Mobile "unlimited usage" plans often cost more than alternative plans offering different amounts of data usage. But service providers and consumers seem to prefer the unlimited plans. The issue is "why?"
As a practical matter, many customers might actually save money by not buying unlimited usage plans. But consumers often value predictability more than total cost.
Dynamic pricing (price varies according to when, how or volume purchased) has been a staple of product pricing in the communications business for decades. The use of the network might be rated higher during weekdays and normal business hours, lower in off-peak periods.
Of course, seller price methods represent cost to the buyer. In any dynamic pricing system, cost can vary based on volume of use (per-minute or per-message or per-megabyte consumed) as well as any other parameters that are dynamically applied (discounts, bundle offers, promotions).
Dynamic pricing is touted as an advantage for buyers. “Spend less” is the attraction. That can apply both for buyer infrastructure spending (capital investment) as well as buyer operating costs (personnel costs, for example).
When both dynamic and static (fixed cost alternatives) are available, businesses and consumers are left to evaluate the value of the options, as well as the potential cost implications.
Quality of service also has been a driver of product pricing differentiation. Business services with QoS guarantees, support services reaction times and financial advantages for customers if the policies are violated, have been a staple of communications product pricing for decades.
The ability to support 5G network slicing in the core network, all the way to the mobile edge, is supposed to create new product capabilities, such as networks optimized for particular parameters.
Ultra-low latency performance; bandwidth guarantees, security or performance predictability will be touted as values of network slicing, a new way of creating virtual private networks.
But there also are situations when dynamic pricing is not preferred by buyers. In such instances, dynamic pricing might lead to lower buy rates than fixed-rate alternatives or predictable cost alternatives, even when users face possible higher long-run costs.
In other cases, total long-run cost also is driven by volume. High usage tends to favor a non-dynamic approach such as buying and operating “owned” infrastructure. In the unified communications as a service business, for example, high volumes mean UCaaS costs more than owning an enterprise switch. At low volumes, UCaaS costs less, and often also provides more functionality.
Many products sold to consumers have similar trade offs. It has been the conventional wisdom in the video entertainment business for many decades that consumers prefer flat-rate buying and pricing to dynamic pricing and buying.
Where a linear video subscription--depending on the number of channels purchased--might cost $50 to $80 a month, a streaming service--depending on which services the customer wants to buy--can start at about $7 a month each but might cost $15 a month or so.
Buying only a few pay-per-view or on-demand items a month can exceed the cost of a Disney Plus, Netflix, Prime, Hulu, HBO Max or Peacock subscription, for example. Granted, no subscription offer from any single provider ever offers “most” content, so most customers likely buy more than one streaming service.
The point is that dynamic pricing offers the most value when a customer’s consumption is low, but offers less perceived value when consumption is moderate (possibly watching more than three movie or TV episodes a month that are purchased dynamically).
Dynamic versus flat-rate pricing also has been an issue in the dial-up and broadband internet access eras. Take rates and time of usage have been higher in a flat-rate environment. Users faced barriers to usage in a dynamic pricing environment that affected the viability of application business models based on network effects.
Network effects depend on the sheer size of the networks. Network effects might also hinge on the likelihood of connecting with a resource in real time, as well as any latency to connect with resources.
Phone, facsimile, email, social or other communication-based networks have little value when the total number of other users is low. So scale creates potential value. Pricing and rating affect scale, so the choice of dynamic or fixed rating also matters.
Volume also affects appetite for either rating method. Rational buyers (business or consumer) are not going to value subscriptions or flat-rate access plans when their expected usage is episodic or otherwise very low. In such cases, dynamic or volume-based pricing should be favored, so long as the per-unit prices are low, in relation to perceived value.
High usage expectations create a better value proposition for flat-rated or subscription plans, which then offer a better per-unit or per-instance cost.
So an ecosystem premised on network effects has incentives to use pricing plans that favor wide adoption, since many business models are contingent on scale. Advertising-based and commerce-based or transaction-based business models require volume.
Pricing plans that encourage volume therefore are beneficial for the ecosystem.
