Veteran marketers trust their intuition, but human behavior is fundamentally unpredictable, as shown by phenomena like pandemic-era toilet paper hoarding. This highlights the necessity of constantly testing assumptions rather than relying solely on experience.
Many marketers claim customer obsession but don't conduct research. True obsession means understanding the irrational "why" behind choices, like a mom buying organic strawberries for her kids but non-organic broccoli for her "already cooked" husband.
To ensure research is actionable, it must answer one precise question, like "red or blue package?" Project scope creep, where multiple teams add their own questions, leads to bloated, confusing data that sits unused and obscures the primary goal.
Using general LLMs like ChatGPT to create surveys can lead to biased results. These tools lack foundational research best practices and are designed to please the user, which can subconsciously embed the prompter's bias directly into the survey's language and structure.
Consumers often misrepresent their actions in surveys (the "say-do gap"). To get honest answers, frame questions to be less judgmental. Instead of asking "How often do you go to the gym?" ask "How often do you wish you could go?" to uncover the truth.
Instead of asking customers to evaluate 50 options, use AI as a "BS layer detector" to identify the top three contenders. This saves time and budget by focusing human-led research on a pre-vetted, smaller set of choices for final validation.
AI's strength is synthesizing vast amounts of past data to find trends, a task that once required a dedicated analyst. However, it cannot predict the future because it lacks an understanding of irrational human behavior, which drives unpredictable viral trends.
AI won't take marketing jobs, but it will consolidate them. Repetitive tasks will be automated, forcing marketers to evolve. The survivors will be those who master AI to handle tactical work, freeing them to upskill into strategic functions like market research.
As AI commoditizes content creation, the most valuable asset is unique, proprietary data that LLMs cannot access. Marketing teams that own the research function can generate this first-party data, creating a defensible moat and establishing true thought leadership.
Top-of-funnel metrics are vanity if they don't lead to revenue. Effective marketers must look beyond lead volume and own the entire customer lifecycle, analyzing downstream metrics like lead quality, conversion rates, and win rates to measure true campaign effectiveness.