Compressing Research Timelines Without Sacrificing Quality

Use these strategies to do faster research and adjust research timelines without compromising accuracy or insights.

We know it. You know it. Research teams are under immense pressure to deliver high-quality results quickly without compromising the integrity of their findings. The challenge lies in balancing the need for speed with the need for accuracy and depth.

It’s all possible with AI-powered research platforms, the right mindset, and good research timelines. Speed and quality can go together.

Why research timelines matter

Research timelines are crucial for keeping research projects on track and ensuring all stakeholders are on the same page.

"The timeline helps the project meet its goals," said Suzanne Walsh, research consultant at Remesh.

Bill Cullo, research consultant at Remesh, echoes this sentiment. He says timelines are essential for keeping projects moving forward smoothly.

"It is critically important that people have an understanding of ‘the first draft of this guide is going to be ready by x date, you have two days to look at it,’" he says. It keeps people accountable and keeps projects moving."

The way it used to be: Example of research time frame

In the not-so-distant past, research projects could take weeks or even months to complete from start to finish. With traditional surveys, researchers had no choice but to wait until all the data was collected before they could even begin analyzing it.

"Depending on the population you're trying to talk to, it could be weeks before your target participants have completed the survey," Suzanne says.

Focus groups were similarly time-consuming endeavors.

"In terms of really being able to look at the whole dataset, especially if you're running multiple focus groups on a topic that used to be weeks of time," Suzanne recalls.

Who has the time? Nobody, anymore.

Picking up the pace with technology

Today, new technologies are making it possible to significantly compress research timelines without sacrificing quality.

"For example, take the Remesh platform," Suzanne said. "Immediately, you get percent agreement scores on your questions, and you have all of your polling data. So you have insights that not only didn't exist before, but are available immediately to you."

This kind of real-time analysis is an absolute game-changer for researchers.

"The greatest utility of this platform is not in exploring the question of what percentage thinks this or that," Bill says. "The greatest utility is discovering why people feel, think or do what they do."

With the power of AI, insights surface quickly and allow research teams to dive deeper way quicker than used to be possible.

Of course, there are inherent risks in trying to compress research timelines too much, too quickly. The results still need to be interpreted correctly, which is why the human researcher is needed.

"If people don't know what they're looking at, they don't know what they're looking at," Suzanne said. In other words, researchers without experience interpreting data and extracting meaningful insights may be more likely to draw the wrong conclusions.

AI is increasingly important in enabling researchers to uncover deeper insights in less time.

By using AI to surface key insights quickly, researchers can dive deeper into the underlying drivers of consumer behavior, even when working on a compressed timeline.

AI-powered platforms can rapidly analyze large amounts of data, identifying patterns and themes that would take human researchers much longer to uncover.

Starting with a strong foundation

So, how can research teams ensure they deliver quality insights that can be trusted, even when working on a tight timeline?

Start with a clear objective.

"Quality research stems from a achievable objective," he says. "Not, hey, I want to figure out what consumers are going to buy. And if they're going to buy this new product, or what it is about my product that they would love, and then in turn is going to make them buy more. That's too broad."

Having a thoughtfully crafted discussion guide is also absolutely essential.

At the end of the day, the role of the researcher is to provide context and meaning to the data. That's still true - even in a fast-paced research environment where time is of the essence. And as the speed of business keeps ramping up, it's important to use the tools that help them move faster - without losing quality in their research.

The bottom line

Undoubtedly, research teams face more pressure than ever to deliver meaningful insights at an increasingly breakneck pace. Compressing research timelines doesn't have to mean sacrificing quality or accuracy.

By leveraging cutting-edge technologies, starting with clear and achievable objectives and providing expert analysis and context, researchers can deliver meaningful insights. Insights that move the needle for their organizations, even when working on the tightest of timelines.

The key is to find the right balance between speed and depth and to never lose sight of the ultimate goal: understanding the "why" behind consumer behavior.

Embracing new technologies and methodologies is essential for keeping pace with the demands of stakeholders and the market. However, the need for speed must not come at the expense of quality insights.

Researchers must continue to strike the right balance between efficiency and depth, leveraging the power of AI and automation while still bringing their unique expertise and perspective to bear. By doing so, they can continue to deliver the high-quality, impactful insights that drive business success in an ever-changing world.

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