When I was fourteen I started attending computer classes at my local community college, one of the basic theories was whether computers would ever become self-aware. This fascinated me, at that time I was thinking that all of the sci-fi books I’ve read could possibly come true. In hindsight, that would have also meant the enslavement or extinction of the human race but when you’re fourteen that isn’t on your mind. As we began to talk about every element of what makes us human versus mechanical elements the sense of hearing was discussed. The professor began to talk about how as humans we have the ability to hear everything but can essentially tune out what is not relevant to us at the current moment. Computers have a much more difficult time to distinguish which sounds are relevant and then to eliminate the irrelevant sounds from current processing. This has always fascinated me, we innately understand what to do and how to do it. This got me thinking about the social web, of course, we are all listening to who’s talking about our brands or keyword interests but that still creates a lot of noise.
It’s funny that even in our attempts to filter out what matters most to us we still find ourselves inundated with useless noise requiring us to separate the chaff from the valuable information. I began looking into what I do on a daily basis for listening services and general search alerts, even though I’ve been able to reduce a lot of the chatter I still find myself passing by or looking over the relentless data because it is no longer relevant. Then it dawned on me that even though I was effectively eliminating the noise I was neglecting to adjust for constant relevance. Relevance is much more difficult to monitor and adjust than signal-to-noise ratios. Just like hearing, we don’t listen to the same aspect of our surroundings all of the time, we are still looking for what is relevant for us. Sometimes that means widening our scope to hear it all and sometimes that means pin-pointing our focus to only hear one specific thing.
In the world of social web listening a big factor is being able to cut down the signal-to-noise ratio and while this is an ever important aspect to daily business life it isn’t where we should stop. Relevance changes for many businesses on a daily basis, you may be seeking one segment of a market but then your competitors make a shift and that changes things for your business, this makes new things relevant and others obsolete. How often are we adjusting what is relevant? Not just what is keyword is relevant.
Being able to focus what people are saying in your most obvious categories is great but is that relevant to your customers. Is the industry creating the buzz and traffic of keyword searching or is the customers? To give an example, for our industry of design, I could search for people wanting to change designs but the problem is I have to filter through the chatter of every other design company talking about how customers should be using design in their business. This almost eliminates the value I would receive by that type of keyword searching and filtering. If I adjust my relevance to find people who are seeking to set up their own website or who are commenting about industry news sites that cover design then I am instantly limiting the amount of noise and increasing my relevance factor. This allows me to find the exact type of potential customer rather than the hundreds of thousands of people who are simply talking about design and websites.
This is the difference between listening and finding relevance amongst your data.
