December 13, 2017

Helping PR pros make smarter decisions

The Buzz on Buzz Monitoring

The Buzz on Buzz Monitoring

Working for a startup, I understand the importance of following any conversation relating to your brand. A hit on TechCrunch, GigaOm, Mashable, and the like can be the difference between internet obscurity and recognition. Tools like Google Alerts, Technorati, and IceRocket have helped automate the process of monitoring mentions in blogs, but a new class of service has upped the ante, promising to apply quantitative metrics to the seemingly subjective art of finding out whether your brand is wired or tired.
This week, via TechCrunch, I was introduced to a service called Scout Labs. Like BuzzMetrics, BuzzLogic, and Nielsen, the service offers brand managers a way to see how their offering is being perceived and discussed in the marketplace. Rather than simply following a keyword-based alert, Scout Labs gives the brand police the ability to see trended “sentiment data” based on a continuum from negative to neutral to positive. It then plots the hits over time and by ranking. To do this, the service looks at the blog discussing the brand and rates how much influence the blog has.
**Implicature**
If you read the preceding paragraph and said “that’s nothing new,” you’re right. All of the monitoring services take influence, keyword density, frequency of post, and reach into their equation. However, Scout Labs is going one step further by acknowledging the fact that there’s something out there called sarcasm. They then give the brand manager the power to change the rating when a quote like “this service is really earth shattering” when it’s in the context of: “I can’t believe what a complete waste of time xyz startup really is. It’s a complete copy of everyone else out there, with zero new features. Yeah, this service is really earth shattering.”
The ability to identify sarcasm is what’s currently lacking in the buzz monitoring space. When humans read blog posts–in context–it is easy to separate compliments from cutting remarks. When the machines attempt to quantify tone, that’s where the robots fall short. That brings me to one of my favorite new vocabulary words (new to me, at least): implicature. Implicature is when you say one thing, and regardless of what you say literally, meaning is derived from the statement. For example, if I said “I went to the store and saw Wayne Newton”, most people would think that I meant that while at the store, I bumped into Wayne. When taken literally, the two events could be completely unrelated. The same goes for sarcasm. I could say one thing and mean the polar opposite. These subtleties in language make the machines short-circuit.
**They’re Bashing My Product! Sick ‘Em!!!**
Let’s pretend for a second that the good people behind these monitoring services have so fine-tuned their technologies that sarcasm is detected at a 99 percent rate. They’re now able to deliver on their promise, and brand managers are able to detect all mentions (positive and negative) of their stuff. Now what? The big question is: once you have the data, what do you do with it?
Is this just another way to automate the kind of mindless pitching Chris Anderson highlighted in his now-famous anti PR agency post? Will companies simply craft stock responses to any criticism, then email bloggers with talking points? The question now becomes “now that I have all this information, can’t I just bomb bloggers with template defenses? Since we’ve now automated the detection and rating of how people feel about us, shouldn’t we now be able to automate our response to them?”
I posed this question to bloggers with the thought that I would get responses from two distinct and divergent groups: those that saw corporate attention as validation for writing and those that thought “hey, corporate suits: stay outta my blog, maaaan.”
Well, I got some comments:
[**Danny Sullivan:**](http://inmediablog.com)
“Can’t help but feel that technology still has a long way to go before content analysis like this can be done effectively by software. Especially for the blogosphere, which is full of sarcastic and humourous comment and must present a significant challenge to a piece of code. But I hope I’m wrong!
On your last question, I don’t think that anyone should feel any different knowing that their blogs are being read by companies. Bloggers know that when they write something, it is now in the public domain and there for ALL to read. And that includes the evil corporations.
Just as every blogger has (or should have) a right to freedom of expression, it is everyone else’s right to be able to view that content and pass their own judgement on it.
As an individual, I may read several blogs on a topic to build a perspective on a subject… companies are entitled to do the same to help build a picture of how the market views them. As long as we don’t see an uptick in bloggers having mysterious accidents, I think it’s safe to say buzz tracking doesn’t pose much of a threat.
Let’s be honest, if people feel uncomfortable about their blogs being monitored, then why are they writing them to begin with?”
[**Katie Delahaye Paine:**](http://kdpaine.com)
“If you can find 10 PR people who are happy with this after a year or two, i’ll be impressed. I constantly get the “what do you do with the data question.” You just can’t do this stuff entirely with computers, you need humans.. Reliable, trained, efficient knowledgeable and economically viable humans. (Okay, that’s a plug for our folks up in Berlin, NH) But If microsoft doesn’t trust computers to do this stuff why should anyone else?”
With that, I thought I’d ask someone from Scout Labs to hear their opinion. And to be honest, I was really impressed, as I thought I’d just hear a polished quote. Instead, I had a great one-on-one conversation with Jennifer Zeszut, CEO of Scout Labs. She said:
“The PR issue is a tough one. We are trying to facilitate a revolution around true relationship building between companies and their customers and influencers. We will say it over and over, but the truth is that our tool (which will facilitate conversations) can and will be misused by people who don’t get it. When they get flamed, they will think that our service isn’t working. But when the feedback loop is so immediate – and through our tool, you can actually see really important people go negative on you and become brand detractors – then I think they will learn pretty quickly.”
It’s a good point. It’s one thing to know how you’re being perceived, and another to find the right way to act on that perception, positively or negatively. And for now (and hopefully until I’m well past retirement age), that distinction is a wholly human one. I’m comfortable letting the machines tell me who’s talking smack about me, but I’m not sure I want them having a conversation on my behalf. I’ll do that part.
*Nathan Burke is the Web Community Evangelist for Boston area tech startup [matchmine](http://matchmine.com). He also co-authors [Blogstring.com](http://blogstring.com).*

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