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May 23, 2025
Is holiday-season research still risky? Explore how globalization and mobile-first surveys are reshaping cross-cultural research timing and response strategies.
Navigating cross-cultural research during holiday seasons can be frustratingly inconsistent. In one country, August might be a dead zone, while in another, it’s business as usual.
The traditional advice is to pause or delay data collection during these periods. One rationale is that response rates are lower, as consumers are away traveling or busy with family activities. Another rationale is sample bias, as those that are available to respond during holiday seasons may not be a representative cross-section of the population.
However, these assumptions may still be tied to pre-digital behaviors. While these concerns still exist with research buyers, the landscape has evolved. In a world of globalization, chronically online respondents and mobile-first research, does this traditional advice still hold true?
One key challenge in cross-cultural research projects is that “holiday season” is not the same everywhere. So, there is never an ideal time to run all your research at the same time. While the Northern Hemisphere's summer is typically June to August, the Southern Hemisphere’s summer is December to February.
This list is by no means exhaustive but gives a glimpse into the diversity and demonstrates why cultural context matters here. Some holidays are mainly celebratory, while others require religious observance and family obligations.
While Ramadan or Christmas are often considered in research planning, lesser-known holidays can also impact engagement in specific markets., e.g. Navratri in India or Nowruz (Persian New Year). To complicate matters further, some consumers live outside their home country but still adhere to their native holiday schedules, so diaspora dynamics should also be factored in.
Not all cultural holidays are formal breaks. If they fall near weekends, then consumers may use “bridging days” to extend their time off work, so there is a “hidden holiday effect”. However, with the rise or remote work, workcations and bleisure travel, work and holidays are blurring. This means that respondents remain digitally accessible even during holiday periods.
This higher digital reach is particularly relevant for mobile and online surveys, digital as respondents can participate in surveys everywhere – equally from the beach or from the ski lodge. Nevertheless, even if consumers are technically "reachable" during a holiday season, are they in the right mindset to give thoughtful responses? You could argue that consumer attention may even be higher, as consumers have more leisure time and may be more willing to participate in surveys. Engagement might be possible, but data quality could still suffer if consumers are distracted or fatigued from travel. Therefore, researchers should use attention checks to filter out low-quality respondents.
While traditional research methods (e.g. F2F, CATI) may suffer during holiday seasons, modern research methodologies, such as social listening, may be more useful, as consumers scroll and engage more during downtime. The opportunity here is to use this strategically, e.g. by testing holiday-specific sentiment or looking at how relaxation influences purchase behaviour.
While traditional holiday seasons still impact consumer behavior and travel, our digital habits, remote work and changing cultural behaviours are making research possible all year round.
Rather than a blanket pause during holiday seasons, researchers should develop a hyper-localized approach for their research projects. PESTLE analysis (Political, Economic, Social, Technological, Legal, and Environmental) can be used as an advanced methodological framework to examine additional drivers, e.g., France’s “droit à la déconnexion” gives workers the right to ignore work emails, while research participation declines during monsoon season (June-September in India, Thailand).
Using the PESTLE approach, researcher can develop a global "holiday heatmap" for research scheduling based on local and regional factors, extending data collection periods where needed to avoid sample bias.
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The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.
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