Tag Archive
Abraham Harrison Advertising Bing Blog Brand Business Business and Economy chris abraham Content marketing Converseon Customer customer service Digital marketing Facebook Google IBM Internet marketing internetmarketing IPhone linkedin marketing Marketing and Advertising Microsoft Online Communities organic search pinterest Promotion public relations search Search Engine Marketing Search engine optimization Search Engines Searching search marketing SEO small business social media social media marketing Social network twitter Web analytics Web search engine Website Yahoo YouTube
Marketing surveys are wrong
Photo credit: Wikipedia
Yeah, I know it is a sensationalist headline. Sue me. I am reacting to everyone constantly telling me that social media listening provides “wrong” information. They do. Every technique that purports to provide insights into markets has some kind of error in them because this isn’t an exact science. But to pooh-pooh social media listening on the grounds of inaccuracy is just as dumb as my headline that takes to task all market research. What’s really true is that different research tools have different strengths and weaknesses and we should understand them so that we use the right ones for the right purposes. Read the remainder of this entry »
The social media listening market is maturing
WI: Milwaukee phone bank and labor walk, September 11, 2008 (Photo credit: aflcio)
Monday, I talked about the Convey API, a new offering from Converseon that earned DataWeek’s Innovator of the Year on Social Media. My point Monday was that the Convey API allows the people who need accurate sentiment analysis to pay for it, even though monitoring platforms are getting cheaper and cheaper and not offering that kind of accuracy. But that’s only half the story. To me, the bigger opportunity for accurate sentiment analysis is how it can be used for entirely new applications that go way beyond social media monitoring. Read the remainder of this entry »
Do you need accurate sentiment for social media listening?
Photo credit: Wikipedia
Most of you know that I serve as Chief Strategist at Converseon, so I spend a lot of time thinking about sentiment analysis techniques for social media listening. My background is in text analytics, so I am no stranger to technology solutions for this problem, but I’ve long felt that technology is only part of the solution to the vexing problem of social media sentiment analysis. The question is, how accurate do you need sentiment analysis to be? Sure we’d all want to know with 100% accuracy whether customer comments about our company are positive or negative. But are you willing to pay for it? Read the remainder of this entry »
Why enterprise digital marketing can’t be completely in house
Image via CrunchBase
Chris Abraham wrote a great post on Friday called “Why you shouldn’t bring your social media (completely) in house.” He made a lot of great points in that article and I want to come back at it again in this post. My experience is that large companies can’t ever bring their digital marketing completely in house. I know that my opinion might be suspicious, because I am Chief Strategist at Converseon, a digital agency, so you might expect that I have every motivation to advise you to work with consultants. But I actually learned this lesson when running parts of IBM’s digital marketing in house. I found that it wasn’t possible for me to bring everything in house. Read the remainder of this entry »
How can you pick the right social media tool for your situation?
Photo credit: Wikipedia
The other day, I posted about choosing the right social media listening tool for the right job. I usually don’t post again so quickly on the same subject, but I got so many questions that I thought I needed to. In my last post, I made the point that simple (and free) engagement tools (such as Hootsuite) work just fine if all you want to do is to monitor for crises (and you’re OK with watching many irrelevant results fly past as long as you eyeball the correct stuff). Any use of social media that is good enough for a person to look at individual social conversations can get by with just these free tools. But if you need to look at aggregate data to do market research or it is too expensive or error prone to have a person look at every tweet to find the relevant ones, then you need a better tool–one that incorporates text mining and probably that uses machine leaning technologies based on human-analyzed training data. Read the remainder of this entry »
