Blog
14 Mar 2016 Research

Research 101: Using Data to Grow Your Business

Ruchi Dhami
Ruchi Dhami
Director of Market Insights & Development

Be honest: how many of you cringe when you hear the word math? I wouldn’t be surprised if it’s most of you. Maybe you’re replaying a horrible memory from your 7th grade algebra class, or maybe you’re thinking about how you never really needed to know anything that appeared on the SATs. In that case, here’s fair warning: we’re about to talk about math.

Before you cut and run, I’m not going to be doing word problems on a chalkboard here (although I do put up weekly ‘Math Monday’ problems in our office, just to keep everyone on their toes). I simply want to make a case for practical and applicable data collection and analysis. Sure, there might be a little math along the way, but the end result will be impactful to your business’ growth and marketing strategy.

So, here it goes…

 

What is Research?

Research can take shape in countless forms. You know those customer satisfaction surveys you get after you buy a new car? That’s research. What about marketing focus groups from Mad Men? Research. Clinical trials for new cancer drugs? 100% research. Those incredibly smart PhDs in sterile labs mixing some blue liquid in a small vial with something that’s bubbly and steamy in another vial? Yep, that’s research, too.

 

Numbers vs. Not Numbers

Data can be collected in many ways, but when you distill it down to its core, data are really either numbers (quantitative data) or not numbers (qualitative data). Beyond this, there are distinctions of utility of data – how are numbers used differently than words when you’re investigating the same topic?

  • Quantitative Data
    Five apples. Ten pounds. 27 years old. 97.8°F. Quantitative data is something that can be measured: length, height, volume, weight, age, count, cost, temperature, and more. Simply put, these data describe how many or how much.
  • Qualitative Data
    Qualitative data includes words, text, commentary, photographs, videos, and sound recordings – really, anything that isn’t numbers. These data describe qualities of a particular subject; they can be observed but not measured, like colors, smells, tastes, appearance, and feelings.

Let’s put our new data knowledge into practice. Here I am at my desk drinking a cup of coffee*. What do we know about it?

Quantitative

See the difference? Quantitative data are the cold, hard facts, while qualitative data describe my coffee and my feelings toward my coffee.

 

This is the Math Part

Qualitative data probably sounds really good to you if you are one of those people who worried about the math portion of this post. But, the two kinds of data are more interdependent that you might think.

Quantitative data is informed by qualitative data. Before my research team and I start any large-scale quantitative project, we always start with something qualitative, like focus groups or interviewing. In doing so, we figure out what questions to be asking and what’s important to measure. Once we get our quantitative data, we do all sorts of cool things to them: basic counts (e.g. How many people at Recovery Brands drink coffee at least once per day?), descriptive analyses like averages (e.g. What is the average daily coffee intake of all RB employees?), and more advanced statistics like regression models, odds ratios, and likelihood functions (eg. Is there a statistically significant relationship between daily coffee intake and number of hours worked per day by RB employees?).

On the flip side, qualitative data can be converted into quantitative data. Let’s use our coffee example to explore this a little further…

We interviewed 20 people at RB about the coffee that they drink in the morning. We asked them to describe their coffee, and tell us how they feel about their coffee. We now know that Ryan needs two cups right away in the morning before her day can start. Ashton likes to add cream, but Heath likes to add sugar because the taste is too bitter for him. Melanie doesn’t drink coffee, but she’s a big green tea drinker. Looking at all of our data we can make the following quantitative remarks:

icon

And just like that, we’ve created numbers from not-numbers. This is just the tip of the iceberg, my friend.

 

What Does This Have to Do With You?

You’re probably not all that interested in doing a large study on how people take their coffee. Being involved in the addiction treatment space, you more than likely want to know what is and isn’t working in your program, how your alumni are doing, and, most importantly, your treatment outcomes. These seem like huge questions, but by setting up a few simple research studies, you can actually figure them all out.

As a treatment provider, you already have a lot more data than you realize. Patient charts are excellent sources of data. Create a questionnaire to send to your alumni asking for feedback. If you don’t already do exit interviews, start doing them. Count the number of participants you have during optional and recreational activities. Routinely collect employee satisfaction surveys from your staff. Of course, you need to get consent from every person you include in your research project and confirm that you’re complying with all clinical and research laws (we’ll get to these sometime soon), but you’re positioned to collect so much meaningful data, and all of your research participants are right at your fingertips.

Research has the potential to help your business develop and grow through data-driven decisions. You might find that your family programming is incredible and all of your current clients look forward to it every month. This might lead you to advertise these programs to potential clients as a strong asset to their recovery process. Maybe your alumni say that the beds are lumpy when they were in treatment, so you have an opportunity to improve your facility and invest in new sleeping accommodations. Perhaps you’re finding that almost everyone participates in morning group runs, but no one is really showing up for afternoon swimming. It might be time to consider where you’re allocating resources based on participation and preference.

For the RB research team, our primary goals are to understand consumer behaviors and preferences: what do those people using our sites actually want to know before they make the important decision to get treatment? We address this huge question through a mixed-methods approach, a bit of quantitative and a bit of qualitative, to get the fullest picture of our site visitors. We do this through surveying, interviewing, focus groups, video and audio recording, and more, and use dozens of different kinds of analyses and statistical techniques to interpret our data. These data help us meaningfully tailor our resources and tools to our consumers, with the ultimate aim of helping them to make the most informed choice about their care. That’s pretty huge for us, and for me personally, it’s incredibly fulfilling to directly and positively impact the way in which people seek and select addiction treatment.

Plus, I’ve always really, really liked math.

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