Market Research Reports: Why Writing Skills Matter in an AI World

1. Writing is Thinking

One of my favorite quotes about the craft of writing is from Pulitzer Prize-winning historian David McCullough, who said, “Writing is thinking. To write well is to think clearly. That’s why it’s so hard.”

Leaning on AI for writing misses one of the great benefits of the writing process. Writing is a rigorous way to think through a problem and work out your ideas. Writing is not just an end product. The writing process is a pathway to discovery, no matter what your discipline. Nothing forces clarity of thought like writing. When I sit down to write a research report, I never know how it’s going to go. Because I don’t know where the writing process will take me.

Conceptual relationships I thought I saw in the data often don’t hold up under the scrutiny of the written word. Insights I thought were impactful lose their import when expressed in narrative form. But other conceptual connections emerge. And other insights gather steam through the process of writing the story.

My spouse and I have a running joke whenever I start to write a report. My wife Cheri – who, by the way, is a far better writer than me – asks, “How long will this one take?” My response is always the same. “I have no idea.”

And therein lies the dangerous temptation of AI. The last line of McCullough’s quote is perhaps the most important. Writing is not easy. It requires focus. Concentration. Hard work. Because of this, the AI easy-button is tempting.

But if you are in a business like I am that, at its core, is about ideas, don’t take the bait. Forgo the easy button and do the hard work of thinking through writing.

For us at RealityCheck, writing in complete sentences, paragraphs and pages is central to our analysis and reporting process. It’s a process we call Insights Journalism®. It is how we connect conceptual dots, test our theories through the rigor of narrative, and find stories that inspire our clients to act on the insights we report.

Another of my favorite quotes about writing is attributed to the sportswriter Red Smith. When asked if writing a daily newspaper column was hard, he said “Why no. You simply sit down at the typewriter, open your veins, and bleed.”

2. Writing is Analysis

Writing is not something you do after analysis. Writing is part of the analytical process.

In the market research business, those who use AI to summarize data and write reports are missing another crucial benefit that writing offers.

The critical relationship between writing and analysis is something many anthropologists and academic researchers know well.

Fieldnotes are critical to the anthropologist’s work. As the famed anthropologist Clifford Geertz once wrote: “I’ve often been accused of making anthropology into literature, but anthropology is also field research. Writing is central to it.”

Even the anthropologist’s endpoint – the ethnography – has writing at its core. The literal translation of the term ethnography is writing (graphy) culture (ethno).  

Similarly, the best qualitative researchers write “analytic memos” as they code, categorize and analyze data.

In his book, “The Coding Manual for Qualitative Researchers,” Johnny Saldana writes, “…whenever anything related to and significant about the coding or analysis of data comes to mind, stop whatever you are doing and write a memo about it immediately. The goal is not to summarize the data, but to reflect and expound on them.”

Put more simply, the sociologist Adele Clarke wrote, “Memos are sites of conversation with ourselves about the data.”

At RealityCheck, our analysts and strategists are taught to ping back-and-forth between the data and the written word; between statistics and narrative; between tabulation, correlation, categorization, and story.

Writing can and should be much more than summarizing and reporting your analysis. It should be part of your analytical journey.

3. Writing is Personal

Finally, writing—your writing—still matters in an AI world because writing reflects your unique voice. The more AI becomes the primary author of content in a given discipline, the more all deliverables in that discipline will begin to sound the same.