Will Data Broadcasting in IBOC Succeed Where Other Services Failed?
In this issue we begin a multi-part examination of IBOC datacasting and its prospects. Much has been made of the added value and expanded services that data transmission might add to radio in its transition to digital broadcasting, yet if history is any guide, the future reality may have a different outcome.
Both radio and TV broadcasters have heard the praises of datacasting sung repeatedly in the past, including promises of substantial new business revenue. The truth of the matter is that to date, such a one-way data delivery service has never been broadly successful. With such a cheerless history on record, what makes broadcasters think similar systems in the future will fare better, especially considering the continuing emergence of new competitive technologies?
To best evaluate this environment, let’s first review some basics of the business and service models involved.
There are several existing models for the types of service that might be operated as a datacasting enterprise.
The first could be called Extended PAD. This would allow a broadcaster to offer more than the minimalist artist/song title/album metadata carried in the standard program-associated data signal, such as song lyrics, related graphics or photos (e.g., album cover art), and music-purchasing data or links. Alternatively, this data could include photos or charts to illustrate a news story, or additional related text and references for the “tell me more” seeker.
Other models for datacasting involve non-program associated, or NPAD, content, in which data that has nothing to do with the station’s audio content is delivered.
Here again, two basic approaches exist. The first simply blasts a continuous stream of data to all receivers, typically with frequent repetition of the same data, which each receiver then filters and sorts according to its user’s preferences. The other method sends a series of discretely created, separately addressed messages to individual receivers, again with frequent repetition or “carouseling” of the same messages.
The blast-and-filter scheme seems to maximize the value of a one-way broadcast model, but the discrete messaging approach could also work if the service provider wanted to offer an open paging service rather than an information service, for example. The blast-and-filter model also makes the receiver work harder and longer, causing more power drain, whereas the discrete messaging system simply requires the receiver tacitly to monitor the stream and only awaken into full-power mode when it hears its address being called. The two models could also be merged, such that a blast service could occasionally insert periods of discrete messaging.
Note that the NPAD services typically are envisioned as originating from some third party, for which the broadcaster operates as a pure service provider (like a telco), delivering data to its service area for a given number of bits per buck, or for a flat monthly rate. On the other hand, Extended PAD services are assumed to originate from the broadcaster, but even these could be created by a third party that is synchronized to the station’s audio program – as is already being done today for simple music metadata-stream creation delivered over RBDS.
Is there a market?
All of these models have been tried at one time or another in the broadcast world (radio or TV). In the United States, at least, none has yet gained substantial traction, and several companies have come and gone in the process. It’s therefore worth examining why these systems failed, as another part of our study.
In the postmortems of the collapse of recent datacasting businesses, several reasons have been cited by analysts, while others have been surmised by knowledgeable observers. One commonly presented reason is that these offerings were just ahead of their time, and the mainstream market wasn’t ready for them yet. This is an easy out, as it ascribes a certain prescience to the corporate leadership (albeit posthumously), but it’s often a disingenuous cover for the real causes. Among the latter is simple lack of demand. Perhaps there really isn’t a sufficiently large market for these kinds of services, neither now nor at any time in the foreseeable future.
Then there’s the delivery model question. How viable is a one-way, point-to-multipoint service for data delivery? The broadcast model is only appropriate for content delivery to a fairly large-scale audience; for smaller, niche-type services one of many point-to-point alternatives may make better economic sense.
Further, the reliable coverage zone for a broadcaster’s datacasting service may not be the same as for that transmitter’s main program reach. Data services generally are less fault-tolerant than audio or video signals, so either the data service area is reduced compared to that of the main program, or additional error correction must be applied to the data signals, thereby reducing throughput of payload.
Another notion that’s been raised is that broadcasters really don’t have a powerful position to leverage for entry into this market. Knowing the ropes of the data-delivery business may be more a strength of telecom companies, and this may have hampered initial movement and led to some false starts.
Finally, some earlier datacast services targeted only fixed receivers, and this lack of capability to address the mobile data market may have intrinsically limited such systems’ prospects to an insurmountable degree.
It’s a nice data day
Proponents believe things will be different with digital radio datacasting. For one thing, robust mobile reception should be assured, although whether reliable coverage can extend to the same limits as audio service remains to be seen. (Some of this will depend on the type of data being delivered; more on this in a future column.)
Another big difference between FM subcarrier datacasting and IBOC is that the data transmitted in the latter can be a multiplex of several services, with each service occupying only the bandwidth it requires at any given moment. This bandwidth-on-demand approach provides far greater spectral efficiency than the subcarrier case, where a fixed amount of baseband real estate is occupied by any single service all the time, whether it needs it or not. For many data services, the demand pattern is quite bursty, and this plays much better into a multiplexed-services model than a fixed-bandwidth-per-service (SCA) scheme.
Perhaps adding even more efficiency is the use of opportunistic data in the IBOC system, which allows the main service’s digital audio codec occasionally to offer some of its bandwidth to data services when audio coding requirements are temporarily reduced. (This gives new meaning to the term “silence is golden.”) Some observers have only half-facetiously commented that public radio, with its heavy emphasis on classical music and talk programming, may turn dead air into dollars by stuffing many opportunistic data bits into its many momentary pauses, something that most commercial formats ardently avoid.
Regarding market experience for data services, consider that radio broadcasters now have a lot more experience than they used to with IT-type systems, due to the increased use of computer-based technologies for audio content production and management. Most stations have significant on-line skills and well-established Web services to call upon, as well. For certain kinds of datacasting, this fresh background may provide a context of familiarity that can lessen the learning curve’s slope and ease the entry to new service offerings in ways previously unavailable to the industry.
Maybe most important, some sectors of the audience finally could be ready for such service, given the broad experience with the Web, instant messaging and other timely and interactive services currently proliferating. Catching some of this interest could give terrestrial radio the hook into edgy, younger-skewing new markets that it desperately seeks today. So perhaps the old lessons will not apply to the new models. It wouldn’t be the first time the conventional wisdom was proved wrong.
Next time we’ll look at some specifics of HD Radio datacasting and examine why some of that system’s parameters are being reconsidered.