The Secret to Reliable and Precise Brand Analytics
MRP, or Multilevel Regression and Poststratification, is the statistical technique we use to guarantee reliable and precise data. We’d love for you to think this is a brainchild all of our own but it was actually devised by Professor Andrew Gelman, a statistician at Columbia University.
How Does MRP Work?
To explain how MRP works, we compare it with a more traditional way of doing things. Let’s take the example of measuring opinion in a very specific, small target audience.
Imagine a brand who wants to run a campaign targeting tech-savvy millennials who play soccer. They want to find out what this specific group of people think of their brand.
The traditional brand tracker creates a sample of 1,000+ respondents and then zooms in on tech-savvy respondents, millennials, and soccer-playing respondents. In the end, there are 20 respondents who fit the target audience. The brand tracker takes the average opinion of this group but because the number of respondents is so small, the margin of error is large.
This large margin of error is a problem Latana is able to fix. Instead of narrowing the sample size to just 20 respondents, MRP makes an estimate of the target audience group by using ALL the information available in the 1,000+ respondent sample size. This means it looks at ALL the tech-savvy people, ALL the millennials, and ALL the soccer players. Because we use all the information from the sample, the estimate for a small group is much more reliable.
What's the Magic Potion?
The magic potion isn’t really magic at all. It’s as simple as this: instead of focusing on a tiny group in a target audience, MRP builds a model. This model is used to calculate the opinion of a brand by looking at the respondents’ individual characteristics and how they relate to the brand.
To put it another way, we use the MRP model to say a tech-savvy, soccer-playing millennial is someone who plays soccer, combined with somebody who is a millennial, combined with somebody who is tech savvy.
We then look at the relationship each of these characteristics has with brand perception. We ask “is there a difference in brand perception between soccer players and non-soccer players?" If so, this difference is the effect of being a soccer player. We do the same with millennials and tech-savvy respondents.
Each time MRP calculates the effect of a characteristic, it uses the entire sample size. As an outcome, the results are much more precise and you can draw reliable insights.
That folks is MRP.