How to Compare Market Research Firm Options

How to Compare Market Research Firm Options

How do you know for certain you’ve selected the right market research partner? How do you ensure that your partnership investment will yield the right outcomes? Consider this:

It’s not a secret that you need great research to truly understand your customers and the marketplace in order to compete. But great market research is expensive, and cheap research isn't great.

So when your internal insights team is at capacity, or they don’t possess the tools to achieve a new objective, how do you get that fresh customer insight, or identify the next white space without breaking the bank?

Building product manufacturers and suppliers have been turning to custom market research firms to study their customers, track their brand health, and advise them on which strategic business moves to make next.

But that begs the question of how you know for certain you’ve selected the right market research partner. How do you ensure that your partnership investment will yield the right outcomes?

Understanding The True Cost of Bad Data

First, let’s level on how most market research firms are compared.

For better or worse, the ratio of total project price to N size, or sample size, of the target audience to be studied has become the commonplace standard for evaluating custom market research options. This narrow (and dare we say, misleading) factor may be used by your insights managers, marketing leaders, brand managers, and product managers to get buy-in from executive leadership for the study.

Too often sample size is the main driver of purchasing. And the problem with this is that it makes two false assumptions:

  1. That all respondent samples are accurate.
  2. That more is always better.

As a standalone number, sample size fails to consider the degree of accuracy that is being delivered from the quantitative or qualitative study and how much you and your teams will be able to trust the recommendations derived from the results. That’s because the sample size does not equal sample quality.

The time allowed for fielding and post-fielding data cleanup also impacts the trustworthiness of the data. When the study is limited in how long it can be in the field, but a large sample size is required, with certain vendors, the respondent vetting process is at risk of being compromised to reach the N size promised in the time window.

It’s true, larger N sizes tend to tickle the ear better, because it sounds like the data would be more comprehensive, but these five examples prove how a larger N size is not indicative of better findings. In fact, that could actually be the telltale sign of a higher risk for inaccurate insights, especially among target populations with low incidence rates, like speciality trades and builders.

This limited view, however, is often used by decision makers to compare market research partners and vendors, and often the firm that promises the largest N size for the smallest dollar amount will win. This does not mean you will win in the end, though.

Because the unspoken assumption is that with a larger sample size, you can gather more information, and that with a bigger pool of respondents, you get better insights into the question(s) at hand; but, that math doesn’t add up as the sample size only represents the input, not the output.

Bad data in = bad analysis out.

A poorly vetted respondent sample that contains entries from bots, generative AI, fake respondents, and duplicate respondents can only lead to inaccurate analysis and misguided recommendations, putting your reputation at risk.  Leading your organization to invest possibly millions on flawed thinking.

Now, there are market research vendors who can (and will) gladly tell you they can field a study among 400 asphalt roof shingle installers or electricians using voltage meters for a comparable project cost as well-reputed firms such as The Farnsworth Group. Sounds like you’d be maximizing your limited research budget, right? Wrong.

Don’t throw good money after bad. In most cases, it is a stretch to get a real N size of 200 humans for a hyper targeted group of trade professionals, like roofing contractors.  You must resist the allure of big N size figures because it likely won’t  increase the confidence interval and may only serve as a cause for more poor data.

Getting To Accurate Insights That Drive The Right Decisions

At The Farnsworth Group, we’ve helped hundreds of building products manufacturers, retailers, and industry associations go from a place of uncertainty about what to do next to a place of clarity in just a matter of months.

We’re in your corner to reduce your risk of launching the wrong marketing campaign or a product line that won’t perform. We’re here to help you understand how your brand is perceived and where there is white space in the market for your company to get their foot in.

You get much more than data. Our proven approach blends market intelligence consulting with primary market research to deliver actionable insights and grounded recommendations impacting your marketing & sales teams, brand teams, channel teams, and product teams. You get customized research built around your needs with proprietary results that off-the-shelf approaches could never produce.

Because our team works exclusively in the building, home improvement, and lawn & ranch industries, as we have for nearly 4 decades, you can trust that our insights and recommendations take into account the complex variables that impact your end to end go to market situation in the complex building materials environment.