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Tony Byrne

Small Data Beat Big Data In Election 2012

The Obama re-election machine was really about small data--and enterprises can learn from that.

Social Studies: Obama vs. Romney
Social Studies: Obama vs. Romney
(click image for larger view and for slideshow)
Even before polls closed Tuesday, some observers were describing the Democrats' vaunted "ground game" -- a.k.a., get-out-the-vote, or GOTV -- as a victory for big data.

Doubtless, the staff of both presidential candidates performed some deep analysis of large datasets. Having participated with my family in GOTV efforts for the past four quadrennial U.S. elections, I have a different take: The Obama re-election machine was really about small data.

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Small Data Writ Large

Compared to previous years, what was fascinating about the Obama effort this time was the intense effort on data curation at the individual record level. In past cycles, registration and voter data seemed like a read-only Excel sheet: You got a well-thumbed, printed list of voters to call or visit with some basic info about them and -- if you were lucky -- some handwritten notes from previous canvassers. This led to a lot of duplicate effort, frustration and miscommunication.

This time, we saw a much more systematic effort to refine and annotate each record iteratively, to match message and approach to where someone lay in their decision cycle. When someone was "touched," their record got updated. If the previous canvasser uncovered a preference for Obama, the next canvasser worked on intent to vote. And if that succeeded, the next canvasser, closer to Election Day, worked to make sure the voter had a practical plan for voting (a key predictor of actual voting, especially among young or distracted voters). A premium seemed to be placed on obtaining mobile phone numbers, updated address information and names of additional potential voters in the household (typically adult children living at home).

[ For more on how the campaigns used big data to chase voters, see Election 2012: Who's Winning Big Data Race? ]

An enterprise data manager would recognize the basic steps:

1. Validate
2. Clean
3. Annotate
4. Enrich
5. Adjust Outreach Message
6. Repeat

To be sure, this was not happening in real time, and it wasn't mobile-enabled, at least from what I saw. A lot of handwritten annotations got updated digitally each evening for reprinting the next day. But the whole process had to be simple and methodical enough that many thousands of undertrained volunteers could master it. I caught a brief glimpse of the packaged software underneath all this, and it was no great shakes, at least from a data-entry standpoint. But with motivated actors, perhaps that didn't matter.

Another notable improvement came in geolocation. For canvassers on the street, more precise maps and better choreography of target lists with a sensible path makes for a more efficient trek. Maybe Google's API will prove another underrated key to this election.

Some Caveats

I should add that this process was by no means foolproof, and every Obama volunteer can tell stories of mistakenly knocking on doors of confirmed Romney supporters, although overall it struck me as a noticeable improvement over what my family saw in 2008.

Also, I'd guess the Romney campaign was similarly taking a more sophisticated, CRM-like approach this cycle as well, although they don't seem to have staffed it as fully. The human element is critical here.

And let's not underestimate content: sophisticated GOTV only works if people are already predisposed to voting for your candidate.

Small Data and Your Enterprise

Still, there are many lessons here. That data quality and relevance matter. That improved execution may compensate for diminished prospects. Perhaps most importantly, that some data is too important to be left just to machines. In the end, the data was big alright, but it took live human beings to realize its value, one record at a time.

As someone who evaluates marketing automation suites -- which try to funnel prospective customers automatically through a similar decision process in the digital world -- it also got me thinking that the current emphasis on sophisticated campaign design over sophisticated data management in that marketplace seems a bit misguided.

Of course, your enterprise probably has to hit targets four times a year, rather than once every four years, and most of you cannot call on passionate volunteers to help. But I wonder if there aren't more lessons to draw here. What do you think?

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