A version of this piece was published in Marketing in 2008
There is a research group out there that’s so large, you can’t get it in to the biggest viewing room. And it isn’t bothered about what you think, so it doesn’t flatter you or attempt to double guess you. And you don’t need to feed it crisps and coke, or travel to Watford to watch it.
Digital media are mostly regarded in terms of their capacity for carrying our messages – the £2.8bn that’s spent on online media, and the thousands of websites that this funds are a direct product of this.
But for all the effort that goes in to advertising on the internet, a tiny fraction goes in to using it as a research tool - perhaps a reflection of the fact that as marketers we’re often better at talking than we are at listening.
In the last two years we’ve understood something new about the internet. That it’s true power comes not from the ability it gives brands and companies to speak directly to consumers, but from the power it gives consumers (or people, as they like to regard themselves) to connect to each other.
And as these billions of conversations have unfolded, marketers have started to understand that there is value in listening in.
Social networks, blogs, forums, twitter (a mobile social tool) and review sites are bulging with conversations that people are having about brands – often referred to as buzz. Sometimes they’re saying nice things about you, often they’re brutally slagging you off. But the challenge for marketers is to make sense of what’s being said – to understand who’s talking, and the significance of those conversations.
There are lots of tools available – paid-for ones like Onalytica and Buzzmetrics that give us breadth of coverage, but also dozens of free tools including Blogpulse, Technorati, Icerocket and Tweetscan.
Between them, these systems allow us to build up a picture of what people are saying, who’s saying it and how much. But knowing what to look for isn’t enough. The sheer volume of data out there means we have to know what to ignore too – someone criticising a brand in a blog that only two people read is probably not a priority.
So typically, a researcher is looking at three dimensions of buzz – Influence, Popularity and Sentiment. Flemming Madsen from Onalytica explains the difference between Influence and popularity well – in the area of childhood obesity, Jamie Oliver is popular. But if you want him to reflect your views, you’ll find it hard to get to him. He gets his information from the National Obesity Forum – in this context, it’s the forum that are influential – get to them, and you might get to Oliver.
Sentiment is harder. Although there are tools that measure this, their results can be unreliable, because at the heart of it, they’re measuring humans – and humans aren’t consistent. A teenager describing something as ‘bad’ can mean the exact opposite, and when you get a post like this (genuine one):
THIS W3B SYT IS GUD BCOZ T3ER3 IS LWDS OF P3OPL3 THT R G3TTING BULLI3D SO B3AT TH3 BULLI3S ND I AM GUNNA DO A PAGE ON MY W3BBY ABOUT IT CYA
Any machine is going to struggle to make sense of it. So you also need humans to comb the data, and distill the sentiment from it.
Put this in place, and you’ve got a thermometer of great sensitivity, which you can use for long-term projects like NPD and brand tracking. But the real power of this technology comes from its immediacy – the almost real-time feedback you can get from the world.
Gauging the impact of new TV campaign, an early-warning system for PR outbreaks, a customer service listening post – these are uses that buzz marketing techniques are already being put to.
So despite the £2.8bn we spent last year on talking to consumers online, we may yet discover that the real value of the internet to marketers is not in the voice it gives us, but the ears.