There was, and still is, a perception that suggesting a more suitable tariff to customers, based on their usage patterns, is directly related to offering cheaper plans. And cheaper plans translate to less profitable plans. But do they really?
Even determining the profitability of a tariff plan is a major headache for most operators. Sure, one can determine the ARPU easily at a tariff level, but that doesn’t help when it comes to determining what tariffs are actually worth offering as an alternative to customers. However, well-crafted plans may provide better value to customers and also deliver better returns to the operator.
To do this with any level of accuracy would require a breakdown of all costs, including SG&A (Selling, General and Administrative expenses) and a percentage of network, IT and staff resources needed to deliver the service. How else could a tariff plan’s real worth be determined, and how could a decision be reached whether to retire a plan, shift people away from one or even modify it to generate better returns (where regulation allows)?
Where a plan is made up of products or services acquired from third parties, the cost element is obviously much easier to determine: it’s basically the cost price paid to the supplier and some onboarding costs.
We can see the benefits of tariff optimization to improve profitability but by far its most common use is as a service to promote customer loyalty. Some CSPs run the process for all or selected customers on a periodic basis. Reaching out through the bill cycle or by calling the customer and suggesting a more suitable tariff is widely regarded as positive customer engagement, but direct contact is also a costly option.
If we stick to the definition of tariff optimization as the process to ‘calculate the best available tariff offer for customers based on their current bill and future needs’, it must be the most effective way to keep customers, acquire customers and quickly build compelling new tariff propositions. It provides positive proof for customers of the best available deal for their current and future needs, based on highly accurate and credible matching of alternatives.
However, that all depends on understanding the profitability of a tariff plan in the first place, and even more important, assuring the profitability of a plan or product before it is launched.
Some operators are utilizing big data to determine this but unless their data scientists are well informed about all the components required to make an accurate assessment of customer or plan value, they could easily miss the mark. But for those working in revenue assurance, every aspect of the financials is monitored and examined carefully to check for leakage and abnormal usage that often indicates fraudulent activity.
It should come as no surprise that leading RA vendors were the first to recognize the value of the data they were processing. Shape, a product from one such vendor, WeDo Technologies, is able to analyze profitability at not only product or plan level, but also at customer level and needs no intricate implementation, big data repositories or data scientists to operate.
Applications like this add the extra dimension of helping to determine which customers should be approached with new services or bundles to get their profit levels up or should be dispensed with because they actually cost the business money. That may sound radical or extreme, but knowing the value of a customer also helps in determining what level of service they should be given.
By analyzing customers’ full usage patterns and even social presence, their true worth can be ascertained and not left to assumptions and guess work. For example, a customer that makes very few calls would normally be deemed low value, but if they are generating massive inbound calls from other networks, their net worth from terminating call revenue should be taken into account.
Similarly, if a customer is making and receiving calls to a large number of other customers in the network it could be an indication that they are an influencer and if they leave, a number of their social network may follow.
There are many other cases like these that can only be accurately determined with analysis of data that already exists but is not being utilized fully. Knowing your customers’ true value is the best way of determining how much value you should place on them.
Tony Poulos is a regular contributor to Telecom Asia and anchor for the Telecom Asia Video Channel
Full disclosure: Mr Poulos is Enterprise Business Assurance Market Strategist at WeDo Technologies
This article was first published on Telecom Asia May/June 2016 edition