The Whole Truth: How to Boost Decision-Making Confidence from DIY Research

Brands often consider bringing market research in-house using DIY tools to save money from outsourcing to agencies. While DIY may be a popular way to conduct research, it is not always as easy as it seems - either in the beginning of the project, or in the final analysis. Completing the entirety of the project demands rigor in application and a commitment to ensure accurate ROI-focused recommendations are properly delivered to internal teams. 

Getting started with DIY research can be laborious, with much room for error throughout. At inception there are details not to be missed with writing the screener and a methodically unbiased survey. Between capturing the right data, programming the study, and getting the right qualified sample, there still needs to be adequate time for analysis. When an unexpected bump in the road occurs, time compression of projects become a reality. In managing the entire project, the possibility for one piece to be rushed at the expense of another can happen.  When crunched for time, it is often the analysis phase that suffers - which nobody wants.

Errors in interpretation of the data can have devastating business impact. Imagine delivering incorrect recommendations to the Chief Customer Officer about CX behavior. This kind of mistake can set a succession of mistakes into action and ultimately create a financial loss greater than the cost of outsourcing the entire project. 

But the reality is that brands need research done and budgets and time constraints pose real limitations. When it comes to new product development, assessment of brand loyalty, knowledge about consumer intent to purchase and more,  a consumer insights tool is needed to bring confidence to the business decision at hand. Even when DIY is not ideal, but a reality there are simple steps you can take to help ensure proper management of resources and maximized integrity for any consumer research study. 


Use Technology to Your Benefit

Seasoned researchers know that bias can find its way into any research process. Confirmation bias is one of the most endemic forms of narrow-mindedness in research. Confirmation bias occurs when researchers form a hypothesis or belief and use the respondents' information to confirm that belief. This bias follows through and extends itself into analysis when researchers tend to remember points that support their hypothesis. Ultimately, research can suffer and be distorted from this bias. 

As humans, we are complicated. Unconsciously, our emotions and preconceived notions often distort our ability to think objectively when analyzing data. But technology, when used properly, can be an excellent asset for eliminating bias and fact-checking. That is why online data analysis platforms rather than humans are best at analyzing data based on facts and trends. Using technology to your advantage will allow you to uncover those ROI-focused recommendations hidden in the data your online surveys collected. 


Tell Better Stories With Data

Most market researchers are not statisticians and are only looking at basic cross tabs built into their DIY platform. Some survey platforms even allow the brand researcher to leverage simple data analytics like correlation, though these outputs never result in specific, ROI-focused recommendations. The way forward is always too fuzzy. And it is a fact that correlation is not causation. These cross-tab reports do not give enough strategic guidance to generate ROI-focused recommendations that could allow you to focus actions on what is going to move the needle. 

Even when market research agencies complete analysis, the result is often a list of high-level recommendations from derived importance. In the end, analysis suffers from a lack of clear and concrete direction that can only be understood when the data is put into context. While a market research agency may provide seven recommendations on under-performing attributes, none of these are accompanied with strategic analysis or contextual understanding of the insights. These broad-brush recommendations often leave brands stuck and unclear on the next best step for product development teams, engineers, or marketing leads. Weaving a story, and coming to the table with concrete, strategic recommendations is difficult when there is so much data and little contextual meaning for that data. 

Analysis that leads to positive business impact includes key factors that can drive your KPIs and help your brand achieve stated goals. Expert contextual analysis will ultimately help your team tell better stories with data that clarifies a way forward. Selecting an appropriate online data analysis platform to deliver clear, concrete, and strategic recommendations to your internal teams is the single most important factor in quickly bringing data to life and informing strategy. 

Check for Alternative Explanations

Often, when teams are deep into the research process, the view becomes very myopic. It is critical to take a step back and consider alternative outcomes. Ruling out and considering alternative results can lead to significantly more robust understanding of the data. With vast amounts of data, you cannot test every scenario. The human brain can only process so many variables. This is why causality models are key to uncovering new insights relating to cause and effect.

Technologies that create sophisticated causality models ultimately save time and energy when completing research projects. Any high-functioning consumer insights tool should provide you with alternative simulations to see how you can improve the outcome by changing different values of the data. These alternative explanations can be a great asset to your research projects. When variables cannot be manipulated multiple possibilities are missed which translates into missed business opportunities. 

Ultimately, when it comes to giving recommendations to internal teams,  confidence in the data is required. Whether completing CX research, new product development testing, ad testing, path to purchase evaluation, or solving for any other important business question, the proper data analytics tool can eliminate the chance of error, misinformation, or misleading interpretations of the outcomes. Critical thinking at every step is required to offer innovative solutions to shape any company's future. Investing in the proper resources such as a data analysis platform creates decision-making confidence and avoids compromise in DIY research endeavors. 

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