Question 1

How do we prove repository use leads to fewer ad-hoc research requests?

Accepted Answer

To prove that using a research repository leads to fewer ad-hoc requests, you'll want to show a correlation between repository engagement and a drop in new project commissions. Start by tracking how often teams access or search the repository (usage analytics) and then see if there's a corresponding decline in one-off research requests on similar topics. If, for example, the marketing team frequently pulls past study insights from the repository and you observe, say, a 20% reduction in new survey requests quarter-over-quarter, that's evidence of deflection. Supplement quantitative data with anecdotes: team members might report that finding existing answers prevented them from launching a redundant study. Together, usage metrics and a measured decrease in duplicative research build a compelling case that the repository is cutting down ad-hoc requests.

Question 2

When is scenario planning critical to strategic decision-making?

Accepted Answer

Scenario planning becomes critical when a company faces high uncertainty about the future. If your strategic decisions involve long time horizons or volatile factors (like emerging technologies, regulatory changes, or geopolitical shifts), scenario planning is the tool that prepares you for multiple eventualities. Rather than betting on one forecast, teams develop a few plausible scenarios (best-case, worst-case, etc.) and strategize responses for each. This is especially important in situations like entering a new market or during global economic instability — essentially whenever the stakes are high and the path ahead isn't clear. By stress-testing decisions against different scenarios, leaders gain flexibility. In summary, when the environment is uncertain or rapidly changing, scenario planning is critical to ensure your strategic choices are robust under various future conditions.

Question 3

How does synthetic data help with hard-to-reach survey populations?

Accepted Answer

Synthetic data can extend insights for hard-to-reach survey populations by generating realistic, representative data points when actual respondents are few or inaccessible. For example, if you only have a handful of responses from a niche demographic, you can use statistical or AI models to create additional synthetic records that mirror the patterns of that group, effectively boosting the sample size. This approach allows analysis or modeling without needing to directly survey more members of that elusive population, and it can protect privacy since the synthetic respondents aren't real individuals; the key is that the synthetic data must be grounded in actual observations and validated for realism — when done properly, it helps researchers explore trends and outcomes for rare or sensitive groups that would otherwise be too small to analyze reliably.

Question 4

When is it appropriate to conduct a longer-than-average survey?

Accepted Answer

It's appropriate to field a longer-than-average survey only when the target audience is highly motivated or specialized enough to handle the extra length. For instance, B2B professionals or enthusiasts on a niche topic might willingly spend 30+ minutes on a survey if they find the subject matter relevant and engaging. In such cases, it's critical to communicate the time commitment up front and ensure the survey is well-structured - perhaps broken into clear sections with progress indicators - to keep people engaged. A longer survey should earn its length: every question must serve a purpose and ideally provide value or insight to the respondent as well. Often researchers will offer a strong incentive or the promise of seeing the study results, as appreciation for the respondent's time. In summary, go long only when you have the right audience and design to support it.

Question 5

What ethical considerations apply when tracking the same participants over time?

Accepted Answer

When tracking the same participants over time, researchers need to uphold strict ethical standards around consent, privacy, and participant well-being. First, informed consent must be ongoing: participants should know they're part of a longitudinal study and be reminded that their continued participation is voluntary (with the right to withdraw at any point). Privacy is crucial as you accumulate data on individuals — personal information must be securely stored, and any reporting should anonymize their identities to prevent someone from being recognized in the findings. Researchers also have to minimize participant burden and potential discomfort; checking in repeatedly can become intrusive, so it's important to space out contacts reasonably and only collect necessary information. By being transparent, respecting boundaries, and protecting data confidentiality throughout the study, you address the key ethical considerations of long-term participant tracking.

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Market Research FAQs with Expert Insights

How do we prove repository use leads to fewer ad-hoc research requests?

When is scenario planning critical to strategic decision-making?

How does synthetic data help with hard-to-reach survey populations?

When is it appropriate to conduct a longer-than-average survey?

What ethical considerations apply when tracking the same participants over time?