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Convincing the unconverted, part 3

For technique #3 of “convincing the unconverted on communities,” I thought I’d talk a little about:  The Data/Evidence driven approach.

#3:  The Data/Evidence approach

Unfortunately this might be the toughest, but at the same time the one with highest likelihood to succeed within a corporation.  What data/evidence to use depends a lot on the following:  

• What industry you are in

• What organization you roll up to (Marketing? Product development? Support? Sales?)

• What communities you have today (is there any baseline data?)

The truth is, there is a community today for almost everything; it’s just that you might not host it.  That might constrain how easily you can collect data from it, but that doesn’t mean that it isn’t very valuable to your users. 

Risk:  Don’t let measurement define your strategy…let your strategy define your measurement.  Sounds obvious, but too often it is not.

The following are some thoughts on Data and Evidence that help build the story for communities.  I’m not saying all this is easily measured or completely measurable at all, but these are some of the areas I’ve thought about.

1. Satisfaction and likelihood to recommend – Every company I know does something to measure these indicators (satisfaction being rear-view and recommend being forward looking).  How do your community users opinions differ from non-community users?

2. Product insights – Are you collecting product insight through the community conversations?  Can you compare that to other mechanisms?

3. Outreach – Are your communities extending your brand or helping you reach users (potential users) you never reached before?

4. Credibility – Mastercard model – the independent community voice compared to your “corporate voice” is “priceless”

5. Image/”humanization” – Your chance to demystify your company.  You can “put a face” on your company through bloggers and/or content that is just downright unexpected, and GREAT.  Example:  Check the ReadMe.txt on Channel 9: http://channel9.msdn.com/about.aspx.  My favorite is #8:)

6. Community “Health” – Unique users, return rate, average days active, answer rate, rss feeds, etc 

That’s a good start, I’m sure I’ve missed some good ideas I hope others will add.  I guess I would note that every metric is inherently limited and taken in isolation could really lead you down the wrong path…so check your assumptions regularly (ask your users!).

Next up:  “The Assumptive Close” – a personal favorite

Sean

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