BrandSavant

Gaining Insight From Social Media Data

What Your Brand Needs To Know About The “Social Media Caucus”

by Tom Webster on January 4, 2012

Election MG 3460Last night, my company conducted the Iowa Caucus Entrance Poll on behalf of the National Election Pool (NBC, CNN, CBS, FOX, ABC, and the Associated Press.) The results, you may already know: Mitt Romney beat Rick Santorum by eight votes. It was clear from the data, and from the actual vote count, that we were in for a long night – it was an insanely close race.

Except, of course, in social media. The “big data” being thrown off by the web told a very different story. Conventional measures of volume showed Ron Paul dominating the social web by as many as five times more mentions than his nearest competitor. A straight-up search for relevant mentions on Topsy shows the race between Romney, Paul and Santorum as…well, not much of a race. If we look at search volume (and even confining it to Iowa, which hardly any of the social measures did) it’s still a one horse race – Paul by a landslide. One sentiment measure I saw quoted calculated the volume of Romney’s positive sentiment as sixth amongst candidates.

To date, I have never seen a repeatable correlation between social media mentions/sentiment and the actual vote. Sure, you could back-test a model that weighted to correct for the Ron Paul phenomenon, but the real test is to apply that exact same scheme the next time and see what you get – after all, most of these social tote-boards also got the relative gap and order wrong for other candidates, as well. I’m not discounting the possibility that it can be done; however, it hasn’t been done and it will be diabolically difficult to do so.

In short, to date I have not been presented with a replicable model which shows, candidate for candidate, that the number of people tweeting about a politician has anything to do with the number of people in Cedar Falls, Iowa who actually got in a car, drove to a high school gymnasium and raised their hand. Can it be done? Maybe. Maybe not. I’m not pessimistic, I’m merely skeptical (in other words, don’t prove me wrong – surprise and delight me.) I do know that raw mention-counting is a long hiding to nothing.

My only point here is that in the case of the Iowa Caucus, there is an enormous gap between what people on social media say, and what people in Iowa actually do.

Now, examine that last sentence. Replace “the Iowa Caucus” with the name of your brand, and replace “people in Iowa” with “your customers.”

Do you know how big that gap is? It is knowable – as I’ve often said in this space, it isn’t a black box mystery, if you do the work. But if you don’t know that gap, you’ll never make sound business decisions from social media data.

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  • http://twitter.com/intercesseur Fabunni Consulting

    The social media results from the 2008 election: http://www.readwriteweb.com/archives/social_media_obama_mccain_comparison.php

    I am looking forward to seeing the social media comparison for the 2012 presidential election.

  • http://www.edisonresearch.com Tom Webster

    They might have called the order, but if we presented a margin like that, given the actual results, we’d hardly be in business. What if that margin were half as large? It would still look like an Obama cakewalk, but again – it surely wouldn’t have been. I maintain that all I’ve seen to date in this field has been rubbish.

  • http://twitter.com/lexx_icon LEXX GRAY

    The solution to save our economy: allow votes via twitter

    its probably the only way anyone under 30 is going to cast their ballot / actually be represented in the voter pool because who in the fuck wants to drive somewhere in the middle of the day when we’re obvs cyborgs at this point. I mean there’s no free wifi in that gym is there? And definitely no Dunkin’ Donuts. 

  • http://twitter.com/148 Anthony Hamelle

    I’ll agree with you, no reliable social media-based research solution has been found to date, however with some attention to details one can get closer to interesting trends, if not representative. For instance if you choose to look at the search volume in Iowa only in the last 30 days, you still find a strong bias in favour of Ron Paul (which is explained by his large online following and the over-representation of organised libertarians online) but the other candidates come in the right order…
    http://www.google.com/insights/search/#q=%22ron%20paul%22%2Cromney%2Csantorum%2Cgingrich%2C%22rick%20perry%22&geo=US-IA&date=today%201-m&cmpt=q

    Again, I’m not saying that social media research is fully reliable yet, but I’m pretty sure it will be somewhere down the line, maybe sooner than we think. In addition social media and networks offer a trove of qualitative insights…

  • Stephen Rappaport

    Tom – a Tweetminster study (UK) done in 2010 showed that Twitter was able to predict the outcomes of elections, but that the accuracy of the prediction correlated with the level of the election: national accuracy -91%; regional accuracy – 88%, and local accuracy -69%. We might be seeing something like that here, but more data is needed. Will be interesting to track. On the point about the gap. Research by Ronen Feldman and colleagues on auto purchases found that there was a strong correlation between cars mentioned in conversations, their sales and vehicle registrations, even though most people don’t talk about cars online. His study was among the first to show that there was no gap, and that online conversations reflect offline behavior. That may hold for autos, but may not generalize to other categories and specific brands. I agree with you, brands need to know their gap, but it’s not always easy to compute because many conversations have a very low level of mentions. In many food categories, it’s under 10%. Makes one wonder what would be the best way for a brand to measure its gap when the number of mentions is low?

  • http://www.edisonresearch.com Tom Webster

    Well, more data is certainly needed. For instance, I doubt the Tweetminster study has enough data – yet – to deal with the two great outliers of Iowa: Ron Paul, who significantly *underperforms* social media, and Mitt Romney, who significantly *outperforms* social media. In exit polling, we have a dozen models that alert us to anomalies like this, because we have decades of data and experience modeling that data to flag these sorts of things. That doesn’t exist in social media…yet. I’m certainly not going to claim it won’t happen! Only that it’s difficult, and we aren’t there yet. The key for me, as I noted in the post, is the existence of a replicable model – one that works the next time pretty closely to the way it worked the last time.

    And I haven’t seen the Feldman study – but will look it up now. Thanks, Stephen!

  • http://www.mltcreative.com Billy Mitchell

    There are so many variables I can’t imagine how best to correlate results from the Iowa caucus with social media commentary. The motivations and mindsets of those that attend the Republican caucus are skewed so heavily evangelical while the activity on social media is wide open and allows for everything from snarky tweets to troll blog commentary from both extreme left and right and all manner of opinion in between.

    I like the idea of substituting “Iowa Caucus” and “people in Iowa” with “your brand” and “your customers”. It’s a great illustration of how skewed projections (based on limited data or circumstances) can be from actual outcomes.

    I’ll be interested in your thoughts on the “Social Media Primaries”.

  • http://www.mltcreative.com Billy Mitchell

    Tom,

    Is it my bad eyesight, or are you experimenting with just how small you can make the type in the comments section? I don’t remember it ever being this small but of course I’m losing my memory along with my vision. 

    Knowing you appreciate research more than most, hopefully you will welcome my question as a response. I vote for larger type.

  • http://www.edisonresearch.com Tom Webster

    Hmmmm – must be a Disqus thing? Certainly not a design “decision.” Thanks, Billy!

  • http://www.edisonresearch.com Tom Webster

    There, I fixed it! I can DO it!

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