There is no question that marketing data must be reliable. Marketing research and analysis is like a house of cards with data being the first floor: if the integrity of the data is in question, then the entire project is useless. However, generating trustworthy data, as important as it is, is only half of the battle in producing accurate and meaningful conclusions to marketing research.
Where analysts often unknowingly go astray is in the analytics report, especially when it comes to how the data is explained and represented visually. Much like aircraft pilots reading their instruments, the smallest misinterpretation can have large consequences.
These analytic and reporting mistakes range from the obvious to the subtle. Examples can include failing to disclose the type of numbers on an axis (i.e., percent, time, dollars) or using an impractical or confusing chart type for a given set of data.
Additionally, confusion can arise in the analysis and commentary of the data. For example, let’s say I am using an index where the value of 100 represents the attitude of the average adult. If the market segment I am researching has an index value of 80 for that attitude, it would be a major misrepresentation to say that “80% of this market segment has that specified attitude.” The correct commentary would actually say something to the effect of, “Compared to the average adult, this market segment is significantly less likely to have that attitude.”
Remember that generating quality data is something to feel good about, but you must not stop there. Accurate analysis and commentary are equally as important.
[Contributed by Ben Hill]