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How Data Makes (or Breaks) Your Media Plan
Congratulations! You received a juicy RFP for a CPG company that’s launching a new line of eco-friendly laundry detergent. They’re looking to reach millennial moms who have an affinity for eco-causes, enjoy fashion, participate in wine clubs, are self-described foodies, and live an active lifestyle. Of course, they also want to reach them on their mobile device.
That’s a tall ask for a target audience. How can you reach all these segments, while still offering a plan that is scalable and set up for success? The answer is all in the data.
Quality of your data will determine success
We now live in a mobile-first world, we have more data points than ever to help us hone our strategies to exactly our target audience. We no longer need to guess someone’s habits when we can know precise data such as timestamp, device characteristics, location, app usage, brand engagement, and survey responses.
As a media planner, you need to be discerning to find the highest quality data to ensure that you can reach the right customers, at the right time, with the right message. Data inspires relevant messaging to the right users, the ability to reach niche audiences, and can track the consumer along their journey.
What happens when you have “bad” data?
When using data, the most important thing to consider is data quality and the source of the data. Ensure that you are buying deterministic data as opposed to probabilistic data. Probabilistic data makes inferences using a “high probability” approach. This is contrasted with deterministic data, which offers a one-to-one approach. Deterministic data can have scale limitations, but it is inherently more accurate and valuable.
With “bad data” you risk misclassification of your target audience and poorly executed campaigns. What good is your creative curtailed to the millennial mom if it’s wasted on a baby boomer? Bad data will lead to lower campaign performance, wasted impressions, lower engagement rates and deteriorate trust with your data sources.
Thinking about your data sources
Luckily, the scenario above is avoidable. We’ll dig into what to consider when vetting your data sources in an upcoming blog post.
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