In the area of online marketing it’s invariably a numbers game. Yeah, we know math isn’t super fun–but it definitely delivers answers. It’s all about statistics providing you with much needed insights. When it comes to finding these answers–quantitative testing is the method you need to consider. It is used to measure behaviors, whereas qualitative testing is geared toward user experience–how they feel and respond. Quantitative research involves methodical and detailed analysis–far more mathematical than qualitative research. We know…math again. The thing is, in quantitative research the question is always–is it measurable? For example, it’s not about the color or texture of an individual’s hair, but rather the length, weight, or thickness of it. This approach yields data in values or numbers.
What does that mean for your business? Numbers are generally far more persuasive in selling your product. Let’s say you have conducted a survey on how new clients feel about interacting with your business. The survey is on a scale from 1 to 10 – this can definitely be useful information. Now let’s say you’ve conducted quantitative testing and found 80% of confirmed sales were from clients outside the bracket of your survey. You might say, “but, nearly all survey participants rated their satisfaction from 8-10!” This is when math comes crashing in like the Kool-Aid man with an enormous pitcher full of refreshing logic and invaluable data. If the majority of clients from your survey aren’t the ones actually going out and purchasing your product–who is? How do you find out exactly who is not only interacting with your website–but actually biting?
You’ll have to find out who your target demographic is and how they interact with your business. What makes them tick statistically speaking? Perhaps survey subject #87 said “I told my friend Veronica about your website and she said it looks great!” - okay…that’s nice - word of mouth can definitely be useful - but, you can’t measure it. Would Veronica have found your business on her own? What would have drawn her there? How long did she spend on your site? Would she have even wanted to visit to begin with if her best bud, survey subject #87 hadn’t told her to? There’s no way to measure Veronica’s loyalty to #87 and let’s face it - that’s not the point. You want to know who is landing on your website and actually interacting.
Capturly reports that “there are specific advantages to using each type of user testing method. For instance, one advantage of quantitative research over qualitative analysis is the statistical significance. Quantitative data is protected against randomness, whereas qualitative research often falls prey to bias, which means the results are less objective than quantitative results, and therefore not a good representation of the entire target population.” You want to understand how your users are interacting with your website and you need unbiased metrics to give you that data. Emotions are subjective - facts equal measurable data. Data that can give you answers as to who your users are, how they were led to your website (social media or your company’s mobile app for example), and when your website is receiving the highest traffic.
Website design and messaging benefit from methods of quantitative research such as A/B testing–delivering variations of your site to see how well one design does over another. This testing includes traffic analysis–researching the numbers of users interacting with each of those variations. Our experts measure user engagement, then use that data to capitalize on what your users respond to most.
Clearly, there are reasons both qualitative and quantitative research are valuable to understanding users. Quantitative testing provides concrete answers, helping to fine tune your website. Hierographx - a Michigan website design company - uses Qualitative and Quantitative types of analysis to make sure your web presence provides the ultimate return on investment. It is based on scientific research that is designed to increase conversion rates. When it comes to user testing–a questionnaire just isn’t enough.