Produce Ph.D. Level Insights Without a Statistics Degree

Research Managers are often squeezed. Projects frequently take longer to execute than expected, whether it's because of a client that takes his/her time providing input on the survey, because of a tough recruit, or something else altogether. Longer project execution results in less time for analysis. We've all been there. It's crunch time until final delivery. Unfortunately, most researchers are beholden to a Marketing Sciences team to run the analytics they'll use to craft their most essential presentation piece, the recommended plan of action. As a result, Research Managers often are left feeling handicapped (and perhaps resentful) because there is only so much they can do on their own with simple crosstabs.


Many organizations' analytics departments are overwhelmed because statisticians can only work so fast (and there's not that many of them!). Much of what they do relies on painstaking accuracy that just can't be rushed. Market Research Managers need an automated data analytics tool that doesn't leave them waiting; a platform that produces sophisticated results that are so intuitive anyone can create and understand them.

 

Break Up the Bottleneck

With a real shortage of available high-level statistical horsepower across the industry, wouldn't it be nice to democratize advanced analytics? Why should so many rely on so few when it comes to crunching the numbers for storytelling and strategic insight? 

A way to break up these organizational bottlenecks while still ensuring you are producing sophisticated models is finding an automated data analytics tool that everyday researchers without a Ph.D. in statistics can use. When looking for a platform, it is crucial to find one backed by sophisticated technology and testimonials from others in your field. Vet platforms to see if they have any highly-esteemed credentials or partnerships with innovative programs. For example, Inguo's underlying algorithms are backed by the NEC Corporation, a world leader in computing and all things technology. 

Automated data analytics tools should be so intuitive you have total confidence in your ability to produce what you need to stay on track. Fortunately, most researchers are pretty self-reliant, especially given shrinking budgets over the years (significantly exacerbated with COVID-related cuts) and a push for DIY tools that make sense. 

 

Know the Punchline Before Delivering the Joke

What happens today when a Research Manager dives into a dataset? Typically, it's on a Research Manager to comb through the crosstabs and generate a story about what is happening in data. But what if this process was completely reversed? Turned on its head. What if the Research Manager didn't have to wait on advanced statistical outputs to come from someone else. If they could produce these outputs themselves, they'd be in a much better place to quickly understand the research narrative and reap report-writing efficiencies. It'd be just like knowing the destination before you started the journey or knowing the punchline to a joke before it was delivered.  

One of the most effective outputs for data visualization and understanding is the causal graph. Causal graphs reveal surprising patterns and connections, making data-driven insights accessible to people at all levels throughout an organization (and with varying statistics backgrounds). These data visualization outputs can also allow audiences across various departments and specialties to understand its meaning. 

A causal graph can help researchers understand how all attributes are interrelated and, most importantly, the key drivers that will move the client's KPIs. If you have this information first, your narrative has direction, and you can supplement your story with bar charts and line graphs afterward. It leads to a more focused story and report-writing efficiencies that aren't possible when reviewing crosstabs alone.  

Start Producing Ph.D. Level Insights

You don't need a Ph.D. or knowledge of advanced analytics and predictive modeling to create causal graphs. Market Research Managers can make the most sophisticated analyses through automated data analytics platforms and use the outputs to tell great research stories without waiting in line.

 

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