In one form or another, much of market research is aimed at predicting the future.  Whether you are considering opening a new line of business, tweaking your advertisements, or just trying to serve your constituents better, the key purpose is almost always some form of “If we do X, then what will happen?”  However, when crafting research questions, it is important to keep in mind that not all questions are created equal when it comes to predicting future behavior.  Respondents tend to respond to surveys rationally, and anyone who has been involved in marketing for long will agree that consumers are anything but rational.

Henry Ford Quote

The key issue to consider when designing research questions to predict future behavior is simply whether human beings are able to accurately answer your question.  Here are a few scenarios to consider:

Scenario 1: Media Choice

Let’s say you wanted to know what types of media would be most effective at reaching your target audience.  It might seem intuitive to simply ask a question such as:

Advertising Question

There’s nothing necessarily wrong with that question, and in fact we at Corona use similar questions here and there when we want to at least get a feel for where consumers might look for information.  However, people are notoriously awful at predicting how they will react to something in the future.  Many will likely name the usual media suspects – TV and radio – without thinking through what they actually pay close attention to.  They may not consider more unique advertising media such as social media, outdoor advertising, direct mail, and many others.  Instead, it might be more reliable to ask the question about what they can recall from the past and make the assumption that their past behavior will likely reflect their future behavior:

Advertising Question 2

In either case, any time you can triangulate your survey findings with other data (e.g., past ad performance, media consumption studies, etc.), the stronger your conclusions will be.

Scenario 2: Likelihood of Purchase

Let’s instead say that you are launching a new product and are trying to forecast how many people will purchase your product.  The most straightforward way of asking that question might simply be:

Purchasing Question

The challenge with that question is that it simplifies an extremely complex purchasing decision into an expanded “yes or no” response.  They may find the product attractive, but what will it cost?  Where will it be sold?  What will the economy be like once the product is available?  Are people already familiar with the product, or will they need to learn more about it to make a decision?  Will other competitive products be available at the same time?  Add to those issues the fact that people almost always tend to overstate how likely they are to purchase something, and you get very tenuous results – the results you get are almost always a best-case scenario.  A respondent will make an objective evaluation of their likelihood to purchase when taking a survey, but the final decision is a very emotional decision that can be influenced by all of these factors and more.

Instead, surveys are more effective at helping you understand the product attributes that will help to drive purchase.  For example, you could instead inform messaging about the product based on reactions to a series of statements about the product in terms of how valuable they seem to consumers.  If it is imperative to forecast future purchase behavior, a different approach, such as A/B testing to compare how different approaches work in the real world, using test markets before your full launch, and other advanced analytical techniques may be more effective.

Scenario 3: Optimal Price Point

As a final scenario to consider, let’s say you are launching a new product and want to know how to price it so that you can both drive sales and maximize your revenue.  You may initially think that simply asking the question outright will be most effective:

Optimal Price Point Question

This question (and a variety of other similar questions you could use) again simplifies a very complex purchasing decision into a straightforward answer.  What will the respondent’s financial situation be at the time of purchase?  Are there sales on competing products?  Will they be attracted by the packaging?  Will the product be sold in a small, boutique shop or a large superstore?  All of these can have significant impacts on what people are willing to pay that would not be reflected in a survey response.

There’s nothing wrong with addressing price in a survey necessarily, but a typical survey will be limited in its ability to give you accurate information about optimal prices.  You can use a straightforward survey’s findings to give you a feel for reactions to prices, but a final decision on pricing should be based on many other data points than the survey results alone.

That said, there is a specific type of survey (called a conjoint survey) that is specifically designed to help determine optimal prices by asking consumers to make choices between a variety of combinations of product or service attributes.  It’s a considerably more complex process, but is by far the most reliable way of understanding the value that consumers place on various attributes and can help to accurately inform your pricing strategy.  Similar to the discussion for Scenario 2, test markets could also be a valuable option to understand how consumers will react to various prices.


Despite these challenges with predicting future behavior, surveys remain one of the most valuable tools for informing product/service development and marketing.  Surveys are highly effective at understanding current behaviors, measuring awareness, understanding pain points that a product or service could address, understanding attitudes and perceptions of a product or service, and much more.  However, keeping in mind the types of information that respondents are able to accurately provide will ensure that the survey’s results are as accurate and actionable as possible when developing your future strategy.