There has been a lot of recent discussion on how mobile operators can look at different ways of pricing mobile data rather than continuing to use the traditional per MB/GB consumption model. There is a general consensus that this model is not sustainable long term from an economic standpoint. With the average data consumption per user ever increasing primarily due to more capable devices and the proliferation of mobile video, operators have limited options available to them apart from increasing allowances to sustain the data plan price point and stay ahead of the competition. This approach, however, is essentially a race to the bottom.
When looking at available data pricing options to adopt it is important to take a wider view of general consumer spending trends that are emerging and models form other industries that have proven to be successful. Consumers are increasingly moving toward an economy where small but frequent “one–off” transactions are more appealing rather than making larger scale purchases with commitments. This may be attributed to the economic downturn where consumers now want to be more in control of what they spend. We do not have to look far to see evidence of this model working effectively:
Users are happier to purchase songs from iTunes at 99 cents apiece rather than buying a whole album for $15-20 USD
In-App purchases for 99 cents have a high probability of uptake because the price point and conditions are right to ensure compulsive buying
Even higher end items such as expensive cars and bikes are now being offered on a pay-as-you go per hour rental basis
Or gym memberships are moving from the traditional 12-month location-specific contract to a use anywhere pay-as-you go basis.
So the obvious question is why not adopt a similar model in mobile data pricing? The message to the mobile data consumer then changes from “buy a 1GB monthly bucket for $29.99” to “buy what you want when you want.”
Let’s look at this statement more closely.
Firstly, the consumer needs to understand what they are purchasing. To date in mobile data the “what” has typically been in terms of MBs or GBs, and I think we can all agree that the average consumer has no idea how this maps to what services and content they access when online. However, consumers do understand the concepts of time and service so why not sell data in this way? For example rather than increasing the MB/GB allowance in a typical data plan to cover the growing consumption of video, why not instead sell the consumer a basic plan with some restrictions at a lower price and then give them the option to buy services such as video on demand in various time buckets and price points (e.g. 2 hours video for $4.99, 10 hours for $9.99 or 30 days for $19.99)? The same model could be applied to other premium data sensitive services such as roaming or device tethering.
Secondly, when and how often you engage the consumer is important to increase the probability of uptake. Following on from the above example, if the operator randomly offers the consumer the ability to buy video by the hour or expects them to find out about it themselves by going to their portal, then the relevance of the offer is lost and the likelihood of uptake is low. However, if the user is provided the same offer in line when they try to play a video and are restricted, then there is a much higher probability of uptake due to increased context. Today, mobile operators have the opportunity to look at consumer engagement models that are more proactive and context driven. OTT players such as Facebook and Apple have been very successful in adopting this model. The user is constantly kept up to date on the latest products and features. This not only covers service upsell cases as described above, but also ensures that the user is more aware of the data consumption and how much of their allocated allowance remains (especially when approaching any limits that may apply). This prevents the classic “bill shock” scenarios from occurring and provides much greater transparency. Aspects such as self-care also put the consumer at ease as they feel more in control of their data spend and can allow them to perform a top up or purchase a service on demand.
Here are a few advantages of this new model for selling mobile data:
Users are happier because they have better control over their data spend
Increased transparency and understanding for how users consume data
Operators are happy because they now have new vectors in the form of time and services to more strategically price data other than just selling buckets of MB/GBs
New ways of engaging the user which will immediately lead to net new revenue streams and greater brand awareness.
As a closing analogy, imagine the mobile web ecosystem today as being one large shopping mall. The consumer has brand awareness of big stores at this mall – the Googles, Apples, Amazons, Facebooks of this new world, and is likely to visit those stores. Even if the operator has their own store at the mall they are not likely to get much foot traffic, since they have minimal brand awareness among consumers. The operator instead is simply regarded as the highway to the mall (the pipe). They could decide to charge a toll purely for access to their highway, but there will always be alternative routes available to get there. They could instead offer the user a choice to pay a premium to use a fast lane or toll free at off peak times (think of tiered pricing and QOS based pricing). But they could also present billboards that they own along the route to make the user aware of promotions and special offers relating to specific stores at the mall, which the user is thus more likely to visit. Thus the savvy mobile operator can exploit their proximity to the consumer and their ability to significantly influence his/her final destination in order to levy sponsorship from the (OTT) stores at the mall.
This analogy is part of an emerging new consumer economy and closer to reality than we might think. The necessity to consider these new revenues models is here and now.