I’m not a massive fan of the “Big” naming convention. But now Gartner are pushing the slightly awkward nomenclature of Big Content, it’s likely to stick.
Big Data is a broad-brush description of the rise in data volumes and variety, leading to challenges and opportunities in storage, classification and use of new and increased volume of data. In most organisations, Big Data is usually used to describe structured data; the explosion in rows and columns, along with the difficulty of creating a single view of data which is spread across disparate databases, and the demand for real-time access.
And now Big Content is described as a sub-set of Big Data, particularly concerned with unstructured data, and the challenges that arise from the rise of content marketing strategy and adoption of social platforms, where compelling content becomes a vehicle for relationships between organisations and their customers and stakeholders.
Gartner defines unstructured data as “content that does not conform to a specific, pre-defined data model. It tends to be the human-generated and people-oriented content that does not fit neatly into database tables.”
The key technology underpinning Big Content is content analytics: the automatic creation of metadata (structure) around unstructured data.
Why does this matter?
This is important because every large organisation has a Big Content challenge, and the rise of content marketing means that in many marketing departments, content of all shapes and sizes is being created, published, distributed, and tracked. The Big Content challenge is getting bigger.
We regularly come across organisations that are doing a content audit and finding content split across 10+ microsites built by 5+ different agencies, many of which have email programs and social profiles to support them. That’s a whole lot of fragmented content, split across content management systems, with no unified way of understanding the customer experience or influencing that journey through targeted content.
And at the most simple level, consider the analytics on your website. You might have hundreds or thousands of articles, videos, etc on your site, and your web analytics give you an overview of traffic levels, and perhaps segments of users by engagement or behaviour. But on an individual level, if you even have the ability to check what a person has read, you are likely faced with a list of URLs. No one has time to open each of those 15 links to get a feel for the prospect or customer’s point of interest and journey.
Big Content for Marketing
When describing the importance in broad brush strokes as above, it becomes important to swiftly move to some easily understandable delivering of value. We find there are a few key drivers of value, when applying content analytics to marketing:
1) Better content strategy
By analysing the current content archives, and automatically classifying them, you are immediately shown the gaps in your content coverage and the areas of oversupply. This can focus and increase the efficiency of content creation efforts.
2) Better insight
By creating metadata around content, the interactions you have logged (and continue to log) become more than performance metrics. They become indicators of each individual’s interest. For eg, you could analyse the clicked URLs of every prospect in your database, and immediately have a easily-understandable interest profile about every one, without needing to dig into the details of what each person read.
3) Better targeting
By structuring your content, you enable targeting that is based on meaning (the metadata). Rather than having to classify each new piece of content into a nurture campaign, whereby it is targeted using a strict set of rules, content can automatically be targeted by interest.
Big People – understanding complex individuals through their content consumption
If we really wanted to be Gartner-esque in our description, then the convergence of content analytics with customer data should really be called Big People. But then, that would be stupid. Naming conventions notwithstanding, there is a massive opportunity when the unstructured data describing the content-consumption of customers/prospects/audiences is interrogated.
Go Big Content or Go Home
Anyway, even if Big Content sounds to you like someone scratching a blackboard, the use cases are interesting.
When you think about the huge array of social, web, and email content that is sitting there, the phrase “sweat your assets” comes to mind. It’s exciting to see this thinking emerge from the deep dark corners of Enterprise Content Management, to the horizon of marketing teams.
If you are engaged in content marketing, make sure you aren’t simply creating a headache for yourself in the future. Address the Big Content challenge now.
If you are interested in making sense of your content (whether it is ‘Big’ or otherwise!) or more your content contextually relevant within your customer communications, please get in contact – we’d be happy to have a chat!