Early in the dial-up internet access period, AOL used per-minute pricing. Usage did not climb until that policy was abandoned and an unlimited usage alternative became standard. In the days of metered use customers only stayed online about 10 minutes a day.
In 1992 AOL had a total of about 200,000 subscribers, using a metered usage approach. By the end of 1993 AOL had grown to about 500,000 customers. By August 1994 AOL had grown to about a million subscribers, and had roughly doubled every year since 1992.
By December 1994 AOL had jumped to 1.5 million subscribers, growing to four million a year later (November 1995).
In December 1996 it switched to unlimited usage, peaking about 2002 with more than 25 million members. The point is that customers really preferred fixed and predictable pricing, as it eliminated uncertainty.
Over time, a wider range of connectivity products also have been repositioned with pricing models that are akin to subscriptions, effectively or actually subscriptions. In many markets, mobile customers have unlimited use of domestic market text messaging or voice, with no per-minute or per-message additional charges.
Veterans of the entertainment video business might agree that the power of consumer fixed-price subscriptions is predictability. That same argument might apply to electricity or water billing that averages the monthly recurring payments over a 12-month period where consumption varies significantly between winter and summer.
There are differences, however. Light users might still prefer dynamic pricing. Heavy users almost always benefit from flat-rate or subscription pricing.
The relative cost burden also matters. Cost of ownership or cost of use matters less when the items represent a small percentage of overall spending or value.
Higher-income households spend relatively little income, percentage wise, on communications or video entertainment, in general. In fact, U.S. households with annual incomes between $100,000 and $149,000 spend most of their communications budget on mobile devices and services. So the actual pricing mechanism matters less than for lower-income households, where communications spending represents a higher percentage of discretionary spending.
Mobile virtual network operators often make a living based on their ability to serve low-usage, low-feature-requirement or cost-conscious segments of the market.
Spending over time also is affected by general price level trends (inflation) as well as product substitution and technological improvements.
U.S. household spending on communications arguably has grown since 1990, but remains flat as a percentage of household income, with a fixed component (connectivity services) and a variable component (devices and a la carte content purchases).
In many cases, product substitution also has happened. Households spend much more on mobile services and internet access, but have compensated by dropping fixed network voice services. In the same way, households substitute lower-cost streaming services for linear video packages, or reduce their spending on linear packages to create room for streaming alternatives.
At the same time, price declines for mobile service and the ability to use Wi-Fi for network connection also have allowed use of more devices per household. Though the conventional wisdom is that the cost of internet access has increased for some decades, real prices have declined, accounting for inflation and consumption.
Is U.S. internet access too expensive? Maybe not. According to a new analysis by NetCredit, which shows U.S. consumers spending about 0.16 percent of income on internet access, “making it the most affordable broadband in North America,” says NetCredit.
In Europe, a majority of consumers pay less than one percent of their average wages to get broadband access, NetCredit says. In Singapore, Hong Kong, New Zealand and Japan, 10 Mbps service costs between 0.15 percent and 0.28 percent of income.
A normalization technique used by the International Telecommunications Union is to attempt to compare prices to gross national income per person, or to adjust posted retail prices using a purchasing power parity method.
There are methodological issues. Gross national income is not household income, and per-capita measures might not always be the best way to compare prices, income or other metrics. But at a high level, measuring prices as a percentage of income provides some relative measure of affordability.
Looking at internet access prices using the PPP method, developed nation prices are around $35 to $40 a month. In absolute terms, developed nation prices are less than $30 a month.
The average global price of a fixed network internet access connection is $73 a month. So average U.S. prices are significantly lower than the global average.
The point is that consumers and businesses often prefer not to buy services or products that are priced dynamically, and prefer flat-rated or fixed-rate product alternatives.
Overall, home entertainment video revenue is dominated by subscriptions not discrete purchases of content globally. That applies both to linear and video streaming revenue.
In a sense, a subscription is a fixed-price contract, providing certainty of cost. The disadvantage is a loss of flexibility, but buyers seem to see value in the price or cost certainty.
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