Increasing mobile revenue share through big data-based pricing

25 April 2016 | Strategy


"Premium subscribers account for a disproportionate share of revenue – identifying these customers and tailoring tariffs to their needs using established quantitative processes are key to increasing revenue share."

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MNOs are putting increased emphasis on share of revenue rather than subscribers

As mobile penetration in most markets is approaching saturation, MNOs are increasingly focusing on premium subscribers and revenue market share rather than all subscribers and subscriber market share. This reflects the fact that premium subscribers constitute a disproportionate share of revenue, with the top 20% of subscribers making up 40% of revenue (as shown in Figure 1a).

In its pricing work for MNOs, Analysys Mason adopts a usage-based segmentation approach to understand the voice and data consumption patterns of different customers. Usage-based segmentation also can be displayed as a revenue heat map (Figure 1b), showing the concentration of revenue (rather than subscribers) for different types of usage. The following conclusions can be drawn from Figure 1 (taken from a client project):

  • There is no linear relationship between voice and data usage for most users and so MNOs need to consider both voice- and data-led tariff propositions
  • Revenue is highly concentrated among users who still make significant usage of voice. This implies that voice is still a key differentiator in pricing for certain segments
  • Data-centric customers generate significant revenue, but while data abusers contribute just 5% of overall revenue they generate 40% of total data traffic. The key driver of data traffic is video. This implies a need to improve how data profitability is managed and define data plans based on types of video content consumed, not just the size of data bundles
  • There is a long tail of customers, each generating relatively low revenue. This highlights the need to offer flexible pricing that caters to vastly differing requirements, but presented in a straightforward way that users can easily understand.

Figure 1: Understanding usage behaviour and revenue concentration among premium subscribers [Source: Analysys Mason client project, 2015]

Figure 1: Understanding usage behaviour and revenue concentration among premium subscribers [Source: Analysys Mason client project, 2015]

There are three main ways to increase perceived value for premium customers as part of the core tariff plan

There is an increasing trend for MNOs to offer shared plans, such as family shared plans (where the main account shares voice/data allowances with family members) or individual shared plans (where a single number is shared by multiple devices). However, MNOs must ensure that the core tariff plan for the main account holder provides the best possible value. As the world becomes increasingly data focused, there are three main approaches for creating the core tariff plan:

  • “Unlimited Voice / SMS”: Also referred to as data-led pricing, this has been widely used in developed markets for several years. One recent successful unlimited voice plan in a middle-income market is the MaxisONE plan in Malaysia, whose users now contribute 50% of Maxis’s postpaid revenue. Such a plan is effective in addressing premium users for whom voice usage is still important. With voice and SMS traffic now declining in all markets, however, there is a small window of opportunity for launching such a plan. The key challenge when designing such a plan is the careful management of margin cannibalisation from high voice users.
  • “Flat-/zero-rate curated OTT content”: Video content is a key driver of data traffic, but to date this has generally been non-curated content from independent sites like YouTube. MNOs are now starting to offer high-quality curated content through their own video portals/apps and increasing their revenue market share by providing flat-/zero-rated OTT content to users as part of a premium bundled mobile content plan. LG Uplus in Korea is a good example of a bundled mobile content plan, which has enabled a 6% increase in revenue market share, primarily through the acquisition of high-ARPU subscribers. However, data usage among these customers can be twice that of an average user. Key challenges when launching such a plan are to identify appropriate content, ensure that fixed content costs are recovered, and achieve profitable growth in data usage.  
  • “Customisation / control to the user”: Tariff plans which allow users to select their own combination of voice/SMS/data have the dual objectives of offering greater value to the long tail of customers who make a small revenue contribution and providing an attractive way for high-value prepaid users to migrate to postpaid / fixed monthly commitment tariffs. For example, when Vivo in Brazil targeted its Controle tariff plan at high-value prepaid users, it successfully increased its postpaid user base from 24% in 2012 to 36% at the end of 2015.

Data analytics is needed to maximise benefits and minimise risk

Pricing in today’s data world requires a combination of skills – an understanding of network requirements to manage growth in data traffic, usage-based segmentation, and awareness of OTT content requirements. A particular challenge is the need to manage margin risk when transitioning users to a new pricing model – due to voice cannibalisation, data profitability of flat-rate OTT content, and loss of ARPU through customisation. A highly quantitative approach based on big data is therefore crucial to the design of tariff plans. 

Analysys Mason works collaboratively with clients to help them optimise pricing through problem identification, process support, data analytics and idea generation. In a recent project with an MNO, we advised on changes to prepaid plans which led to revenue growth of around 3% over two quarters.