Content Syndication and Sharing
In the last post, I discussed some of the challenges around creation, acquisition and management of content. This post I want to look at the problems with distribution.
Content syndication has been around for a while for most types of publishers. There’s a lot of ways to consume information, away from its source of creation. These include RSS readers, aggregators, etc.

An example of feed flare for publishers
However, this hasn’t really been the case for e-commerce. Content syndication has thus far been limited to Comparison shopping engines, and in some select types of content (such as reviews) the content is aggregated together by a third party such as Buzzillions.
Why is this?
Shopping (especially in certain verticals such as fashion, home, and for almost all purchases above a certain ticket price) is a social activity (whether you’re consulting your friends, your wife, your bff etc.) Yet this social component of the shopping experience has been slow to move over to the web. For the most part e-commerce is a one to one experience – and its tough to incorporate a social component into it without calling your consultant over to the screen to look at the product you’re looking at. This makes, “distributed” shopping very difficult.
Only recently have things like “share on facebook” started to pop up on sites such as Dr.Jays (fashion) etc.
This content syndication, and sharing is still in its infancy. Much more is possible, as should be obvious by taking a quick look at the publisher’s toolset.
As companies like BestBuy start to create open API’s to their data and structure and format of e-commerce data starts to follow a standard, we will see the democratization of content. Take a look at what Bestbuy offers below :
As you can see – it includes data for historical, and current products including near real time availability information for both online, and retail store locations. This is merely a first step. Imagine the types of applications that could be built using data like this from all vendors? People “rolling” their own comparison engines that are limited to a few stores, and a few verticals that they are interested in. People getting RSS feeds of all products reviewed by at least 50 people that have a rating over 4 stars across all vendors, but limited to products that are in the category “Vespa Accessories”. All these slices, and dices should be possible today, but aren’t because of this limited access to data.
Sites like Fixya or RateItAll are trying to build this meta social layer, but they struggle with the basic information on each product – descriptions, specifications, features, images, manuals, etc. from the manufacturers and availability, pricing, shipping, and other value added content from the retailers.

Fixya.com attempts to build a social support layer for consumers
Once we have access to complete, well formatted, standardized data – what would be the effort involved in taking the next step and building the ability to socially share information about it. Imagine an application that makes shopping as social as PhotoPhlow makes photograph discussion. If you haven’t seen Photophlow yet – watch the video below.
What is Photophlow?
This ability to discuss, share, talk in real time, or asynchronously will lead to a radical change in the way people interact with e-commerce sites. As data standards start to form, more and more content will be user generated. We can already see some of this in the form of user submitted pictures on Amazon, and certainly in reviews and ratings.

Images with notes as submitted by users on amazon.com
This data format standardization and availability will enable the widespread syndication, and sharing of data, and the merging of the manufacturer, and retailers supplied data with user generated data (the beginnings of which can be seen above). This in turn will enable a wide set of applications developed to help people shop in a wider variety of methods. At this intersection of widespread disemmanation of data, and social interaction between users, lies a gold mine of analytics data that will help surface, what people are buying, what the trends are, what the gating factors are – as well as who the mavens, and connectors are across the entire industry. I for one am excited to see it coming.
What else do you think we could build if we had easy access to clean e-commerce data?

