Question 1

How do I make a credible business case for ethnography versus surveys?

Accepted Answer

To justify ethnography (immersive observational research) versus just surveys, highlight what unique value it provides and how that translates to business outcomes. Emphasize that ethnography uncovers the "why" and unspoken behaviors that surveys often miss. For example, maybe surveys showed decent satisfaction scores, but an ethnographic study revealed customers struggling with a product in their daily context - a hidden pain point that, once solved, significantly increased retention or sales. Frame these insights in dollar terms or KPIs: the improvement might reduce churn by X% or open a new market segment, adding tangible value. Also compare costs: ethnography is more upfront investment, but point out how much a failed product launch or a misread customer need would cost the company (often far more than a few field studies). By providing a concrete success story and a clear ROI argument (value gained vs. research cost), you'll make a compelling, credible case that ethnography isn't a "nice-to-have" but a strategic necessity for deeper insights that drive growth and prevent costly missteps.

Question 2

Is a dozen high-quality IDIs too few to inform a major decision?

Accepted Answer

Twelve in-depth interviews (IDIs) can provide robust insights, but whether that's enough for a major decision depends on the consistency of the feedback and the stakes involved. In many studies, by around a dozen interviews you reach "saturation" - the same themes keep coming up - which suggests you've captured the major insights. If those 12 well-selected participants all underscore a clear point (say, every interviewee dislikes a particular feature), that's strong directional evidence even for an important decision. However, if the stakes are very high, it's prudent to validate further. You might use the IDIs to form a hypothesis and then run a survey or a few more interviews to ensure no critical viewpoint was missed. In summary, a dozen interviews can absolutely inform a big decision, but for a mission-critical call it's wise to corroborate those qualitative findings with additional data just to bolster confidence.

Question 3

When should I run IDIs after a survey to explain unexpected results?

Accepted Answer

You should schedule in-depth interviews (IDIs) whenever a survey yields puzzling or unexpected findings that need more context and explanation. This typically means right after analyzing the survey results-while the data is still fresh-to probe into the why behind the numbers. For example, if a particular segment of respondents gave an unusual answer pattern or a key metric moved opposite to expectations, follow-up IDIs with some of those participants can clarify their reasoning or reveal hidden factors. It's best not to wait; conducting interviews soon after ensures people still recall their survey responses and that insights can feed into decisions promptly. In short, plan IDIs as the next step whenever the survey alone doesn't tell the full story of your findings.

Question 4

What are the potential pitfalls when deploying multi-country data collection?

Accepted Answer

Deploying data collection across multiple countries carries several pitfalls, from translation mishaps to legal complications, if it's not carefully managed. One big risk is poor translation or cultural mismatches in surveys and interviews--questions that make sense in one country may confuse or offend in another, leading to skewed responses. Sampling and logistics issues also crop up: a recruitment method or online survey platform that works well in one region might falter elsewhere due to differences in internet access, response habits, or panel quality. In addition, teams must navigate varying data protection laws and time zone challenges, which can delay fieldwork or require different handling of personal data by country. Without careful local adaptation and coordination, a multi-country study can end up with inconsistent data or insights that don't truly compare across markets.

Question 5

What regional data residency laws affect multi-country data integration?

Accepted Answer

Strict data residency laws in different parts of the world (like the EU, China, and Russia) can complicate multi-country data integration by limiting where personal data can live or be sent. For example, the European Union's GDPR requires that EU residents' personal data stay within the EU or only be sent to countries with adequate protections — this has led companies to use EU-based servers and legal mechanisms like standard contractual clauses for cross-border data flows. China's Personal Information Protection Law and Russia's regulations similarly mandate that citizens' personal information be stored on servers within their borders, forcing global firms to maintain local databases in those markets. When integrating data across borders, companies often must anonymize or aggregate certain datasets before moving them, or design systems to keep sensitive data in-region and only share permitted insights. In short, multi-country data integration must navigate a patchwork of regional laws by keeping data where it's legally required and using approved safeguards for any cross-border transfer.

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