The two routes to big data monetisation in telecoms

big data monetisation in telecoms

It is no secret that profits in the telecoms industry have taken a hit in recent years. So the promise of new revenues through big data monetisation is a welcome one. Over the past 12 months the big data monetisation hype has transformed from talk to action, and two clear routes to big data monetisation have now emerged:

1. Internal big data monetisation: up-sell through operational insights

2. External big data monetisation: new revenue through the sale of insight packages

In this blog we take a deeper look at these two routes to big data monetisation, exploring how they work and their potential impact on the telecoms industry.


Big data monetization through internal operational insights

Telecoms operators collect massive amounts of data on a daily basis. This data can include call details such as time of call, duration and destination, as well as network data such as faulty equipment, black spots and call quality metrics. Unfortunately, for many operators this data is either not used at all, or is used in isolation for one specific purpose such as billing, or network maintenance.

However, operators are now realising the potential in this data, and are introducing new ways to monetise this through internal operational insights. The combination of both customer data and network data can be used to not only improve customer satisfaction and retention, but also identify new upsell opportunities to increase subscriber value.

One example of this is identifying up-sell opportunities by analysing subscribers network performance versus subscriber satisfaction. If a subscriber in in an area of good coverage and quality, yet is reporting a poor performance, this can be indicative of an external issue affecting their performance. Telecoms operators can investigate this and identify new up-sell opportunities such as a new handset upgrade or a home small-cell.

Pros of internal big data monetisation in telecoms

  • Operators can increase revenue per subscriber through new up-sell opportunities.
  • Operators can improve customer satisfaction and retention.
  • There is no red-tape to overcome.

Cons of internal big data monetisation in telecoms

  • Operational changes are required to adapt to using big data in a new way.
  • Revenue growth via this method is limited primarily to existing subscribers.


Big data monetisation through the external sale of insight packages

Data monetisation through the sale of data insights is not a new concept. If you have ever used a comparison site for your car insurance, then you will know when it’s time to renew, by the countless emails you receive from providers you have never even heard of. In this example, the comparison site has monetised data by selling contact information, vehicle details and renewal timelines.

In the telecoms industry, this concept is being explored as a new revenue stream, of course with much tighter regulation and security. It can be split into two branches, macro data insights and micro data insights. An example of monetising macro data insights can be found in the tourism sector. Telecoms operators have immense insight into human behaviour from their subscribers’ mobile phone use. They can anonymise and aggregate this data to see key trends such as subscriber waking hours or typical movements around a city. These insights can also be segmented into age groups, genders, tourist vs. locals etc. This can provide major insights for tourism businesses to act upon. For example, a tour bus company can increase customers by positioning booking stations in areas with high tourist footfall at certain times of the day. This type of information can also prove useful for local governments. They can monitor the movement of people to support the planning of new developments and transport links.

Another avenue currently being explored is the monetisation of micro insights. In this scenario, retail outlets can work with telecoms operators to place targeted advertising via mobile devices when in the proximity of a store. For example, when a subscriber enters a shopping centre, they can be sent an SMS with a discount voucher for a coffee shop in the venue.

Pros of external big data monetisation in telecoms

  • Operators can introduce new revenue from an entirely new customer base.
  • There is massive opportunity for continual growth through new industries and uses of data insights.

Cons of external big data monetisation in telecoms

  • Operators must comply with industry regulations, which will require deep exploration and understanding.
  • New tools are required to create data insights packages.