Media OTT: A multi-dimensional jigsaw to solve

by Shafeer Badharudeen, Chief Technology Officer

Media OTT: A multi-dimensional jigsaw to solve

by Shafeer Badharudeen, Chief Technology Officer

Internet is ‘the’ channel of commerce across industry segments selling physical goods, digital goods and services commoditized as products. Being in the business of media asset life cycle management, media industry also has embraced internet commerce in the form of media OTT platforms. But are all the players venturing into the media OTT playground have the right approach and strategy to architect their OTT platforms as an ever evolving and winning media OTT business model backbone?

With the option of plenty for consumers when it comes to media consumption and their availability, the first and foremost dimension of the jigsaw puzzle to focus on for anyone venturing into media OTT playground is the continuous profiling of its ever evolving customers or audience. A reactive feedback driven corrective measures within the platform will be equivalent to missing the bus by an irrecoverable distance. The OTT platform should evolve as a brand when it comes to customer service and customer centricity(for delivering the right media assets and delivering the best experience from locating the item to consumption of the item) similar to a brand like Nordstrom which is synonymous for customer experience. 

Nordstrom sales reps will never give pointers for customer’s enquiry about location of certain assets, rather they accompany and take you there! In similar way, every customer or audience in the OTT platform should feel that they are privileged and an intelligent invisible personal sales assistant is available within the platform to help them locate the assets of their preference and taste by best availing the real estate available for catching customer eyesight. Also the platform client components should be consistently following the philosophy of not having longer checkout funnels in customer’s journey from entry to exit in the platform. Platform should not also deliver any fluffy and unwanted selling attempts that are not having any context and relevance while the customer is towards the last leg of transaction fulfilment once the decision is made. Platform should also offer seamless viewing experience that doesn’t expose any constraints of the platform components that are spread across the front end, demanding the content or the backend, supplying the content. 

An integrated self-adapting and continuously learning engine should be spearheading and controlling this experience by distributing real time precision driven responsibility to each and every front end and backend components within OTT platform to perform specific tasks. 

As experience delivery has several dimensions beyond a usage pattern based content recommendation, the job of such an engine should be way beyond the traditional recommendation systems and should be modeled as a feed forward model. While taking into account the behavioral and content consumption patterns, it also has to look into the device and communication infra of the source of the request, number of concurrent request for the same asset, the availability of PoPs (Point of Presence) of CDNs (Content Delivery Networks) with shortest route, SD or HD to be delivered based on decision factors etc. In order to perform that job, such an engine should be receiving the feed of real time abstracted health and vital parameter information of all of the systems and components involved in the content delivery life cycle. Hence real time analytics and data sharing has to be embedded everywhere in the OTT system landscape, not only at the client side to capture the users’ transaction patterns. Such an integrated approach will not only ensure the right content delivery personalised and contextualised for consumers, but will also ensure best and optimal resource consumption across the OTT flow. 

The next key and important dimension of the Jigsaw for OTT is around the content or the media assets to be put on sale within the platform. Content alone irrespective of the value it brings in terms of the popularity of the star casting or crew members are not going to help in acting as the catalyst for boosting the OTT platform. Packaging of the content for presenting it to the target audience depending on the context is also key. Social media marketing and teaser based viral marketing has become one of the key success factor for media releases now. It helps in developing an initial audience base having the mindset to drive viral campaigns in their ways. While the success depends on how well the context definition happens, context driven teaser delivery personalized for individual target audience will help in boosting the content value while launching new assets into the platform. Detailing of the assets are also key. While the individual asset level meta data can remain static for a media asset within the platform, detailing when it gets presented to the consumer can be personalized and contextualized by bundling the asset metadata with the correlational assets. An NLP (Natural Language Processing) or text mining backboned ingest process will help in achieving this bundling in the metadata space. If the media asset recommendation to a target consumer happens based on his/ her inclination towards a star cast and genre, meta data delivery including the teaser, tile images etc. also has to be delivered contextually for a true personalized experience.

Having a very segmented market place of foundational components required for building an end to end OTT platform like OVP, CDN, media player etc in the media space at the moment, an integrated collaboration platform (with real time data sharing by the different systems and feeding of the outcomes from the models defined within the platform to those systems back) is the missing piece in the jigsaw for extracting the real value of the assets getting on boarded for sale in OTT platforms.

The next core dimension is the supply chain when it comes to content delivery.  Affiliate driven sales has evolved as a major volume of sales in the Retail e-Commerce segments. If the platform player also have either the original ownership of the media assets or digital content ownership and distribution rights of them, they should build the OTT infrastructure in such a way that a robust supply chain can be flexibly built on top of it. It will help in monetizing and managing the content delivery through affiliate driven boutique platforms and content aggregation mediator platforms like the one that wireless service providers are launching apart from your direct reach to their target audience. This will work as one of the most result driven strategy for them if they are dealing with multi lingual and multi-regional contents of regional and local relevance. 

If the OTT platform infrastructure can become robust backbone for driving an affiliation program driven multi-channel content delivery models by providing the required API support for extracting meta data driven catalogue mapping and a tightly coupled TV everywhere framework skeleton (that can be easily configured with the required rebranding)OTT with multi screen support , it can deliver a game changing experience in the OTT playground. 

The last dimension of the jigsaw is the business model. Shared resource (e.g cloud platforms), shared service (e.g. Uber) and volume selling (e.g. Walmart’s’ business model) are the evolving models emerging across industry segments. Those models have proved their success in their respective market space as well. 

In the media OTT space, it’s time for further segmenting and re-defining the SVOD and TVOD subscription models to bring in volume driven, shared and distributed subscription models that can also help achieve the scale while aggregating the social and community power for the platform.

A social collaboration platform buildup within OTT will also help in expanding the scale while it also helps in extracting the customer sentiments around the platform and assets put on sale within the OTT platform.