January 2011 Archives

Hidden Costs of Listening Silos

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bills.jpgFirst, listen. Listen first. First, listen. Getting redundant yet? Is that also the way you've set up your own listening activities?

I recently talked with someone whose company has social media responsibilities divided among several executives. Each has a listening arrangement in place: one has an internal team, and the others have outside agencies doing the work. The kicker? All of them may be using the same platform.

I'm thinking there are some opportunities to rationalize costs there.

So here's a deceptively simple question for you:

How much are you paying to maintain multiple, independent listening posts?

  • How many times do you pay for the same software?
  • How many times do you pay for the same data?
  • How many times do you pay for the same analysis?
  • How many people are handling the same posts?
Getting started is great, but the pilot project approach has costs. Are you ready to manage yours?

Photo by Andrew Magill.

How to Present at AnalyticsCamp

I got a very nice note from out of state—someone from a social media analysis company who wants to present (we prefer to say "lead a session") at AnalyticsCamp. I told him the super-secret process that's required to get your session into our unconference. If you promise not to tell anyone (shh!), I'll share it with you, too.

Here's how it works:

  1. Register for AnalyticsCamp.
    It's free, but please cancel if you're not going to make it; we use the total for food planning.

  2. Add your session proposal to the list.
    Just copy the format used by the existing entries. Please don't plan the session around a demonstration of your company's product. Selling doesn't sell in this setting.

  3. Show up on March 12th.
    We'll do the BarCamp session pitch thing at the beginning, so you'll get a chance to pitch the crowd on coming to your session.
If you want to participate but don't want to lead a session, skip step 2. Yeah, it's a demanding process. :-)

AnalyticsCamp is, at heart, a local event, but we're flexible about the interpretation of local. Despite icy roads that scared off some closer folks, two participants drove nine hours from Nashville to be with us last year. If analytics (any flavor) is your thing, join us. You'll meet interesting people, and you might just learn something.

AnalyticsCamp registration is open, and 120 people have signed up so far. We'll update the details on the wiki as we get closer to the event.

penguins.jpgCustomer ratings are useful things, aren't they? They help when you're making a purchase decision, even if you end up disagreeing with the rating. And they're showing up more and more—in the form of stars, likes, favorites, and thumbs-up buttons showing up everywhere. Naturally, all this structured data makes us want to analyze it, but what do the ratings really mean?

What if people have figured out that these scores do something, and they're trying to make the algorithms work better for them?

Tipping the DJ
Here's an easy example. Pandora is a wonderful service. Tell it the name of an artist or song that you like, and it starts playing music that you'll probably also like. The new list becomes a "channel" that you can listen to any time you like.

As Pandora selects songs for you, you can rate the tunes with thumbs-up/down buttons. Thumbs up? You'll hear the song more often when you listen to that channel. Thumbs down? Never again. If you're going for a particular sound, you might give a thumbs-down to a song that you like, in order to remove it from that channel.

Before you analyze the ratings (assuming you could get the data), what do they mean? In this context, it does not mean "I like/don't like the tune." It means that the user wants to hear more or less (none) of that tune on this channel. If you create a quiet music channel, you might give your favorite artist/song a thumbs-down, because it doesn't fit with the channel.

iTunes does something similar with its option to play higher-rated songs more frequently in its shuffle mode. But its five-star ratings are global within a user's playlist, so it's trickier to fine-tune individual playlists. Still, more stars don't really mean "I like this more" if the system interprets them as "play this more often."

Playing favorites
Media-sharing sites (YouTube, Flickr, SlideShare, and the like) give users the ability to mark an item as a "favorite." Which means the person really, really, likes it—or wants to be able to find it again. You'd need to do usability testing to figure out how people use the feature. My take is that favorite is like friend: overused and meaning something different in the online context.

Ever favorite a tweet? Was it really one of your favorites, or is that just how Twitter's bookmark feature works? Thought so.

Like a discount?
Who doesn't like fans, right? They're almost like friends. But a survey by ExactTarget and CoTweet found that 40% of Facebook fans are there for discounts and promotions. Maybe they're a lot like Facebook "friends," in that the label doesn't really describe what's happening.

Sometimes, a star is just a star
I'm more inclined to believe the product ratings people give on shopping sites, though there's always the risk that a "customer" review is from an employee (high score) or competitor (low score). Usually, the 5-star scoring system seems to be what it claims: people's opinions of the product.

Still, it's worth considering whether product ratings might be considered in sites' recommendation engines. I know that Amazon, for example, recommends products based on things you've bought or looked at, and I don't always want to see more of what I just bought. I don't know if product ratings figure into the mix, but what if people think they do? How does that affect your interpretation?

Photo by Adam Arroyo

Buzzword bingo bonus: use these words in a sentence: social, ratings, sentiment, influencer, customer, tomato.

WMSN1210.pngI've been interested in things international a lot longer than I've been blogging international topics (just look up careers in international affairs). At work, that translates into tracking down companies globally; it's one way my research is different. So when somebody takes a good look at social media patterns beyond the US, I'm usually interested.

Global view

Regional view

Country-level view

If your view has been dominated by US trends, you should be interested, too. As it turns out, people are doing this stuff all over the planet.

Some lists are more incomplete than others. What sources of regional or country-level information on social media usage have you found?

About Nathan Gilliatt

  • ng.jpg
  • Voracious learner and explorer. Analyst tracking technologies and markets in intelligence, analytics and social media. Advisor to buyers, sellers and investors. Writing my next book.
  • Principal, Social Target
  • Profile
  • Highlights from the archive


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