Question 1

How should we capture total cost, not price, in choice tasks?

Accepted Answer

In choice-based exercises, present the total cost of each option--not just the sticker price--to ensure respondents weigh realistic trade-offs. This means incorporating all relevant expenses into the choice scenario, such as maintenance, subscription fees, or usage costs over time, rather than a single upfront price. For example, if comparing service plans, you might display the full annual cost of each plan (monthly fee times twelve, plus any extras) so participants consider what they'll actually spend. Emphasizing cumulative cost avoids a common pitfall: options that look cheap initially but end up more expensive in the long run. By capturing total cost of ownership in the task design, you get more accurate insights into true price sensitivity and value perceptions.

Question 2

How can AI help detect low-quality survey responses in real time?

Accepted Answer

AI can act as an always-on quality gatekeeper during surveys, spotting low-quality responses the moment they happen. For instance, machine learning models can be trained on patterns of bad data (like straightlining, random clicking, or implausibly fast completion times) and immediately flag a respondent who fits that profile. Natural language processing helps with open-ends: if someone types gibberish or irrelevant text, an AI system can recognize the nonsense and mark that response for removal or follow-up. Some platforms use anomaly detection to catch inconsistent answers (e.g., the respondent's age is 25 in one question but 45 in another). By integrating these AI checks into the survey platform, problematic respondents can be disqualified or prompted to clarify while they're still taking the survey. The result is cleaner data in real time - you're filtering out bots, inattentive participants, and bogus answers on the fly instead of discovering them only after fieldwork.

Question 3

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 4

What can packaging research tell us in addition to shelf appeal?

Accepted Answer

Packaging research can reveal much more than just shelf appeal--it provides insights into user experience, brand perception, and even purchase behavior. For instance, observing how consumers open and handle a package can uncover frustrations or delights (like a box that's intuitive to open, or a resealable pouch that encourages reuse). Good packaging studies also gauge whether the design communicates the product's benefits and brand values effectively; a design that's attractive but fails to convey key information might hurt sales. Additionally, packaging tests can highlight if a new format affects portions or usage frequency (e.g., single-serve packs leading to higher consumption). So beyond aesthetics, packaging research informs you about practicality, message clarity, and emotional impact, guiding refinements that enhance the total product experience.

Question 5

When should we use dubbing versus subtitling when testing concepts globally?

Accepted Answer

It depends on the audience and the importance of the original audio. Use dubbing when you want participants in each country to experience the concept as if it were made for them, without the extra effort of reading text. Dubbing is often best if the visuals are complex or the emotional tone in voice is critical - it helps ensure comprehension because viewers can focus on the imagery and message in their own language. On the other hand, subtitling can be effective when you need to preserve the original audio (say the voice of the original actor or spokesperson is important to the concept) but still provide translation. Subtitles are usually quicker and cheaper than producing multiple dubbed versions, and in markets where people are used to subtitles, it won't be a big barrier. So, if native-language immersion and ease of understanding are top priority (and budget allows), lean towards dubbing. If authenticity of execution or speed is more important - and the audience can handle reading - subtitling is a solid choice.

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Market Research FAQs with Expert Insights

How should we capture total cost, not price, in choice tasks?

How can AI help detect low-quality survey responses in real time?

Is an RCT always the gold standard for public programs?

What can packaging research tell us in addition to shelf appeal?

When should we use dubbing versus subtitling when testing concepts globally?