The emerging discussion in the communications industry is how we get beyond data. Pricing data per megabyte, for example, does not make sense. Customers (even those who work in the communications industry) cannot tell you how much data a video consumes. Even an engineer would ask you technical questions about quality, jitter and who knows what. Uncertainty and lack of clarity brings only mistrust. And mistrust is exactly what customers do not want from their service providers.
The good news is that there are more and more examples of data pricing that bring with them a degree of clarity.
The latest compilation, from Comptel and tefficient comes in the shape of a ‘top ten’ clearest data plans. While some of these do not actually make the data usage itself clearer to understand, it validates some of the other discussions on this subject.
The first two or three that the slide show looks at are about sharing data, either with other devices on a single account or shared data amongst groups. Other, more sophisticated ideas look at sponsored data, free apps for a limited period and ad funded data.
Whilst these all go some way toward the goal of clarity in data, there are some flaws that need to be discussed. Mainly these concern the ‘freemium’ trap.
Ad funded data, for example, is all very well, but most customers do not have the time or patience to watch a 40 second advert before using data. And, how do you measure whether a customer is actually watching the advert or making a cup of tea? Free apps for a limited time are also a development in the right direction but a significant percentage of customers (the same breed who covertly used SMS for free in the early days) will take advantage of the free offer and not migrate to paid options, instead bouncing from free offers and then from WiFi to WiFi.
These examples are welcome and will hopefully help us avoid the traps associated with unclear pricing and mystical charging. Some operators have certainly got to the point of pricing voice and texts as commodities but they need to avoid similar traps with data.
Interestingly, with this set of slides, there is also an indication of how difficult each idea is to implement, how difficult it is for competitors to copy and what the differentiation potential is likely to be.
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