Posts from — November 2008

On Saturday, Motrin posted the ad below:

What followed was a viral social media response that most marketers can only dream about.

In just 48 hours they had:

• Over 100,000 views on YouTube for both their ad, along with all the video blog responses to their ad
• Number 1 (motrin) and Number 2 (motrinmoms) topic trends on Twitter, according to Twitter Search.
• Over 8,000 individual blog posts about the ad and Motrin itself according to Technorati.

Additionally, they had the undivided attention of many of the leading pundits in the digital marketing blogosphere, including Seth Godin, Jeremiah Owyang, Brand Flakes, Adfreak, ReadWriteWeb, Hard Knox Life, David Armano, Frank Martin, The Consumerist, Adrants, Mashable, Viral Blog, Peter Kim, Adverganza, Brand Experience, Rogue Agency, and many more.

Now to the fine print:

This social media marketing campaign was all a big, unintended mistake.  And as you may guess, the overwhelming response was negative.

Motrin is now backpedaling, pulling the ad from their site, posting apologies all over the place, and they and their agencies are probably in an all points scramble mode.

Which is all too bad, because, if you just looked at the response numbers, Motrin had a lock on social media marketer of the year with this one.

With the announcement of its innovative use of search data to track the spread of the common flu, Google Flu Trends has allowed Google to lever the enormous potential of search analysis in order to track the most viral (pardon the pun) of trends.

Search Engine Optimization 2.0 and Search Engine Marketing 2.0 as concepts have dominated digital media over the last couple of years.  And now with Google Flu Trends the concept of Search Engine Research 2.0 is truly coming into its own.

Google Flu Trends is based upon the aggregation and analysis of the search behavior of people who type the flu symptoms they are experiencing into Google in order to confirm their self diagnosis and to look up potential treatment options.

Google has found there is a close relationship between the amount of people searching on flu symptom related keywords and the amount who actually have the flu itself.

In the chart above you can see how Google Flu Trends has been well correlated with data from the Center of Disease Control on the level of flu cases being reported in the US over the past several years.

The advantage with Google Flu Trends is that the data is available a couple of weeks ahead of what the CDC compiles and announces.

Google Flu Trends is a good demonstration of the potential of the large and relatively untapped potential of levering search data for marketing research and consumer insights.

I look at what Google is doing with its Flu Trends tracker as bit of kicking the tires and taking their data for a test drive around the block.

When researchers finally take this information out on to open road and push things to the limit, that’s when we will really start realizing the full potential of search engine research.

With the 2008 Presidential election now almost a week behind us, the media is filled with backwards looking punditry on what lessons this campaign will inform history with.

But of all the unique aspects of this campaign, one thing that stood out was the use of data and how that influenced strategy, especially with the Obama campaign.

His unique electoral strategy of looking outside the typical swing states into areas where Republicans have always been strong (Colorado, North Carolina, Virginia) was driven by statistical analyses that showed how changing demographics in these typically Republican areas provided opportunities for a Democrat willing to take advantage of them.

I tend not to be very politically minded, but one site that fascinated me throughout the election season was Nate Silver’s FiveThirtyEight.com blog (538 being the number of electors in the Electoral College).

Throughout the campaign, he aggregated all the available polls and then analyzed them using regression analyses to find out what their outlier tendencies tended to be.

He then weighted the polls and re-simulated the election 10,000 times per update in order to, in his words, “provide a probabilistic assessment of electoral outcomes based on a historical analysis of polling data since 1952″.

And his accuracy throughout the election process was remarkable.  According to this New York Times article entitled “This Math Whiz Called It For Obama Months Ago”, in the primary election versus Hilary Clinton, Silver “projected Senator Obama would win 833 Super Tuesday delegates, which was within about a dozen of the actual vote estimates”.

Additionally, when the returns came in on election night, it was found that “Mr. Silver had predicted the popular vote within one percentage point, predicted 49 of 50 states’ results correctly, and predicted all of the resolved Senate races correctly”.

What will be interesting to see is how this new approach to the analysis of polling data will have an effect on future elections.  What is certain is that the data driven approach to election strategy is probably here to stay.