Howard Kaushansky of Umbria Communications discussed what he calls a 'rigorous blog decomposition process.'

AOL is another company that's making significant use
Text mining is one of the most powerful tools that AOL is currently using to generate their WOM understanding.

1. Outbound word of mouth - WOM is generated by someone
2. Inbound word of mouth - WOM is recalled by the recipient

The concept of Net Promoter has been touted quite a bit today, and AOL is yet another example of a company that's covering this metric, but it's not without its faults. It only measures the positive side of the WOM equation, not the negative. Essentially, the Net Promoter concept explains the phenomenon of a customer's "likelihood to recommend' your service to others

AOL has 4 basic leave behinds on their WOM measurement tactics:
- Examine outflows and inflows
- Negative WOM is more impactful than positive WOM
- Some product features generate disproportionate WOM
- Net promoter does not measure all WOM, just positive (still need another measure to capture negative WOM)

Steve Rubel has a good point about multimedia content and it's lack of 'scanability' and how we could measure any and all "non-text" content for WOM. Right now, Umbria (and I assume others) are working toward audio-to-text and other tools.

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