Recently, there has a been a swathe of interest in IBM Watson – an artificial intelligence machine that analyses unstructured data (content) and responds to complex human conversation.
Although nearly a decade in the making, Watson’s ultimate purpose continues to be shrouded in mystery. A flurry of acquisitions by IBM suggest that the primary use cases will be in healthcare and business intelligence, however the technology giant has sought to initially display Watson’s content analytics capabilities in a series of public-pleasing instances – such as Personality Insights.
As a software company in a similar space to Watson, it is encouraging to see the power of content analytics being popularised to the general public. However, beyond working out if your written musings are “stoic and philosophical” or “expressive”, there are a range of very important leaps in content analytics that have made it increasingly valuable in the enterprise.
What is content analytics?
At its core, content analytics is the ability to extract structured information (such as people, places, and things) from unstructured text. This information is used to track, organise, and search content. Another way of thinking about it is measuring the meaning of content.
Customer-centric organisations have an unstructured data problem. Marc Benioff, CEO of Salesforce, explained at Dreamforce last year that unstructured data now outweighs structured data five to one within marketing, sales and service environments. And this is set to only increase.
Benioff went on to identify that the biggest imperative for customer-centric companies is to make sense of their unstructured data so as to be in a position to leverage it to better understand and influence the customer journey.
Content analytics brings a whole raft of benefits in the marketing, sales and services environment. Content audits are becoming increasingly important, particularly as the cost and size of content wastage in the enterprise becomes increasingly apparent (newsflash: it’s at least $50 billion in the B2B realm). The problem is that reading, logging and analysing each piece of content takes a huge amount of time to do manually – content analytics does this automatically.
Thanks to content analytics, no longer are businesses limited to aggregate level ‘pageviews’ and ‘bounce rates’, the typical information given by traditional web analytics.
By knowing what each page ‘says’ – i.e. the places, the topics and the sentiments within it – organisations can build an understanding of customer preferences as they read that page. This in turn enables them to determine the tastes and even begin to predict the intent of the customer.
When married with a customer database, content analytics can identify the topics of interest of any prospect or customer that engages with a piece of content.
This insight can be collected and passed onto salespeople who can see which topics have engaged any prospect or lead that comes their way – thereby enabling them to have more relevant sales conversations with better lead context.
Data-mining social media communities for the topics, sentiments and locations of their conversations means organisations can also build a richer profile of each person on a customer database.
This might include their interests, their most shared links and indeed the details of others in their extended network. As a result, businesses can begin to identify brand advocates and influencers very quickly and much more effectively than just crudely going after those with the largest ‘follower count’.
When businesses are subject to thousands of inbound communications from customers – be it online reviews or email correspondence – content analytics can help in filtering and giving structure to the information you receive.
If certain words are being used or a particular sentiment is articulated frequently, organisations can identify these trends and react accordingly, be it in a customer support capacity or for PR purposes.
IBM Watson is cool and something of a novelty for some people, but it shouldn’t be. There are a whole host of content intelligence companies that are employing the same technology to deliver business applications that solve actual business needs.
Sourced from Andrew Davies, co-founder and CMO, idio