Posts Tagged ‘audience’
Influence Mapping: The Maverick Cop Way (Part 2)
Wednesday, June 18th, 2008
The story so far: In the last episode of Influence Mapping: The Maverick Cop Way, we discussed a simple process for organizing what you know about influencers. We discussed briefly the decision making unit model we were using, our (very broad) definition of “influencer”, and showed how we can score them quickly for the three key variables reach, authority, and “ease-of-use”. At the end of the process, we found ourselves with something like this:
Now we’re going to go a little further, and show how we can map the relationships between the various stakeholders. This is the second and final post, and it may introduce a lot more that’s new to you. But stick with it – it might be worth it.
What you’ll need before you start
You’re going to need UCINET, a programme that analyses matrices and networks. It comes along with another programme from the same publishers (Analytictech) called NetDraw that draws networks. You’re going to want both. UCINET costs $250 for a corporate license, but the first 30 days are free. NetDraw is a free download.
They only work on Windows, but I’ve not experienced any real problems running them on a Mac using Parallels.
1. Create a matrix
Take your list of influencers (as per the table above), and add in the four key players from the decision making unit; the initiator, the decision maker, the purchaser and the end user.
Paste them down the left hand side of your table, and along the top edge, as in the illustration below. Excel’s Edit > Paste Special > Transpose command is useful, not to say essential, when you’re doing this. At the end of the process, you should have something that looks like this.
The rows show the influencers, the columns show those being influenced, the targets.
Because we don’t think that an influencer can exert influence themselves we drop a line of zeroes down the diagonal. This is more to help us navigate than anything else. Don’t feel you have to do this.
2. Fill in the matrix
Go through the rows one by one, deciding if a given influencer has any effect on the targets (the column headings). So for example, we know that the initiator influences the decision maker, and so on. But knowledge of the end user may well influence the decision maker, too. So – for example – when I’m choosing my dad a computer, I take into account the fact that he’s not so au fait with technology, and that if he can’t use it, he’s going to call me to ask for tech support. So I’d better choose something that will limit these calls.
At the end of the process, you’ll end up with something like this (although probably much bigger). It can take quite a lot of time to go through this process – this may be one of those times when you want to work with a partner to bounce the ideas around.
Tags: audience, influence, mapping, networks, planning, public relations, tool
Posted in how to, influence | 2 Comments »
how to: perform free Facebook audience research
Tuesday, November 20th, 2007
Facebook provides a free, useful way to interrogate its database of users. This can be invaluable whether you’re actually thinking about planning a campaign on Facebook, you’re looking for some quick-and-dirty audience research, or you just need some corroborative detail.
So where’s this tool? It’s all part of Facebook’s Social Ads platform. Here’s how you do it.
Step 1
Go to http://www.facebook.com/ads/create/. You don’t need a Facebook account to do this.
The page may look a little different if you’re already logged in, or if you’ve created something using the platform in the past.
Type in any URL. It doesn’t matter.
Step 2
Now this is where it really gets interesting. Play around with the various drop-downs and check boxes. How many Australians aged 25-30 have registered accounts with Facebook? How many of these work for the Macquarie Group?
Or ask Facebook how many of its UK users enjoy peanut butter?
If you have a Facebook account yourself, you’ll know that there are lots of places in your profile where you can answer questions.
So for example, it’s perfectly possible to dig around and find out what portion of the Facebook audience say, likes peanut butter enough to feel that it’s important that they tell their friends.
Or which age group most (publicly) enjoys Curb Your Enthusiasm.
Caveat 1
We’ve seen that (at May 6, 2008) there were around 9.7 m registered UK accounts aged 18+ (or approximately 16% of the total 2006 UK population). But – of course, we can be more granular than that, and look at specific cities. For example, we can see that there are around 2.5 m users based in London.
Of these users, 788 K are male. This should raise a few suspicions, because at first glance one might infer that the remainder (2.5 m – 788 K = 1.7 m) of the users are female. This would mean that (in London, at least) female users of Facebook outnumber male users two to one.
But when we add women into the mix, we see that women and men combined account for only 1.7 m Facebook accounts in London.
What gender are the remaining 900 k (2.6 m – 1.7 m) users?
Facebook can only tell you what its users have shared. If they have chosen not to share their age, gender, location, etc. you can’t see it. Double check your numbers, and bear in mind that the more granular you get, the more room there is for error.
Caveat 2
It appears that there are around 140 people aged between 18 and 19 on Facebook who like peanut butter enough to tell their Facebook friends.
Breaking it down a little further, we see that 40 of these are aged 18.
And 120 of them are aged 19.
Adding those numbers together, that’s 160 peanut butter lovers aged 18-19 , not the 140 peanut butter lovers we saw in the first run.
Running the exercise again confirms that twenty new peanut butter lovers haven’t suddenly signed on in the past five minutes.
There’s clearly some kind of rounding error. It seems that Facebook rounds to the nearest twenty. Bear this in mind that these estimates are intended for the purposes of estimating advertising audiences.
Tags: audience, facebook, research
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