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« Join me for a free Groundswell Webinar April 3, courtesy of Lithium | Main | Some early Groundswell coverage »

March 31, 2008

Weekly social data chart: Small-business owners

by Josh Bernoff

Today we introduce a new feature – once a week, on Mondays, we’ll share a data chart from Groundswell or from our research, and talk about its significance for social strategists..

Our interactive social profile tool is great if you want to profile your customers by country, age, and gender. But since we’ve collected our data globally using the same social technology questions, we can profile nearly any group of consumers, anywhere. (Here's a quick explanation of our social profile system and the groups that make it up.)

For our first data chart, we’ll examine the Social Technographics Profile of small business owners. (This is from the case study for Constant Contact, from Groundswell Chapter 7.

groundswell figure 7-3

If you’re marketing to small business owners, what does this profile tell you?

The first thing to look at is the proportion of Spectators (people who consume some form of social content) and Inactives (those who do no social activities at all). With 53%, Spectators, and only 38% Inactives, small business owners are significantly more likely to participate in social applications than the average American consumer. This tells us it's worth putting social in your marketing budget for them.

Second, notice that Creators and Critics are well represented among this group. The Creators among them are blogging and uploading content like video – it would pay to keep an eye on them, using monitoring services like Motivequest. The high number of Critics tells you that business owners are relatively open to responding to blogs and participating in communities. In our book, we describe how Constant Contact’s Maureen Royal took advantage of this in creating the company’s ConnectUp! community.

While there are only 17% Collectors in this group, that’s still way above average. This indicates that if you’re marketing to this group, you could potentially get some of them to join and vote in an idea community, like the one Starbucks just set up.(Voting sites are one of the indicators for Collectors). Of course, that depends on if they’re interested enough in your products, and you should remain aware the fact that you’ll get a skewed subset of your customer base.

This analysis is typical of the first step in our POST method (P for people). Once you know your customers’ profile, you can follow up with objectives, strategy, and technology.

Look for more data in this space every week. We’re looking forward to your reaction.

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Comments

Tom O'Brien

Hi Josh:

Nice post. I have a question - I know that my role in the social computing world is situation dependent. For one community I am creator, but for another I am a spectator.

Have you talked about this aspect of social technographics?

Thanks - TO'B

Social Marketing Journal

This is great! Looking forward to seeing more data and info in the upcoming weeks.

annplugged

Tom, you took the word out of my mouth, I wanted to ask exactly the same question. :)
See my blogpost on it too: http://videovoo.com/2008/03/31/groundswell-mondays-for-social-media-strategists-web-activeness-levels/

Thanks for the tool anyway.
Anna

Josh Bernoff

@Tom O'Brien and annplugged -- this is a great point and one we think about a lot.

It's valuable to know the level of activity of your customers, but no matter how active, they aren't necessarily talking about YOU.

Once you know the level of activity of your customers and why you want to engage them, the next step is to figure out why THEY might want to engage with YOU. For the most active people online, they are also the busiest already with their own stuff.

Anything else is company- and brand-centric thinking and that's deady in the groundswell.

Greg

Is this a tremendous data? Wowwwwww

Terri in Tokyo

this is fantastic, and really comes at the right time for me - thank you, and heartily subscribed!

Malcolm Kass

While I will not be as sarcastic as Greg's comment, as an ex-engineer, I am more familiar with statistics than I care to admit. My question is how these groups were formed and how possible is it to replicate this? Clustering methods? Use of Neural node techniques commonly used in data mining? I guess I am coming from the skepticism of science, for if I am going to use this information for my business, I really need to be confident that the validity of this information is internally and externally significant. Can anyone help me out? Can we get at the raw data?

Ivan in Florida

Interesting observation. Thank you for sharing.

The comments to this entry are closed.