When Barack Obama won reelection in the fall of 2012, the marketing world took notice of the tactics the campaign used to reach voters, especially on TV. Two years later, political advertisers are lining up to use the same tactics in the mid-term elections. Meanwhile, traditional brand advertisers are still looking to develop similar solutions that leverage their data to find the best consumer audience.
At this juncture, there’s no point in keeping these two marketing verticals in separate silos. What works for brand advertisers works for politicians and causes – provided that both parties know what they’re looking for.
The Obama campaign succeeded not because it reached undecided voters, but because it reached undecided voters who were actually going to vote. There is a difference, and leveraging the Obama model means brands and politicians both need to identify their target audience and then zoom in on the segment that is most likely to take action, whether that’s in a voting booth or checkout line.
Consider pharma advertising. Because disease and illness do not discriminate based on age, gender or interests, standard audience profiling and segmentation do not help when building an ad strategy. But advertisers can comb their data and identify people who respond to ad messages, not necessarily with prescriptions, but through coupon redemptions, email submissions, or dialing a hotline for more information.
These respondents make up a smaller segment that can be referred to as “treaters.” Not only are they sick, but also they’re actually taking action to get better. To put it very bluntly, advertisers don’t make money off of the sufferers — they profit off of treaters. This is the segment that will spend and, once identified through that additional first party data, this is the segment it makes the most sense to advertisers to through targeted TV buys.
In the Obama campaign, they called this likelihood a persuasion score, which calculated how easily someone could be swayed to vote for the candidate. That’s the piece that so many political advertisers still miss, and it is translatable to traditional, non-political advertising as well.
Both kinds of advertisers have so much information about their constituencies and consumers already on hand. Properly combining that first-party data with other sources, such as set top box data, lets advertisers target action-taking consumers through TV — whether the “action” taken is voting or buying. This is possible today, in programs where the competition doesn’t advertise, and often at less expense.
A brand selling ketchup may look at their consumer data and learn that people who collect coins buy more ketchup. They can find the programs on TV that deliver that audience, but it doesn’t mean that audience will run out to the store to buy. Some may actually prefer mustard, and some may have a big bottle of A1 in their fridge that they need to finish first. What the brand really wants are probably coin collectors in certain geographic areas, with families and larger households.
Drawing consumers to the cash register is no different from getting them to the polling place. The movement to big-data powered advertising has taught advertisers of all stripes that they should focus more on the best audience segments, and they can shift their spend that way to avoid any wasting money. It’s helpful to comb through first party data and identify the best customer profiles, but ad spending shouldn’t include bumps on a log that will watch an ad and never get out of the house, whether to vote or buy. The next step is understanding intent and the likelihood that a viewer will actually vote (with their wallets).