Video content companies in every industry have essentially the same goal: to provide the best possible media experience to their chosen audience, regardless of the platform, device, or business model.

A key aspect of this experience is video quality. If the image is hard to see clearly, or the motion isn’t smooth and fluid, it’s impossible to become truly engaged in the content, regardless of the size of the screen. Formats, codecs, and compression standards may vary, but one thing remains constant – the higher the quality of your master source file – the better the quality of the transcoded distribution file.

There are many factors that impact the quality of the master file – including frame rate, color depth, aspect ratio, as well as more subjective characteristics such as composition, lighting, and subject matter. One thing is certain, however: the higher the quality of the video, the bigger the master file.

Given all of this, why do so many hosted or cloud-based video processing services continue to charge their clients based on a gigabytes in/out model. This CDN-inspired approach does not make sense for content preparation as it effectively penalizes media companies for attempting to provide their viewers with the best media experience. It becomes one more reason for enterprise players to dismiss the cloud approach without really investigating its strengths.

The traditional pricing model for cloud-based video services works like this:  say a client uploads a 6 GB master file and wants to encode 3 different versions: a 3 GB file, a 1.5 GB file, and a 500 MB version. Under a GB pricing model, the client will have to pay a flat per-GB fee for the combined size of all of the resulting output files PLUS the size of the input file. So, if the rate is $3 per GB, the client would have to pay $3 x 11 GB or $33. More than half of the fee in this case is associated with the input file. If this operation were performed in-house within a finite encoding farm, the size of the input file would have no bearing on the cost of the job. If cloud providers penalize content owners for sending higher quality files as input, some of the cloud value proposition is ruined as content owners will most likely generate lower-quality mezzanine masters in order to keep costs down.

The GB model is even more confounding when you consider the fact that most cloud infrastructure providers (Amazon Elastic Compute Cloud, for example) charge per hour of processing time along with a minimal transfer charge (currently free or heavily discounted). A far more sensible approach is to charge clients based solely on the number of content hours out. So, let’s assume a content owner want to produce 3 different distribution versions of a single 60 minute television program. In this model, the customer pays a flat per hour fee for the total time of all output files. Assuming a rate of $5 per content hour out, the resulting fee would be $15 and the content owner is free to send the best quality master file without fear of paying more.

To make this model workable for enterprise clients, however, the service must also dispense with arbitrary limits on file sizes and hourly volume. Clients should be able to send as many files of whatever size they want without being forced to wait in processing queues. Isn’t that the real value proposition of the cloud?

Only Panvidea currently provides this kind of instantly scalable, enterprise-ready encoding and processing engine. We are breaking with convention to provide an architecture and pricing model that are more aligned with our clients’ needs and aspirations.

This is part of a broader effort on our part to provide a service that can satisfy the requirements of all players in the media space from small business to global conglomerates.