ADOTAS – Over the past 20 years big data and analytics has had a transformational impact on changing the way we do business. Our culture has increasingly become a data democracy or an environment where individuals have access to unlimited information from diverse sources and the power to make informed decisions with greater responsibility.
Nowhere has this been more prevalent than in the media space where a reliance on a “burn to learn” approach has been utilized by media planners and analysts for some time. In this practice, a media planner may have a hypothesis on a particular audience and due to various exigencies like client budget and competition for campaigns the need for certainty is paramount before a commitment can be made.
So in order to see the results, they might spend a little money on a little media to just get a sampling of what’s to come. This form of testing is employed in a myriad of industries and is a reliable safeguard in managing potential risk.
This approach may be effective in getting real data so that the first step in the media buying process is a confident one, especially when millions of dollars are at stake in selecting the right set of inventory or audience. However, there’s an alternative approach in achieving this goal but it’s rarely employed.
Why? Because it challenges the everyday minutia of our lives that has increasingly become more busy, more distracted and more demanding.
If done wrong, using the “burn to learn” approach can be a losing proposition. Here’s a quick look at the costs that it take to run this type of test:
In this case speed kills in a positive way. If testing can be done in a quick and efficient way then that’s ideal. But if test results take time then the lack of speed kills. It kills client enthusiasm, team motivation, chances to iterate and time to market. So in order to extract any value from this type of approach, speed is essential. Without it, the risks go up.
Money Is Scarce
Budget dollars for testing is only marginally easier to get than expanded budgets. Why? Because it’s somebody else’s money and gambling with somebody else’s money is risky especially when you don’t have any data to support your bet.
Testing Inventory vs. Audience
This is flat-out wrong. At its core, advertising needs to touch actual people, so testing proxies will distill little information about an audience.
You Could Be Wrong
Using a small sample audience doesn’t paint an accurate picture of the types of results a media planner might get at greater scale. Testing a small sample will only result in data on a small sample. It’s difficult to extrapolate data to begin with so it’s vitally important that the ends justify the means in this process.
The next revolution of audience targeting eliminates this practice of “burn to learn” by giving media buyers data on a large enough scale that will enable them to make better and informed decisions before spending media dollars through analytical solutions. With analytics, media buyers can better understand which first party audiences need to be targeted, eliminate any costs to model or simulate multiple audiences in real-time and make audiences go live when appropriate.
While a true data democracy might be a stretch for our industry in the near term, putting a stop to the “burn to learn” approach is within our grasp today and good first step.