media messaging. O2 More uses a standard advertising CPM model, with targeted SMS costing about 15 eurocents. The platform has now reached 10 million users, half of O2’s UK total base.

Other operators have invested in advertising. In the summer of 2011, AT&T re-launched its advertising business as AT&T AdWorks, declaring a tighter focus on the targeted advertising business. Most recently, AdWorks has been experimenting with using online targeting models in the TV world; analysis of a customer’s viewing patterns (when they change channel, adjust the volume etc.) against what is being played out, can yield valuable insight data.

Some operators, including Sprint & Telefonica, have formed partnerships to address the opportunity in data monetisation. In February this year, the two operators announced a global mobile advertising alliance, which would enable brands to reach more than 370 million mobile customers across the US, Europe and Latin America with targeted and consumer controlled advertising.

More recently, the UK operators EE, O2 and Vodafone have formed a mobile marketing and wallet joint venture called Weve which provides brands access to 80% of UK mobile subscribers via a single mCommerce platform. Weve will be an integrated platform, offering simple and rich media messaging, application-based promotions, voucher and loyalty scheme functionality, and payments.

Operators are just beginning their journey in data monetisation, with most efforts so far focussed on either targeted advertising (controlled and targeted advertising), and supporting business customers in making informed business decisions. To date, almost all of these initiatives have adopted a B2B approach with the interests of the end consumer being almost secondary.

Across the board, operators are currently exploring new technologies to dynamically extract and manage customer data. Commercial and operational models are evolving towards two objectives: to maximise incremental revenue, and to attract customers over traditional and trusted insight and advertising solutions. We believe that the more significant opportunity for operators is to enable direct adjacent revenue capture.

The Future of Data Monetisation

There is an opportunity for the operators to grow their relationships with the consumer and to serve their needs beyond communications. In focussing on the benefits for the consumer, operators will drive long term engagement and adjacent revenue growth.

First, the volume of data that is collected needs to be increased and managed in real-time. Insights can be drawn from data held in operator legacy systems. By developing an extraction layer that can interface with multiple legacy systems, operators can collect vast amounts of data on their customers, expanding beyond typical profile data, location, and spending, to using deep packet inspection on mobile internet traffic.

These data should be aggregated in single repository to form a central location for all information on the customer, which should update in real-time. External data such as social media usage, weather, news, currency movements, etc. should also be fed into the platform. Operators must analyse this data themselves, rather than just selling the data to 3rd parties. New Big Data technologies can solve the volume – variety – velocity - visualisation challenges of data analysis. Operators should now bring these capabilities in-house to micro-segment their customer base.

Figure 2: Sources of Data

Data Monetization - Sources of Data

A new focus for data monetisation should be consumer engagement. Operators will maximise adjacent revenues by developing extensive engagement with their consumers.

To start with, customers can be engaged through a platform (e.g. downloaded application, internet application, or mobile website), where relevant services, offers or rewards can be shared in return for even more data. For example, by providing a personalised portal page containing integrated calendar, aggregated inbox and social media feeds, operators could collect a huge amount of highly useful data. This portal would also serve as the platform for offers and recommendations for loyalty, commerce or third party products, which would be centred on each customer’s profile. Relevancy and response rates should be monitored, and the customer must be able to customise type and frequency of outreach.

With these capabilities and these platforms, operators can move up the value chain, fully leveraging the superiority of their technology to justify direct adjacent revenue capture.

Currently, operators have no or little visibility on the subsequent purchases in response to targeted advertising for 3rd parties. Because of this, operators need to recruit a set of partners willing to enter a wholesale or commission-based relationship, where the customer can buy the product or service through the operator. The solution should enable the operator to capture a share of revenue from goods sold, or to receive a commission from the partner based on the expected lifetime value of the customer (such LTV commission models are already being used in app stores). In order to succeed, the platform must provide a “frictionless” payment, e.g. adding the purchase to the monthly bill, paying with prepaid credit, or paying with a linked instrument such as a debit or credit card, or PayPal.

The vision for data monetisation thus combines the operator assets of customers, communications tools, billing and customer data, to allow the operator to accomplish the following:

  1. Be the single aggregator of real-time customer intelligence and predict customer needs
  2. Drive relevancy and response rates up beyond traditional advertising
  3. Engage directly with the consumer rather than handing over to the brand partner
  4. Create a business model that allows cross-selling outside of telecoms, thereby increasing share of wallet in the customer’s wider spending
  5. Share directly in the success of its own analytics and recommendation engine

Supporting This Vision

This vision is part of a longer journey in customer data monetisation for operators, starting with efforts to more intelligently upsell to their own base, moving through basic and more targeted advertising, and recommendations, and ending with an end to end platform that can allow operators to increase engagement and capture revenue share. In mature markets, telecoms spend accounts for less than 4% of a consumer’s total monthly disposable income. A growing number of operators believe that there is considerable opportunity for them to expand their share of wallet.

