OUR POV: THE MMR BLOG

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The Real Cost of DIY – What to Ask as You Plan

By Patricia Houston, VP – Client Relationships

It’s very easy to see on the surface how DIY research can save you money, and often the low rates offered and quick speed promised by DIY providers make their products look enticing. However, in order to “DIY right” is it really cost effective once the time commitment and expertise required are factored in to the total cost? That answer largely depends on what you are trying to decide.

Personally, I’m a big fan of the new tools and tech in the DIY research space since they make research more accessible. “DIY” is almost a misnomer now, since most platforms will guide you through the process. Ultimately, this enablement is a force for growth in our industry as it provides more exposure to what’s possible when decisions are driven by data.

Before you start down the DIY path, here are three questions to ask yourself. Your answers will help determine if DIY is going to be a true time and budget saver, and if you have the ability & time to get a “close enough” answer.

1 – What are you trying to decide? Determining your research purpose

Let’s consider two decisions – first, whether to launch a new product that will require millions in production investment and marketing support and second, how to determine what the 100 attendees at your recent lunch-n-learn thought of your presentation.

If you are launching a product, we’d consider that a BIG decision with far reaching impact, and lots of risk.

If you are determining what the 100 attendees at your recent lunch-and-learn thought of your presentation, there is more risk in not gathering feedback versus gathering “inadequate” feedback.  A lot of this comes down to how the results will be used…for the event survey, you will likely read through most of the responses and you’ll filter the results based on what’s reasonable and actionable. In a way, each response could feel like an anonymous conversation with your audience because you have provided them with a feedback loop.

If your decision is closer to the second example, there is less risk in doing the research yourself even if you have little training or previous experience.

2 – How complicated are the questions that inform that decision? Defining your research objective(s)

Decisions are informed by answering research objectives – the actual questions a research project will address. It’s common to jump right to this step without defining your purpose, and that can lead to research objective overload. Filter your objectives based on your purpose to narrow down the question list.

Back to the new product launch decision, what do you need to know to inform your go/no-go launch decision? There are many research methods commonly used in this space including concept receptivity  (often compared to benchmarks), trial rate estimation, volumetric forecasts, price sensitivity, or market share expectations. These are more complicated topics and often involve advanced analytics.

Compare these to the types of questions you’d need to ask to have someone evaluate your recent presentation: overall rating, likelihood to attend future events / recommend, and open ended likes / dislikes are easy questions to construct and can provide great direction. In fact many DIY platforms have simple survey outlines/questions already built in that can be used for this type of application.

If your questions are simple, DIY platforms will often provide the guidance you need to compose a survey yourself.

3 – Who do you need to talk to and how will you find them? Defining your sample frame

A key component of research design is defining the sample frame: the universe of people from whom you will gather feedback. There are nuances in how a sample is defined that make a big difference in data quality, and costs, especially related to sample source and invitation balancing (who gets a chance to enter your survey).

Again thinking of the new product launch, let’s assume you are gathering feedback prior to launching a new toothpaste flavor. Finding people that use toothpaste is easy enough, but you also need to make sure you have a representative sample of toothpaste users. And you should also know where your sample is coming from to ensure data quality. This is not impossible to do on your own, but it’s never a good idea to blindly buy an online sample.

For your lunch-and-learn, you have a known universe and likely a list of attendees to query. Your sample frame is predefined and you know exactly who you are reaching.

If you have a list of the people you need to gather feedback from or your sample is easily defined, DIY platforms can enable you to reach relevant respondents.

Other Considerations – Timeline & Bandwidth

There are a lot of automated DIY research tools that promise delivery of research results in just a few hours, and that type of speed is definitely possible with some tradeoffs and previous experience. Here are a few things that can slow down the process or take up more of your time than you anticipated:

– To effectively use even the most streamlined DIY tools you need to have addressed the previous 3 questions: research purpose, research objectives, and defined sample frame. These can take time to define internally, and often what slows research down is simply consensus on purpose,  objectives and approvals.

– If it’s your first time using a specific DIY tool, expect it to take longer – there’s always a learning curve.

– Once you obtain results, factor in the time it will take to craft a decision-focused report with a POV on what you are trying to decide. Simply organizing the information in a logical manner isn’t enough.

DIY tools are a great way to get research done as long as your expectations are reasonable. Don’t expect it to be a quick fix; assume you’ll likely need to do some “research” of your own along the way, and don’t be afraid to ask for help. When making the decision between DIY research or working with a research partner, balance the risk to your business with your know-how and bandwidth. Assessing these areas before you get started can help avoid rework and frustration.