Even when such data is reasonably accessible, reaching an accurate understanding of the situation is not always straightforward.
In today’s aggressively competitive telecoms markets, an attractive and balanced product portfolio is absolutely vital. Ensuring the efficiency of product portfolios is a complicated balancing act, and one that is impossible without a complete understanding of the market dynamics, the internal sources of profitability, customers’ behaviour and future market trends.
This understanding can be gained by using appropriate analytical models, based on good-quality data and a carefully structured approach.
The models used to explore and understand the efficiency of a product portfolio depend upon company data, market data and international benchmarks. Even when such data is reasonably accessible, reaching an accurate understanding of the situation is not always straightforward: Operators must ensure that the most appropriate and valuable data is selected, and that its consistency is checked, before seeking to decipher the real meaning behind the figures.
For example, Figure 1 below presents the different sets of data that would allow an operator to understand the market dynamics when optimising its product portfolio. It should be noted that quantitative and qualitative factors need to be taken into account. Detailed analysis of the data can yield new insights into market behaviour and characteristics, competitors’ products and profitability of the operator’s own products and segments. Such insight is of fundamental importance in informing strategic decisions. The practical application of this is shown in the sample project outlined below, in which Analysys helped a mobile operator to optimise its product portfolio, increasing its prepaid ARPU by over 20%.
Figure 1: Market data required for understanding market dynamics (Source: Analysys)
First, during the data collection and processing phase, we identified various internal and external sources, and analysed any discrepancies between data sources, in order to obtain a clear understanding of which data should be taken as key performance indicators. In this case, we selected key indicators related to revenues, costs, profitability, pricing and market behaviour.
We then analysed the different sources of revenues and profitability in different subscriber segments, which allowed the identification of the strengths and weaknesses of the operator’s product portfolio. We were then able to optimise the portfolio by refining available products, introducing promotions and launching new products.
The final stage involved building a traffic and revenue forecasting model taking into account the characteristics of the fast-growing mobile market and uncertainties associated with market developments and changing customer behaviour. Our methodology included assessment of international benchmarks to back up assumptions on market developments. This involves conducting systematic cross-checks with a top-down macro-economic analysis, exploring a variety of forecasting methods and identifying the most appropriate option.
The successful application of this portfolio optimisation process can enable operators to anticipate future market development and to determine efficient future products that would optimise ARPU and margins.
More generally, Analysys has developed a series of analytical tools including:
- Analysys PriceManager, an analytical tool for rapid analysis of current tariff plan positioning and simulation of the impact of future propositions on revenues and margins
- forecasting models to estimate future usage, revenue and margins, that will help to determine appropriate products to be launched
- cost and profitability models to gain a clear understanding of a company’s cost and profitability structure.
Analysys’s analytical models have helped operators increasing revenues, margins and market positioning. As a result of our work operators have generally seen their ARPU increase by 4% to 8%.