Surveys are really common in the agriculture industry as a way of collecting information about farmers and their operations. Unfortunately, this can set agribusinesses back because there are very common weaknesses that come when you collect data from subjective gathering methods like surveys.
The most important marketing asset you have is information. You want to know about farmers’ behaviors, interests, needs and more. So gathering this data should be a top priority.
We’ve seen that many in the ag industry gather data through surveys. The thought here is that by getting data directly from the farmers themselves, you’ll have the most reliable information at your fingertips. Right?
While surveys are often a common way to collect data from farmers, survey data can be unreliable. Here are some of the weaknesses that come from survey data.
Survey Design Can Cause Error
Let’s say you’re at a trade show and you want to figure out how many farmers are growing soy. Because lots of farmers are at the show, this sounds like a great chance to get some real data for your marketing and sales efforts.
So you set up a survey outside an event and let the farmers fill it out. Once you see the results you’ll notice – all of the respondents are dedicating 50 percent or more of their acreage to soy.
You may be tempted to think that, based on this data, soy farming is becoming a new, sweeping trend across U.S. farming.
But looking at the data closely, you notice that only 10 farmers out of over 100 at the trade show filled out the forms. Based on the low number of respondents, it’s going to be impossible to draw conclusions.
That’s because when you do a survey it’s hard to get a representative sample – a group of respondents that’s large enough and representative enough of farmers across the board.
Looking a bit closer, you could also notice that you set up the survey outside a panel discussion on soybean farming. So the people who passed by your survey were already those interested in soy, so obviously they’d all be dedicating a large portion of their operation to soy farming.
Not only does this mean that your sample is non-representative, but it’s also a sign of selection bias – only the people interested in soy filled out the survey.
There are many ways that surveys can give incorrect results. Sometimes, the survey design words questions poorly, confusing the respondent into giving an incorrect answer. Sometimes, the organization administering the survey may influence who does and doesn’t respond.
A great example of this is the U.S. Census. Because it’s a government survey, people often under-report on their income, for fear that it would cause them to have to pay more in taxes later. While this may or may not be true, the fact that the government is administering a survey impacts the results.
Surveys are helpful for driving engagement and for gathering qualitative data to help guide your agribusinesses’ efforts. They’re excellent for feedback on products and to help understand what your audience wants to see you do in the future.
But when it comes to market research and analyzing trends in the industry, survey data is weak and will often yield inaccurate results.
Not All Respondents Are Created Equal
Of course, there’s more to surveys than who’s creating and administering it.
Surveys depend on respondents giving correct answers - and finding out who’s given “bad data” can be challenging.
Some people may simply wish to speed through your carefully-crafted survey. Marking that they grow 500 acres of soybeans could be the fastest path to the end, regardless of whether it’s true or not.
If you’re running an incentivized survey, they may be driven more by gaining the gift card and not by providing accurate responses. Motivating people who are tangentially related to your business is hard to do under the best of circumstances, and downright impossible in less-than-ideal conditions.
Plus, surveys can cause problems when it comes to garnering contact information. Transposing digits in a phone number or even giving an incorrect email address are fairly commonplace errors that can render your carefully-collected data nearly useless.
Facts Are More Useful Anyway
While surveys can be powerful when done correctly, it’s much faster, simpler, and more accurate to work with facts. With segmented marketing data, you don’t even have to give up on getting highly targeted information about your audience.
Segments like Gross Farm Income, Planted Acres for a variety of crops, and Total Farm Acres, can give you real, actionable insight into your target audience. Sources like the USDA, NCOA and more give you a more accurate picture into your market – moreso than any survey could do.
Sure, surveys used to be considered an effective way to gather information about customers and prospects. Today’s marketers, however, have incredibly powerful tools just a click away - so why not take advantage? Ditch the old-school survey and jump into the digital age with easy, effective fact-based marketing data.