Discover how brand tracking software fuelled by advanced data science can provide more accurate insights into brand perception for target audiences.
Brand tracking software faces a major dilemma. Their small sample sizes make it difficult to measure brand perception at a level that can really drive brand growth. This is an issue for brand and marketing managers who know the best way to stand out to consumers is to tailor to the specific concerns, wants and needs of different customer segmentations. But times are changing. Advanced data science has devised a method to uncover insights in niche audiences even when sample sizes are small, thus breaking past the limits of brand tracking software that uses traditional survey research techniques. This method is called multilevel regression poststratification (MRP), and it helps generate the survey insights based on a statistical model. To illustrate the benefit of this component of MRP, this whitepaper includes a case study based on JustPark, a parking app. Using the data gathered by Latana for JustPark, it will show how MRP makes it possible to uncover differences in brand awareness for niche target audiences in cases where traditional brand tracking methods are limited by small sample sizes. Key insights include: - The traditional approach generates unreliable results that are based on a tiny sample of respondents in the niche audience - The MRP model is able to uncover differences between old and young respondents in JustPark’s niche target audience - JustPark can confidently say that brand awareness among young, car owners who live in the top 3 cities in the UK is around 34% - JustPark can confidently say that brand awareness among young, car owners who live in smaller cities in the UK is around 21%
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