Question 1

Can ethnographic studies be done remotely without losing quality?

Accepted Answer

Yes, ethnographic studies can be done remotely without losing quality, provided researchers use the right approaches to capture rich context. Techniques like video diaries, virtual interviews, and even live video tours of participants' environments allow researchers to observe authentic behaviors and surroundings from afar. For example, a participant might film their morning routine using a product and narrate their thoughts, which the researcher can analyze almost as if they were there in person. The key to maintaining quality is careful design: use reliable technology, build trust and rapport with participants over video, and supplement self-reported data with photos or sensor readings when possible. With these measures in place, remote ethnography can yield insights comparable to those from on-site fieldwork in many cases.

Question 2

Is an RCT always the gold standard for public programs?

Accepted Answer

Randomized controlled trials (RCTs) are often considered the gold standard for evaluating public programs because they can show cause and effect clearly, but they are not always feasible or appropriate. In real-world public interventions, strict random assignment may be unethical, too costly, or impractical — if an initiative must serve an entire community or it's urgent, you can't withhold the program from a control group just to run an RCT. For example, a city-wide education reform or disaster relief effort can't randomly exclude some residents; instead, evaluators might use quasi-experimental methods like matched comparisons or pre-post studies to assess impact. In essence, an RCT is ideal when conditions allow, but many public sector evaluations rely on alternative rigorous designs to get credible results when an RCT isn't possible.

Question 3

How should we collect feedback from non-desk logistics workers fairly?

Accepted Answer

To fairly collect feedback from non-desk logistics workers, meet them on their terms with accessible, flexible methods that respect their time and working conditions. For example, use mobile-friendly surveys or text-message questionnaires that they can complete during a break on their own phones, or set up a kiosk or tablet in a common area for quick feedback. Keep the format short and simple — just a few straightforward questions, possibly offered in multiple languages — so it doesn't become a burden or require a computer. It's also critical to ensure anonymity and to communicate how their input will be used; these workers need to feel safe and valued when sharing opinions. By tailoring the process to their environment (e.g. scheduling around shifts and avoiding disruptive times) and providing multiple ways to respond (phone, paper, or in-person discussions if needed), you make feedback collection as inclusive and fair as possible.

Question 4

When should we localize ideas before global co-creation workshops?

Accepted Answer

You should localize ideas ahead of a global co-creation workshop whenever cultural or language nuances might not carry over to all participants. If a concept was developed in one market (with region-specific humor, examples, or jargon), it's best to adapt or translate it for other locales before the joint session. For example, a tagline or product idea that makes sense in one country might confuse or even offend in another if left in its original form. By localizing key ideas beforehand, you ensure that everyone enters the global workshop with a clear, culturally relevant understanding of the concepts. In short, whenever an idea could be misinterpreted or lose impact outside its home context, localize it first so the co-creation discussion stays productive and inclusive.

Question 5

When should MMM reconcile with platform conversion-lift studies?

Accepted Answer

You should reconcile your MMM with platform conversion-lift studies whenever you have credible lift data for a channel — especially if the MMM's findings differ from what those experiments show. Platform lift studies (like Facebook's or Google's conversion lift tests) provide hard evidence of incremental impact. So, for example, if your MMM says social media contributed X%, but a well-run Facebook lift test shows a different contribution, that's a flag to align the two. Typically, this reconciliation happens during MMM updates or recalibrations: you feed the lift results into the modeling process as calibration points or constraints. In practice, many firms do this annually or quarterly. After big campaigns, if a platform provided lift metrics (say, YouTube showed a 10% sales lift from ads), you'd use that to tweak your MMM so it doesn't over- or under-credit YouTube going forward. In short, whenever high-quality lift studies are available, use them to sanity-check and refine your mix model. It ensures your MMM stays anchored in experimental reality, improving its accuracy and the trust stakeholders place in its guidance.

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Market Research FAQs with Expert Insights

Can ethnographic studies be done remotely without losing quality?

Is an RCT always the gold standard for public programs?

How should we collect feedback from non-desk logistics workers fairly?

When should we localize ideas before global co-creation workshops?

When should MMM reconcile with platform conversion-lift studies?