2014/11/19 Pricing for data profitability: usage-based segmentation can identify profit drains

A problem facing mobile operators is that a small proportion of subscribers consume a disproportionately large proportion of data. Analysys Mason has undertaken a detailed assessment of data profitability based on detailed CDRs for an operator in South-East Asia. Our assessment found that the 5% of subscribers with the heaviest data usage use 30% of total network data consumed, but contribute only 6.5% of revenue and a mere 1% of overall margins (defined as revenue less network costs and subsidies), as illustrated in Figure 1. The cumulative margin line has points of decrease indicating unprofitable users in all usage segments. Notably, these are not only in high data usage segments, as is generally believed.

Figure 1: Distribution of data usage, revenue and margin, South-East Asian operator [Source: Analysys Mason, 2014]

Usage-based segment heat maps can identify profit drains

Usage-based segment heat maps provide an overview of the level of profitability for different customer segments, as illustrated in Figure 2. Typically, higher-ARPU customers provide higher margins, although some lower-ARPU segments can also be highly profitable (these tend to be voice-centric users). However, in order to manage data profitability, operators need to assess how best to manage the profit drains – that is, segments that have negative margins – and how to improve margins for the low-margin users. In the example shown in Figure 2, just eliminating negative margin users will improve total margins by 2.2% even though revenue will decline by 3%.

Figure 2: Customer segment margin heat map (after network costs/subsidies), South-East Asian operator [Source: Analysys Mason, 2014]

Managing segment profitability can ensure profitable data growth in three ways

Usage segmentation will provide operators with the basis for ensuring three key areas of profitable data growth.

• Eliminating subscribers who appear to be profit drains, based on heat maps. A time-of-day usage assessment for profit drains can provide significant additional analysis.
• Reduction of subsidies or promotions for unprofitable customers. A customer lifetime value assessment needs to be carried out after usage segmentation.
• Improving margins for existing customers. This could be achieved by setting tiers for data bundles based on growth of data usage by segment.