Figure 3: Evolution of Data Monetisation

Evolution of Data Monetisation

Cross-Selling Examples

This is, of course, a form of cross-selling. While it could be argued that telecoms companies have not been successful in this area, there are several well established examples across industry sectors, including telecoms, to support the hypothesis that operators can capture sizable adjacent revenues.

Reasons for cross-selling vary: in some cases, the primary objective is customer retention (e.g. Magyar Telecom, which bundles utilities with its core telecoms services); in others it is about improving brand perception (e.g. Sainsbury’s efforts to improve its green credentials); while in others the objective is to diversify and add incremental revenue streams (e.g. postal organisations, such as the UK Post Office).

Figure 4: Cross-Selling Examples 

Data Monetization - Cross-Selling Examples

Trends and Drivers

With consumers continuing to spend more time using their mobile devices, one of the key trends supporting this vision is the mobilisation of commerce and purchasing. eBay reported that 16% of its gross merchandise value was sold through mobile. Forrester has predicted that over the next five years, total mobile sales in the US are expected to grow annually at 33% to reach $31B in 2017, making up 9% of all online sales. Google reported 29% of its smartphone users engaging in mCommerce in 2011, increasing to 35% in 2012.

Mobile has also demonstrated high relevancy in advertising. O2 More has response rates of up to 35% for some campaigns. However, mobile advertising response rates usually only reach these levels when customers are being offered something for free or at a highly discounted rate via a coupon. Mobile advertising is also predicted to grow at 34% annually until 2016, faster than online advertising at 15% and traditional advertising at 2-7%.[2]

Benefits and Risks

The benefits to an operator which can pull this vision off are manifold.

Firstly, increased insight into an operator’s own customer base will help in driving core ARPU uplift and retention initiatives. Secondly, by centralising the intelligence in its own platform, an operator can prevent marginalisation from its customers by other players in the value chain, enabling it to shift away from the “dumb pipe” scenario. Thirdly, increased customer engagement from owning the end to end experience should provide clear financial benefits as the operator promotes and captures adjacent revenue streams, ensuring operators mitigate downward pressures in the core business.

Such an ambitious strategy is of course not without risks. Key potential pitfalls include the following:

  • Technology: Complexity of data extraction from legacy systems; accuracy of analytics engine
  • Regulatory: Attention, scrutiny and intervention, especially around deep packet inspection
  • Partner: Lack of interest; fear of lack of control; unpopularity of wholesale model
  • Customer: Insufficient adoption of platform (whether opt-in or opt-out); lack of engagement; lack of willingness to buy through operator; adverse impact on customer experience
  • Internal buy-in: Resistance in moving away from the core business, near-term negative impact on overall margins and low mind share versus other priorities
  • Right to play: Ability to compete for share of revenue alongside established players such as Amazon, Google, Facebook, etc.
  • Financial: Excessive platform cost; inability to directly capture certain types of consumer spending (e.g. mortgage payments, supermarket shopping in-store, car purchase, etc.)

What Next?

There are a number of immediate next steps for operators considering the opportunity in evolving to the next level of data monetisation:

  1. Investigate the technology. A number of specialist vendors provide solutions to extract and analyse data, advertise or make recommendations to customers, and integrate retail partners.

Figure 5: Example Ecosystem Vendors

Data Monetization - Example Ecosystem Vendors

  1. Begin conversations with strategic partners. Understand the appetite of big brands and businesses to enter into wholesale or commission based models.
  2. Define the objective. Does the data monetisation initiative support adjacent revenue uplift or is about driving an uplift in customer acquisition or retention.
  3. Determine the priority diversification areas where operators have a right to play, can successfully leverage internal data for increased relevancy, and can provide a significant new revenue stream.
  4. For multi service operators, understand how to optimise data collection and targeting across their different service lines (mobile, fixed and TV).
  5. Understand customer engagement. Survey customer appetite for a new promotions / offers platform, and comfort with paying for products and services through the operator.
  6. Do the business case. How much will this cost to set up? How much spend can be captured or redirected? Is this enough to justify the investment or prioritise versus other initiatives?
  7. Define the optimal operational model to run the business. Should it be set-up and run in a test bed environment through a separate subsidiary or sub-brand?
  8. Understand the competition, both from mobile, internet and data analytics players.

Cartesian has supported operators in a wide range of projects concerning data monetisation, adjacent revenue capture and revenue growth strategy. Key areas of expertise include market opportunity and business case development, competitor evaluation, proposition design, technology and vendor assessment, partnership strategy, as well as overall go to market launch support.


[1] http://www.tmng.com/knowledge-center/insights/data-monetization-leveraging-subscriber-data-to-create-new-opportunities

[2] PwC Entertainment and Media Outlook, 2012-2016