When it comes to market research, quantitative data is king. Marketers want to dive deep into numbers to inform their company’s next steps. How many people are using their products? What’s the demographic breakdown? Which products are most popular?
An abundance of quantitative data is collected daily in the cannabis industry. For instance, we know product sales spiked over Mother’s Day and Father’s Day weekends (my, how times have changed). Data analysts tracked by state the average price per ounce of high-quality marijuana in 2018. According to a recent Forbes article, such data is being used to manage growing and delivery activities and cut down on inefficiency.
Quantitative data is crucial, but it only tells part of the story. It gives the “what” but not the “why.” And in the “why”—what’s called qualitative data—we get a more complete picture of consumer trends.
For example, the numbers might indicate a specific brand of CBD drink is popular in a certain city, but the data point doesn’t explain why that’s the case. Perhaps buyers really like the flavor, or maybe the beverage is the only one stocked in the city’s single dispensary. Without other contextual data, some quantitative statistics mean nothing at all.
In the example above, if the situation represents the former, then the manufacturer and retailer can say, with confidence, they have a strong market for that product. But if it’s the latter, they can’t yet make that claim. Without talking to the customers to find out why, the owner might determine he miscalculated what to stock and made unfortunate purchasing decisions. The truth, however, may be people actually resent the customer service in the store and don’t like shopping there.
Knowing the “why” behind the numbers, the motivations and emotions, can help cannabis manufacturers and retailers gain a more nuanced—and, therefore, more informative—understanding of consumer behavior.
Now for the obvious question: How does one capture qualitative data? Generally, qualitative data is collected via one-on-one interviews, focus groups, open-ended questions on surveys, observations, and action research (active involvement in a change process while conducting research). The main benefit is the information tends to be richer and provides deeper, more nuanced insight into the subject of investigation. Clear disadvantages to this approach exist, however.
Because gathering qualitative data involves one-on-one interaction, the process is time-consuming and costs much more than collecting quantitative data. That often leads to small sample sizes, leading to potential for interviewee bias, conscious or not, to impact what a company safely can claim based on the data. Furthermore, analyzing qualitative data takes judgment and even linguistic skills to parse wording; you can’t simply run a report and obtain relevant analyses.
In many cases, capturing both quantitative and qualitative data—known as mixed-methods research—can provide researchers with the best of both worlds: large sample sizes, the ability to run analytical reports quickly, lower costs, time efficiency, and richer information that helps tell the full story. Often, the empirical data provides the base and the interviews back it up. It’s a great example of the whole being greater than the sum of its parts.
Many industries use mixed-methods research to gain better understanding of their market landscape and inform business decisions. For example, the banking industry has used the combination research method to determine consumer perceptions of trust, risk, the usefulness of mobile payments, plus consumer credit trends by age. The Society of Chemical Industry conducted mixed-methods research to study Mid‐Atlantic consumers’ fresh and processed peach purchasing behaviors to determine whether packaging certain numbers of peaches together, providing information about nutritional content, and other factors would increase purchases. Using both quantitative and qualitative data can yield a veritable treasure chest of valuable information when looking at consumer website usage. The applications are endless.
Lots of quantitative cannabis data exists, but far from enough qualitative data is available. That’s a shame, because it means we’re making decisions without fully understanding what’s taking place. Pairing quantitative and qualitative data provides companies powerful consumer intelligence, which can help drive not only product development and marketing but also cultivation, packaging, and delivery.
That being said, the cannabis industry as a whole needs to invest in collecting—and sharing—more user feedback and other qualitative data in order to make the best, most informed decisions possible.
Darren Roberts is co-founder and chief executive officer at Green Mile Holdings, a provider of consumer mobile products and enterprise technology systems. GMH offers product data insight, proprietary technologies, machine learning consumer data platform HighQ, and social network High There! Roberts previously worked in the financial lending sector for more than twenty-three years.