Until recently, tariff optimisation has been little more than a pipedream for telcos. Now, however, mobile companies can use advanced analytics to ensure optimal pricing of their different service offerings and achieve that fine balance between breaking even on each customer, and pricing themselves out of the market
"More companies are beginning to use business intelligence technologies to optimise tariffs," says Bruce Jones, General Manager: Commercial Sector of SAS SA, leader in business intelligence. "This ensures prices are set at correct levels that result in increased profits and customer retention."
The first step in tariff optimisation is to determine the cost of customers to the telco. The organisation must perform activity-based costing, per customer, a process best achieved using business intelligence technology with proven analytical power.
Having determined actual customer costs, the telco then needs to calculate ideal tariffs. This involves consideration of a number of issues. Firstly, the minimum that each customer should be charged is equal to the true cost of that customer.
"This could be extended to say that the minimum to be charged is equal to the cost plus a fair mark-up," says Jones. The maximum that can be charged relates to what the market will bear, which, according to Jones is a simple statement, but one which is not so simple to put into practice.
The first step in establishing what the market would bear is to segment customers into 'like-minded' groups. This is achieved by applying data mining techniques to as many variables per customer, and on as many customer records, as possible. If performed properly, groupings of customers with similar usage and behavioural patterns, or 'like-minded' customers, will emerge.
To then establish what prices the market will bear, the telco needs to perform market research into what proportion of a 'like-minded' population would take up tariff offers at different levels of fees and offerings, such as free minutes. The market research would have to take competitive offerings into account as well.
Once the results of this market research were available, the telco would embark on scenario planning.
"It would need to see where total volumes - or the number of users multiplied by income per user - per 'like-minded' population are maximised," says Jones. "The higher the tariffs, the fewer the users, and the lower the tariffs, the higher the number of users. Tariffs are optimal at the point at which the graph of total income peaks."
Optimised tariffs are therefore a function of:
* The true costs of 'like-minded' customers; and
* Maximised revenues from the same group of customers (which is a function of tariff versus value)
"SAS can provide the technology required to make this task less onerous than it sounds," concludes Jones.
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