Content marketing and network analysis: Why you need both
Chris Arnold, CTO of Cambridge startup Awedience, came to see us recently to demo their new software, which enables you to analyse and strengthen your Twitter networks and hone in on the influencers who can make a difference.
Of course we didn't let him leave the building until he agreed to write a guest post for us.
2013 was been described as the year of content marketing. In fact Exact Target described it as a concept that has hit the main stream.
Yet at Awedience we believe it does set the cart before the horse.
The problems with content marketing
Too often there is an assumption that, with a few tweaks to existing marketing materials, customers will be happy to receive regular, repetitive broadcasts arriving in their inboxes or social media accounts.
We have been looking at a somewhat different approach: analysing very large volumes of Twitter data to identify more coherent segments.
It’s not that content marketing isn’t a good idea but rather it often falls over in three key non-editorial ways:
1) Companies rarely understand the nature of their own networks. Who drives the conversations? Where are the digital cul-de-sacs and who is critical to getting the message across?
2) Optimum times are rarely identified, let alone differing content types to drive engagement. For example: Do you want this retweeted, a video watched or photo shared?
3) This is not a numbers game. More followers doesn’t mean greater reach, especially if they’re fakes. Last week we detected a community that had a fake follower rate of over 30%, and this was for a leading blue chip digital marketer.
Your own network
We’ve recently been looking at the Twitter account of a large software firm.
When we applied our community detection algorithm it highlighted an immediate challenge. There are four distinct communities within one network of followers.
As these groups are disparate in their interests, messages blindly broadcast are irrelevant to at least 75% of those receiving them.
Great content needs great timing. Tracking the conversations within specific segments, as opposed to your whole network, is crucial to making sure you’re having an impact.
Detecting fake accounts has gotten a lot harder in recent years. They tweet regularly, have full profile information and even their avatars look genuine.
Taken in isolation they look real, yet when you look at them in the context of communities you can immediately see that their behavior is different. They normally form a disjointed group that sits within the account, densely interconnected yet not linked to any other community.
It’s early days at Awedience but we believe that there’s an essential need for both elements to work together seamlessly if we’re to meet our customers’ expectations of delivering engaging content to the right people at the right time.
Join @Awedience on Twitter for more advice on strategic network analysis.