Challenge 1: Volume
"Inundated with spam or searching for needles in haystacks?"
Dealing with large volumes of online consumer discussion creates different challenges according to what you are trying to do.
The most obvious volume-related challenge presents itself if discussion about you is extensive.
Maybe you’re an innovative business which has just launched a highly successful viral campaign. Or perhaps you are a major software firm or consumer electronics manufacturer releasing a new version of a widely used product. Or maybe you’re a popular music artist or TV series with a large – and vocal – fan following. In these cases just staying on top of the buzz that occurs directly about you every day is difficult.
In our experience, the number of clients facing the keeping-up challenge is relatively low. It happens, but not all the time. However, when it does happen, it takes expertise to deal with it.
The reverse of the keeping-up challenge presents itself when there is a lot of buzz about you, but you are looking for specific details which people rarely discuss.
Imagine you’re the producer of a popular TV series, and rather than wanting to know everything people are saying about your show, you’re interested in how viewers respond to a particular character or story line. The challenge in this case is to sift through vast amounts of data to identify only what is relevant, and you need to make sure you don’t miss anything, because what you are looking for is rare and therefore highly valuable.
For instance:

This buzz cloud shows the most frequently used words in US discussion about the Harry Potter and the Half-Blood Prince trailer. Most people responded very generally to the trailer, talking about how they “couldn’t wait” to see what “looked like” an “amazing” and “awesome” movie. Identifying discussion on how viewers interpreted particular scenes involves sifting through vast amounts of buzz, but it means we can investigate what consumers think of the cave setting and the zombie-like Inferi characters, for example.
A similar problem occurs when discussion about you is relatively low, but difficult to identify because there are large amounts of buzz out there on closely related topics.
Let’s say you’re a detergent manufacturer with a brand name which is also a commonly-used noun (or even the name of another, entirely unrelated, brand). Locating discussion which actually refers to you rather than simply mentioning ‘your’ brand name in a different context can be a trying task.
In our experience, the identification challenge is very common. For example, it often arises when popular brands launch updated versions of existing products. For these brands to understand consumer reactions, they need to be able to separate buzz about the new version of the product from buzz about previous versions.
Sometimes there is just no buzz out there. We used to say you could never research buzz around washing-up liquid, because they are simply too commonplace in people’s lives for anyone to talk about them. As it turns out, we were wrong about that (people do talk about washing-up liquid - just not very much).
The overall volume of online discussion continues to grow and today there are fewer and fewer instances of a brand, product or service generating no buzz at all.
Still, there are some scenarios where there is generally little or no buzz and it's useful to remember when this occurs: