Skip to main content

Lazy Mass-Market Thinking Limits Mobile TV

Most wireless communications industry analysts report that the full potential of mobile TV services has not been realized. The apparent lack of mainstream consumer interest is the most mentioned challenge that's been reported in market surveys.

As recently as 2001, some mobile communications experts were saying that mobile television might be a reality within 20 years, but would probably arrive much later because the technical problems were so difficult.

Yet a few years later, according to a new market study from ABI Research, successful mobile video technologies are largely in place. As questions about business models, distribution, and content are resolved, the mobile TV industry should now develop momentum -- theoretically.

ABI Research director Michael Wolf says, "Just a year ago, there was a lot of discussion in the industry about whether unicast or broadcast distribution models would prevail, and it seemed possible that unicasting would soon disappear. The new research suggests that while the major top-ranked channels will follow a broadcast model, unicasting is here to stay as a conduit for the long tail of other content that consumers will desire."

Unicasting also has the advantage of an unequalled intimacy between service providers, advertisers, and their presumed captive audiences. However, captive and yet otherwise uninterested in the currently available offering doesn't equate to a viable business model.

ABI says it's a time of experimentation. I believe that it should also be a time to move beyond the lazy marketing approach, and start to segment the customer base. Most of the formats and distribution models under consideration have both pros and cons, and the effort is to find the right mix for each type of content and each target audience.

Pricing is a good example. There are at least half a dozen proposed models for pricing access to mobile video content, reflecting the medium's origin in the collision between the entertainment and wireless communications industries. Some will find the sweet spot that will attract and hold consumers -- others will not.

Even recent assumptions about consumer's likely viewing preferences are under challenge, in light of the medium's improving quality.

"Last year," notes Wolf, "everybody was saying 'We're only going to have 2-minute, bite-sized morsels and mobisodes.' Yet our latest research shows that people are actually watching mobile TV in their bedrooms, for 40 minutes at a time. So many content providers are now thinking about hour-long episodes of prime-time shows."

I believe that the lesson-learned from ABI's study is similar to what I've been saying for some time now, the notion that one-size-fits-all offers are still good enough is misguided thinking -- and a legacy mass-market myopia is at the root of this problem.

The incentive to better understand the differing customer needs or wants can be expressed in two words -- new revenue. Again, the upside opportunity is significant for those prepared to invest the effort to learn more about customer clusters and associated offer preferences.

Popular posts from this blog

AI Edge Investment: Real-Time Intelligence

In the past decade, many organizations have pursued a singular vision of cloud-centric transformation; consolidating data, applications, and compute into centralized datacenters managed by hyperscalers. Yet, the explosive growth of connected devices, the rise of Applied-AI and real-time data requirements, and new operational models are reshaping that paradigm. Edge computing — the practice of processing data closer to the source where it is generated — has moved from niche experiment to strategic imperative. According to the latest market study by International Data Corporation (IDC), edge computing is now the new core in the distributed Global Networked Economy. Edge Computing Market Development IDC forecasts global spending on edge computing solutions will reach approximately $450 billion by 2029, that's up from $265 billion in 2025, driven by rapid advancements in edge-based AI workloads, distributed architectures, and enterprise transformation initiatives. Several key data poin...