Six degrees of mobile data plan innovation: capacity-based plans

In this seventh installment of the Six Degrees of Mobile Data Plan Innovation blog series, we look at capacity-based mobile data plans. With capacity-based plans, subscribers are encouraged to use the network when it has spare capacity or to pay a little bit more as the network nears its capacity. Mobile operators can use these plans to reduce network congestion, monetize peak-time data traffic, and better manage the investment required to address continually growing demand for data.

Fast-rising mobile data traffic – driven by increasing consumption of real-time entertainment on the go – is putting a strain on mobile networks (see Figure 1 as an example). Mobile network operators are working hard to increase capacity so they can meet peak demand and keep subscribers satisfied. Adding capacity can help ensure that users don’t encounter a slow or unresponsive network during mobile data traffic peaks. But it’s an expensive solution that means even more capacity goes unused at off-peak times. Capacity-based plans are an excellent way to slow network growth requirements while monetizing available capacity.

Capacity-based plans have roots in yield management

Capacity-based plans are derived from yield management principles pioneered by the airline industry. They are designed to influence customer behavior as a means to maximize revenues and make better use of available capacity. Like an airline, a mobile operator has several fundamental characteristics that make yield management a viable option. For example:

It has a fixed capacity at any given time.

Its unused capacity cannot subsequently be monetized.

If capacity is available, the marginal cost to carry additional traffic is negligible.

Its customers differ in their willingness to pay for services.

Because their marginal costs are so low, mobile operators should be salivating at the prospect of extracting value from spare capacity in any way that doesn’t cannibalize existing revenues. They should also be keen to seize the opportunity to slow network investment by using capacity that would otherwise be wasted.

So how do they make these things happen? Airlines use forecasting, overbooking, reservations and pricing to manage yield. But mobile data services are different: They serve up data sessions of varying size and intensity on demand. In addition, subscriber contracts generally feature locked-in data pricing. As a result, mobile operators’ yield management toolboxes include forecasting, quality of service (QoS) management and discounting. These tools open up opportunities to increase yield using capacity-based plans.

Approaches to capacity-based plans

Mobile operators can take 3 different approaches to capacity-based plans, each of which may appeal to a different subscriber segment (Table 1).

1. Shift existing traffic to off-peak

By identifying trends in network utilization down to the cell tower, mobile operators can predict when and where capacity is likely to be available. Armed with this information, the operator can offer discounts or a higher QoS to subscribers for consuming mobile data in these areas during these off peak times. The operator could make these benefits available through an inexpensive subscription add-on.

One example of such an add-on is a “happy hour” service in which the operator offers discounted data or increased QoS for selected hour-long blocks of time. Subscribers choose the block that best meets their needs. A variation of the happy hour service is to provide discounted data or improved QoS at locations where the mobile network typically has available capacity. Services like these may appeal to subscribers looking to get the most from their mobile data budget.

The goal of these services is to entice subscribers to shift some of their data usage away from known high-congestion periods. The approach used for these services is static and therefore easy to implement. More importantly, it’s easy for subscribers to understand. The drawback of a static approach is that real-time network conditions could cause occasional overlaps with a peak traffic time. Given the abundance of historical usage information, these overlaps should be relatively rare. We’ll explore dynamic approaches another time.

2. Create services to consume off peak capacity

Mobile network operators can create services that only consume mobile data when the network is not heavily loaded. For example, consider the mobile data used by NetFlix customers in North America (Figure 2). Subscribers who want to download a NetFlix video – or any long-form video – on the go would be a perfect audience for a service offering bulk mobile data transfers for a discounted rate. The catch is that the subscriber would have to allow the mobile operator to decide when to transfer the data.

Subscribers wouldn’t give up all control over these data transfers. They would have the ability to specify when a given transfer must be completed – for example, immediately, within 4 hours or overnight. Working within these parameters, the mobile operator would seek to transfer the data when the network is lightly loaded. Subscribers would get a discount based on the amount of time the operator has to make the transfer. Longer intervals would result in larger discounts because of the increased likelihood that the entire transfer would be completed during off-peak periods, or perhaps even over Wi-Fi®.

This kind of smart mobile data transfer could be linked to an offer orchestration system to ensure that it would only be offered when network analytics indicate that the network is in a peak traffic condition.

3. Monetize peak traffic

The opposite of discounting traffic shifted to off-peak periods is to monetize traffic consumed when the network is congested. With mobile service contracts in place, operators aren’t in a position to raise prices for traffic during peak periods. They can, however, use an offer orchestration system to sell services that may improve the customer experience.

For example, when a network analytics system detects that the network is moderately congested, it can trigger the offer orchestration system to make service level-based offers to mid- or high-end subscribers. These offers could be for a turbo boost or premium subscription. If accepted, the offers generate revenue for the operator while boosting QoS for subscribers. It’s a balancing act: The operator must ensure that those who accept the offer see some benefit and that others don’t see their service degraded even further.

Key ingredients for capacity-based plans

This discussion has already highlighted the role that network analytics and offer orchestration systems can play in capacity-based plans. As always, these systems work hand in hand with an online charging system, a subscriber data system, a billing support system to apply appropriate discounts, and a policy control system to implement enhanced QoS.

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