Is Google + finally going to come of age?
I’ve long argued that Google+’s ‘public’ profiles are something of a stalking horse for Google’s more corporate aspirations. And at the end of August, the (former) search engine took another giant leap into offering collaboration and content software for enterprises by launching a set of Google+ features specially for businesses.
The quietly-announced development means that some corporates can formally use some of Google+’s innovative features as part of the suite of Google apps. Group video conferencing (on hangouts) during which teams can share, discuss and edit (google) docs in real-time is now a reality.
The battle-lines are increasingly being drawn for enterprise-level ‘social’ software. Microsoft recently bought Yammer, and IBM has long been active, along with Salesforce and Jive and a number of other players. It’s only a matter of time before Facebook makes a play in this financially-lucrative market.
The days of organisations being tied down to using what came bundled with Microsoft Office are drawing to an end.
And the days of organisations starting to build communications networks structured around the ways that people actually like to communicate are beginning.
Q: When is a Tweeting clock more influential than the editor in Chief of the Guardian?
A: When you rely on a flawed algorithm like Klout to measure influence
Klout is an algorithm which promises to ‘measure influence’ in social media. But (as I seem to be arguing a lot recently) it’s immensely flawed. It’s also getting huge amounts of attention – yesterday/today (in Wired and the Wallblog) and last week, from Mark Shaefer, who was in London to promote his book Return on Influence).
As social media started to come under the wing of Marketing Directors and e-commerce teams, it was only natural that the ROI of social media activity would come under the same scrutiny as other comms. But because social media is by its nature networked and leads indirectly to people saying or doing things, and cause and effect is therefore harder to measure, companies like Klout and Peer Index started to offer ‘proxy scores’ of influence – to help marketing managers decide who is ‘influential’, based on social media footprint and activity.
Understanding influence is a social science of its own. Measuring it adds even more complexity. And one of the central concepts of influence is that it depends on who’s asking. So reducing ‘influence’ to one number, irrespective of the algorithm behind it, is always going to fail. Yes, a Klout or Peer Index score can help to identify some people’s networks, but it’s incredibly short-sighted to rely upon it.
As a social business consultant, when I’m asked to identify influential people in a community I never start with Klout. I always start with a question: Why? Why do clients want to identify these people? What do we want them to do once we’ve identified them? How likely are they to actually do what we want? Where do they hang out online, and who do they talk to? I take a lead from the PR industry, from years spent creating stakeholder maps, using a mix of data and gut feel to understand a community, ideally from within it.
Newer start-ups in this space, like Kred, are much more subtle in their identification and application of influence. But there’s still a long way to go – I recently blogged about how measuring social media influence is like nailing jelly to a wall. It will remain so for several years to come.
Until yesterday, @big_ben_clock was deemed to be ‘influential’ in drugs because it regularly used the word ‘bong’ in its tweets. In fact it pretty much only uses the word ‘bong’. That’s how wrong Klout can be.
(This is a slightly updated version of a post originally written for Cogs Agency)
Understanding and measuring influence has vexed social media communicators for years.
Two good places to start would be the release of Brian Solis/Altimeter’s “how to” guide, The Rise of Digital Influence on 21 March, and last week’s panel debate (22 March 2012) at the Guardian’s Changing Media Summit, featuring Leo Ryan (group head of social at Ogilvy), Andrew Grill (UK CEO of Kred), Bonin Bough (global head of digital at Kraft), Philip Sheldrake (Author – The Business of Influence), and Joanna Geary (digital development editor at Guardian News and Media).
But neither one will nail it. Because trying to find a single algorithm to measure influence is like trying to nail jelly to a wall. Fun trying. Maybe a degree of success, but you’re going to basically end up in a bit of a mess.
That doesn’t mean you shouldn’t try. It just means that you shouldn’t rely on a single algorithm. Your mix of qual and quant tools and analytics has to have the right balance. Algorithms should be the starting point, not the end point.
And above all, it means you need to ask the right question to start with. You need to know exactly what you’re trying to measure, why you’re trying to measure it. And what all the proxies are along the way. Quite separate to that you need to ensure your tools aren’t being gamed – which they all are to a greater or lesser extent.
Yes, it’s possible to use tools like Peer Index, or Klout (or younger and better upstart Kred) to put a measure on ‘influence’, but influence always depends on the context of the question. By way of analogy, which of those tools would tell us: Who is the most influential journalist when it comes to reporting last week’s budget? Or even, which is the most influential newspaper, or broadcast channel? It all depends on who’s asking, and why they’re asking. Ask five different people, you’ll get five different answers, depending on their different perspectives. There’s no way an algorithm can answer the question and get it ‘right’.
Back in the day some people used to think that content is king. Then it became conversation. Now it’s context. While empirical data is always useful, it is shortsighted to run any ‘influencer’ campaign based on that data alone. And naive to base it on any one number which is spat out by an influence-identification tool without understanding individuals’ pre-disposition and motivation alongside it, as well as desired outcomes.
Brian Solis is right when he writes: Before you start to even try and measure influence, you need to understand what you want to achieve at the end of the process.
Which – hang on – is exactly what good PR people have been doing for years. Using a mix of qual and quant data, and a decent brief.
I’ve lost track of the number of stakeholder maps I’ve helped draw up using a combination of readership figures, demographics, gut feel and (the missing link with most of these tools apart from Kred) that stakeholder’s willingness to listen/participate – “to be influenced” if you like.
So I was disappointed to see that Klout featured so heavily in the Altimeter case studies. It’s an incredibly blunt tool, and extremely easily gamed. And it takes no account of people’s ‘receptiveness’ to what is essentially a PR approach. People who know their own Klout score know what’s expected of them when they’re invited to something. There is still no such thing as a free lunch. Or a free status update.
I therefore hope that the case studies were actually much more sophisticated than they’ve been presented. From my experience, all the UK mobile phone networks are already significantly more advanced in their social CRM and influencer engagement than the Windows Phone case study. And Nokia have been running a textbook influencer-engagement programme with 1000 Heads for years.
Having said that, though, Altimeter’s Influence Action Plan is spot on – maybe because it reads to me as a decent guide to running an effective PR campaign. The only thing that’s different compared to 5 years ago is the scale and the channels/tools to reach people. And while there are now tools to help measure influence which can cope with this recent change in scale and channels, I worry that the more the process is automated (i.e. based exclusively on Klout scores) the blunter and ultimately less effective it becomes.
I’m willing the tools to get better, I really am. Altimeter’s reviews and feature trackers are really useful in picking out some of the highlights. But those tools are never going to be as effective as people within organisations having a relationship with the people they are trying to influence – the ‘permeability’ that, as a social business consultant, I’m helping clients develop on a daily basis.
Yes, use the tools can help identify potential influencers. But those tools are better used, in my opinion, as a starting point for further research, not as a definitive list. Simply using an algorithmic tool to start a ‘transactional’ relationship will (as Dinah Boyd acknowledges) kickstart the Heisenburg uncertainty principle – just as professional ‘compers’ have mastered the “RT to win” phrase on Twitter.
Influence totally depends on content, context and nuance. That’s the problem with trying to measure it. Tools can help. But – although it’s time-consuming – eyeballs and gut feel should always play a bigger part in doing so.
(This is a version of a post originally written for Social Media Influence)