social media monitoring | Show me numbers

Social media listening tools can provide powerful insights when they’re used to find answers to really good actionable questions.

But recently I’ve noticed a move to start making absolute statements based on such analysis. I highlighted one such area earlier this year in relation to the UK general election. Some people even suggested Twitter could predict the outcome. They were wrong.

The thing is, as much as social data can be powerful and seem vast in scope, you still need to keep a sense of perspective.

It’s been estimated that every day people speak an average of around 16,000 words. With this in mind I thought I’d try and make a quick estimate of the proportion of people’s conversation in North America and the UK that social media monitoring data represents.

Answer? 0.16 per cent*

And that’s before we get into issues like spam accounts, bias towards power users’ output, questions about whether tweets and posts are truly an authentic reflection of what people think and feel, demographic bias and the online disenfranchised.

I based my estimate on Twitter and Facebook, as they represent the majority of conversation that such tools access. We could add Reddit, blog posts, comments on online articles and YouTube videos, forums etc, and if anyone fancies doing so, be my guest! But I don’t expect you’ll get to a much bigger number.

Particularly as on the other side of the equation we could add to what people say other forms of conversation that aren’t accessible to social listening: emails, messaging apps and collaboration tools like Slack to name a few.

So does this make social listening as an insight tool a waste of time?

No, of course not. I’ve spent enough time buried deep in social data to know that it can provide hugely valuable insights. But to achieve this you need to be extremely focussed.

Ask good questions

Structure questions that take into account the limitations of the data. “Who does Twitter conversation suggest is going to win the UK general election?” does not fall into this category. Also ensure the answer doesn’t lead to a “so what” moment, but provides a genuine basis to take more action.

Say no to pretty noise

Pretty dashboards that pluck results out of the ether aren’t the answer. Make sure you understand exactly who you’re listening to – who is behind the data.You need this audience perspective to be confident what you’re seeing is real insight and to address what I call the four (f)laws of social listening.

Be sceptical

Sometimes social media analysis gives you an answer you didn’t expect, one that differs from your existing world view. It’s crucial you don’t dismiss such answers as they could be the most valuable insights you’ll ever get. Equally, don’t naively just accept them at face value. Challenge. Try and triangulate the answer from another source. Try asking the question in a different way and compare the answers. Sometimes you can be surprised.

* You can see my back of an envelope calc here. The estimated variables are editable in the “Try your own” sheet (highlighted in blue) so you can have a play to work out your own figures. In simple terms we’re comparing:

Talking: c. 422 million people across US, Canada and UK using 16,000 words per day = 6.75 trillion words.
Twitter: c. 137 million tweets (N. American and UK users assumed at 27.5 per cent of active users multiplied by 500 million tweets per day) assumed to contain an average of 25 words = 3.4 billion words
Facebook: c. 707 million Facebook posts per day (N. American and UK users assumed at 16.4 per cent of users multiplied by 4,320 million posts per day) assumed to contain an average of 50 words = 35 billion words. Only 20 per cent of these posts assumed to be accessible by social listening tools. I have no specific basis for the level of this last assumption, though clearly it is the case that social listening tools can’t access all Facebook data – though Datasift’s PYLON offering provides a potential solution to this privacy issue. However even if you assume all posts accessible the result only increases to 0.57 per cent.

In the week before Christmas, Brandwatch, the social media monitoring company, acquired influencer platform (and Lissted* competitor) Peer Index for a reported figure of £10m in cash and shares.

In the words of Giles Palmer, Brandwatch’s CEO, it was because

“As we (Giles and Azeem, Peer Index’s CEO) talked, I became acutely aware that PeerIndex were years ahead of us in their understanding and technology for influencer analytics and mapping.”

But why the need for a social media monitoring company to invest so heavily** to address influencer analytics and community mapping?

The answer lies in the exponential rate at which online activity has been growing, and the challenge this has created to find the people, content and conversations that really matter to PR and Marketing objectives.

*I’m the founder and architect of Lissted for anyone who doesn’t already know me.
**£10m looks to represent around 10-15% of Brandwatch’s value based on filings relating to its most recent finance raising in May 2014.

A world of ‘pretty noise’

The key social media monitoring platforms (including Brandwatch) were conceived and designed in the mid-to-late Noughties when we had a fraction of the online conversations we have today. Even by the summer of 2008, Facebook had only reached 100 million users (versus 1.35bn now), Twitter had a measly 10 million (versus 284 million now) and Instagram didn’t even exist.

