At first glance, a campaign is something that seems to be bounded in time. Whether it be battle (win it), an election (win that), or pitching of a new product to a new customer segment (win them), you’d think that campaigning would stop when the desired end was achieved.
In the real-world, though, we all know that campaigns don’t necessarily end when they “end.” They are not necessarily over when the initial tactical objective is realized. It’s always possible for the initial gains to be reversed if the campaign discipline is not somehow incorporated into ongoing operations. They must also focus on an ongoing basis on the larger “ends” (plural) that the initial time-bounded campaign was addressing.
I was checking Merriam-Webster’s definition of “campaign” to see if it reflects that larger sense of the term, and indeed it does. One of the senses of the term is “a series of activities designed to produce a particular result.” If we conceive “a particular result” as ongoing steady-state ends (e.g., hold the territory, consolidate power, retain and cross-sell the customer), then it’s clear that continuous campaigning is not an oxymoron. It may be a necessity.
Unfortunately, continuous campaigning has become a mainstay of modern US politics. To a growing degree, non-stop campaigning–by the recently victorious and recently vanguished in equal measure–is an abrasive factor that risks eroding whatever fond feelings the electorate may once have had for the politicians, parties, and principles they supported at the ballot box.
These thoughts came to me as I read a recent article with the headline “”Data analytics ‘nerds’ now mainstay in U.S. politics.” We’re all familiar with data scientist Nate Silver, who became a legit nerd-celeb when he accurately predicted that Obama would win re-election in 2012. If you’ve been paying attention, you also realize that both the Obama and Romney camps had their own teams of data scientists. As someone from the erstwhile Romney campaign stated in the article, that year’s presidential race “was definitely the first cycle in which the term data scientist was part of the org chart in a campaign.”
Political, scientific, and data nerds have a lot in common. The article discusses how each of those candidates’ data-scientist teams has spawned its own post-2012 start-up firm to carry on those parties’ never-ending campaigns. It describes how these and other partisan data scientists are using social media, digital TV, and other online channels both as data sources and as avenues for ongoing engagement with the electorate. If you’ve been on the Internet at any point in the 2013 election season, you can see how feverishly active the partisan data scientist communities have been on their respective crusades.
Personally, I want them all to stop, but I know that’s not likely. One of the ends they’re inadvertently achieving is irritating me to distraction. In an ideal world, optimization of any campaign, be it time-bounded or ongoing, should factor in the “quality of experience” of the impacted customer/stakeholder/voter. That, in turn, demands a fine degree of microsegmentation and sentiment analysis that I’m sure these partisan data scientists are playing with.
As regards microsegmentation, the article quotes an academic data scientist: “‘When you do a poll and you talk to 1,000 people who represent 100,000 people, you get a margin of error plus or minus 3%,’….That’s helpful…but not nearly as helpful as having 70,000 of those 100,000 people. At that level…you get much more precise and start identifying subcommunities that you can’t do in a poll.’”
However, I’m not at all optimistic that hardcore partisan data-scientist nerds have any interest in analyzing it all down to the microsegment called “James Kobielus” or measuring my personal peeve quotient. That’s because their core job is to sway the electorate as an aggregate, not as individual voters or influencers. Also, they know that their partisan activities will annoy many people no matter how kindly and gently they do it.
Some campaigns exist to sway the love-hate equation in the direction of the former, but are highly unlikely to eliminate the latter entirely. To quote a 19th century American politics nerd who singlehandedly inspired a lot of the love and a heaping helping of hate: “You can please some of the people some of the time, all of the people some of the time, and some of the people all of the time, but you can never please all of the people all of the time.”
To some degree, continuous brand marketing in the commercial world also risks alienating the hearts, minds, and pocketbooks it seeks to woo. The more interminable and aggressive the campaigning, the more your target customers will curse you under their breaths (if they’re in a good mood, that is.)
However, customers are willing cut many businesses a lot of slack on their brand-marketing overkill. The consumer culture in most countries– not just in the US–long ago begrudgingly accepted the in-your-face ubiquity of advertising and promotions. If nothing else, most people now accept that continuous brand marketing is integral to modern life. Most people have developed a thick skin of cynicism and skepticism about the claims made in advertisements, but none of that has eroded most people’s implicit faith in the economic system that streams these commercial messages 24×7.
Perhaps the same marketing-weariness is stoking the cynicism that many people feel about today’s political system. For example, every time you play a YouTube video during a US electoral cycle, you have to endure aggressive attack ads by, say, gubernatorial candidates in some swing state. After a while, you tend to forget that you actually plan to vote for one of these attack dogs. You just want all these two-bit politicians get out of your face and let you play some beloved Talking Heads video.
“Don’t Worry About the Government“? You should be worrying when the electorate tends to hand power to the partisans with the most aggressive advertising. And you should worry when never-ending campaigns decay into nasty ideological blood feuds that long ago stopped making sense.