Tagged: analytics

When Will Request Platforms Evolve to Recommendation Engines?

The visual media industry is good at content aggregation, yet has had historic challenges in customer retention. Once a service focused intently on solutions, it became broadsided by online sharing and a new class of creators that reflected a shared economy. Rapid focus on rights protection drew attention away from marketing development, and a game of catch-up has been in play ever since. What has been clear throughout, however, is that the core use cases supporting the industry haven’t really changed a whole lot.

Along the spectrum of content, the most simplistic need is the readily-available and cheap: quick use for a corporate blog, or short-duration non-campaign use can be easily obtained from volume stock platforms or begged from anonymous sources at low to no cost (other than time). The actors involved are reflective of this use, typically a single marketer.

At the other end, where complexity factors into everything, content acquisition math becomes tougher to solve. The campaigns are larger, far-reaching, and longer. There’s significant budget, many actors to appease, and in general much is at stake. With money come options, and more option means more decisions, more inventory, more potential sources.

While supply has struggled to keep pace with demand, there are no lack of products on the market to help solve content strategies. In fact, many are turning to technologies such as computer vision to help build enhanced services upon their existing business models (Shutterstock’s reverse engine search being one). A few, like ImageBrief, Foap, Snapwire and now 500px, have implemented request platforms, but with such few imitators among licensing incumbents it’s questionable how valuable a service this is.

Request platforms invite brand owners to publish their need (loosely in the form of a creative brief) to their community, reap engagement, and harvest content for consideration. Those brand owners dictate usage rights, price paid to the winning community member (or in some cases, a prize, as the process is essentially a contest). As hosts, the request platform receive all the content submitted as new inventory to market elsewhere – in itself a content acquisition strategy that can help fill much needed areas.

As business models, request platforms have been around for a long time, before cloud tech enabled offsite hosting and digital distribution had significant hurdles. Even with the strides into big data and computer vision, why hasn’t the model improved beyond what seems to be simple search and retrieval?

More information exists online about how content is being consumed and by whom – metrics that can help define the success and potential optimization of campaigns. Beyond marketing analytics, actual rights information and other risk mitigation data can be obtained, widening utility beyond campaign efficacy and into digital rights management. As a service this has certain value with campaign/brand owners, but how else can request platforms – or any visual media licensor – move the needle on their product and start to anticipate the needs of their customers?

Auto-parse creative briefs:    Online forms are a hassle, and are an impediment from someone using your site/service. Why not allow for briefs to be uploaded in their original form, parsed and automatically generating a set of applicable results in inventory? Briefs can contain a high degree of conceptual information, which has a good chance of being filtered out through a normal search. By subscribing to the largest data set applicable to a single query, you’re guaranteeing more relevant results.

Expand the inventory base:   While perhaps antithetical to most licensors who are primarily concerned with aggregating inventory on their own platform, providing clients with options where platforms fall short addresses retention and service. Why not open the scope wider, include competitors and partners, and develop a product that delivers option value? This is the age of referral traffic and micropayment processing – broad collaboration, channel agents and reselling is not a foreign concept to this industry.

Avoid myopic metrics:           User data derived from one’s own platform is insightful, but it’s still a single view of characteristics and trends that at best reinforce successful tactics. Why not apply a multi-dimensional view, and incorporate broader data sets? Invest in historical and forecast data that are macro influencers, and start to map future state requirements from the community. Basing future behaviors off of past without the inclusion of environmental factors is missing the narrative thread.

Provide follow-up tracking and analytics:        Post transaction, customers have little to no interaction with the content source, thus cementing the ‘transactional’ nature of the relationship (and underscores core retention issues). Give them more reasons to engage, like options around campaign reach (through computer vision tech) and bundling aggregate metrics for comparative views. Sharing knowledge is a first step toward recommending future actions.

Very few companies are looking at full lifecycle content management that encompass acquisition through analytics (Adobe is the most bullish through its recent acquisitions), which is where the bulk of previous licensing business has migrated to. Those request platforms that seek to solve UGC harvesting target only part of the problem faced by content marketers – viewed as true consumers, content marketers are in the position of formulating the questions around what they need next; for platforms that seek to fulfill these needs, endeavoring to answer the questions before they’re asked is difference between their current model and a recommendation engine.