In this relatively quiet online world the platforms didn’t need to do much to address what I think of as the ‘laws of social listening‘. A few simple metrics – like number of Twitter followers – and keywords were often enough to find who, and what, mattered most.

As the scale of online conversation has grown in the last few years these platforms have invested in an arms race of engineering to try and keep pace with the demands of multiple sources, processing and storage. Meanwhile at their heart they mostly still treat ‘listening’ as a purely data driven exercise, continuing to use similar metrics of now questionable worth, combined with increasingly complex Boolean keyword strings, to desperately try and filter it.

This has resulted in what I call “pretty noise”. Beautifully designed front end applications with graphs, charts and word clouds that look wonderful, but often tell you very little of real value, or worse can be genuinely misleading.

Because real listening, and the insight that comes with it, requires an understanding of people and communities, not simply data mining.

Noise doesn’t equal influence

At the same time as social listening platforms have been struggling in a Canute-like fashion with this vast wave of conversation, we’ve also seen the rise of the ‘influencer’ – someone who is judged to have the potential to exert higher levels of influence over others.

Such people have always existed of course, but social media and the wider online world has increased the ways in which this potential can be earned, observed and utilised.

Again, a plethora of tools and platforms have been created to try and help users identify these influencers in relation to their brand, product or industry. The majority of them start with who produces online content around your chosen keywords, and then look at the reaction they generate before deciding who ranks highest.

Unfortunately, these tools generally suffer from the same weakness as the social listening platforms. The scale of conversation and online activity is so great that they often equate noise to influence.

And even when these tools are successful in identifying truly influential and relevant content creators, they’re still of limited use, as creating content isn’t the only way to be influential.

They may help me identify candidates for outreach purposes, but it certainly doesn’t follow that their answers will be relevant to other key Marketing and PR activities such as:

ranking higher in search;
organising an event with industry leading figures;
understanding how my competitors are behaving online;
reaching more relevant people with my own content; or
identifying who I should target with my advertising.

True, there may be some active content creators in a particular field who will indeed be relevant no matter what your objective. For instance – if you’re looking at a list of UK PR influencers that doesn’t have Stephen Waddington near (or at) the top (as I was the other day) then I would seriously question whatever approach they’re using.

But mostly, this combination of noise driven methodologies and varying objectives has created a situation where users are asking questions of these tools, and it’s often just dumb luck if they get back the answer they really need.

It’s all about Community

So how do we address these two problems?

Effectively listen to social media sources to find true insight in a real time world.

Identify the right people and organisations depending on our objective.

The solution lies with understanding communities and the contextual relevance they provide.

It’s about identifying, observing and listening to enough of the key members of a community, particularly the ones who are authoritative and knowledgeable.

Lissted approaches this challenge in a very different way to Peer Index, but we do agree that if you can understand the makeup of communities relevant to you, everything else starts to fall into place. This is because the very people, content and conversations they are paying attention to are the ones that are likely to matter most.

We call this “Superhuman” social listening. A host of people who really know their stuff helping you to filter the online world and discover who, and what, really matters to your PR and Marketing objectives:

Reputation management: they’ll highlight important stories and conversations about your brand before most people get to hear about them.

Outreach: they’ll tell you who the content creators are that drive influential conversations, not just noisy ones.

Amplifying your content: they’ll tell you who the curators are that identify and share influential conversations.

Improving your search ranking: they’ll tell you the domains that they trust, which are therefore likely to be the very ones that Google will trust too.

Targeting your advertising: they’ll help you identify the people most like them and who share their interests.

Event organising: they’ll tell you who are the most recognised people in their field.

Real time marketing: they’ll help you identify what’s really getting relevant people engaged.

And so on……

The future

The critical element is the ability to identify these communities accurately. To find the right people to listen to. This is why we’ve spent the last two years developing Lissted’s real world approach to identifying relevant communities and why I believe Brandwatch have invested heavily with this acquisition to try and achieve this too.

I expect we’ll see a lot more activity around this challenge in 2015 and beyond as others in the social listening industry recognise the need to address the elephant of noise in the room.

Beta invites

We’re currently running a private beta of Lissted’s latest community analysis tool. If you’d like to get involved then drop me an email, adam@lissted.com.

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