Challenges With Market Research

There are many challenges associated with market research and data. In fact, it’s never totally easy to collect, manage, or analyze data—something’s always going a bit awry! You could conduct market research and analyze marketing data for a decade, and it might never become a smooth process. Here are some of the common challenges you could run into:

• budget: Running primary research or buying syndicated data costs money—often a lot! Purchasing samples for primary studies can be very expensive if you need to work with a niche population or B2B professionals. This is because the cost per interview (CPI) increases as the size of the population decreases (supply and demand). Likewise, collecting data in countries outside the United States or in rural or emerging markets is also expensive because you may need to use one of the pricier methodologies (like door-to-door) or translate surveys into local languages. Finally, the research methodology itself can increase costs—online surveys tend to be less expensive than focus groups or face-to-face interviews, for example.
• survey questionnaire design: Survey questionnaires are written, programmed (if online), and administered by humans. Thus, they’re subject to human error. Market research questionnaires tend to be complicated and often long, with lots of logic and skip patterns, in order to make the most of the respondent’s time and capture as much data as possible. Even though questionnaires are pretested for mistakes, invariably there’s something wrong that someone missed: a typo, a bad skip pattern, or a filter that’s not working correctly. Any mistakes in the questionnaire translate into bad data that may be costly to re-collect or just unusable.
• data management: Once the data has been collected, data files need to be created and managed. Many quantitative market research data files are thousands to tens of thousands of rows, with hundreds of variables. Data scientists and market researchers must clean the data to put it into standard, structured formats to be used in statistical analyses. This is often done through writing code and syntax. Any mistakes in manipulating data can lead to errors in the data file—and it does happen!
• unresponsive interviewees: Interviews can be tough when you’re working with folks who aren’t talkers. It’s like pulling teeth!

 

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