Relational Content Management in eCommerce
Content management is a topic that can send shivers down the spine! Not because it’s particularly hard necessarily, but if you ask 10 people what it means you’ll quite likely get 10 different answers! Delivering to exceed expectations becomes challenging if you’re not entirely sure what the expectation is!
An interesting question regarding content management on eCommerce sites is how to manage “assets” that can be associated with your product range (or used more widely within the overall site). It’s pretty well documented already that providing related, contextual “content” will add significant value to the customer in terms of branding, value-added services and ultimately in improving the shopping experience and likelihood to buy.Nothing new here of course; this concept is pervasive throughout eCommerce right now: buyers guides, videos, alternate and enhanced images, “how to” guides, comparisons and the list goes on. The value curve of course is, the more content the better as long as it meets some golden rules: it must be relevant, it must be contextual and it must show value.
But how do you manage all of these assets and most importantly, their relationships to products, categories and merchandising areas without building an army of content managers?
The good news is you’ve probably done all the hard work already! As we all know, in eCommerce data is king, and always will be. You’ve probably already spent a great deal of effort, time and money in getting your product data accurate and comprehensive. You’ll have them nicely categorised, ranged and organised within the natural boundaries of your chosen market: season, genre, technology, range, features etc.
This focus is always given to the product range so why not content? Why not categorise content in a similar way to products so a range of content assets can be created each with their own attributes and categorisation? If we do this then imagine what we can (most importantly) automate!
Most eCommerce sites these days use a powerful search engine, be this Endeca, Adobe Omniture, the Apache foundation’s open-source SOLR or others; it doesn’t need much extension in either thought or programming to exploit these tools to index content as well as products.
Now, rather than manually setting up each and every relationship between product and content, which means a lot of time in an area where humans tend to make mistakes, we can ask the search engine what it thinks is the most relevant content to “surface” on various areas of the site. The advanced business tooling already in place from these search engines can be exploited further to enhance the relevancy, weighting and filtering of the content.
Naturally, and to the same extent as products, the engine is only as good as the data but with a 'setup once, use many times' principle, it’s easy to see the potential savings in effort of avoiding the initial setup and ongoing maintenance of single product to content relationships. In essence the technology is doing the hard work - which is what it’s there for!