Week 5: Tracking the Trends
March 31, 2026
What’s up, trend trackers! Welcome back to Week 5 of my blog! Continuing on from last week, I’ve continued collecting key data that will support my full analysis later on. In recent weeks, I focused on identifying periods with no advertising and gathering the Google Search Trends for each of my selected drugs.
New Data
If you’re interested in exploring the data on non-advertising periods, feel free to check out the fourth tab on the same Google Sheet from last week!
docs.google.com/spreadsheets/d/163-6EA6IB6Wc043hF1K0sJT0yqWN5yuMI4Wk4RopeS0/edit?usp=sharing
Following my methodology, I used Google Trends to track how search interest fluctuates for each drug over time. To improve accuracy, I collected data for both the brand names (Ozempic®, SKYRIZI®, and DUPIXENT®) and their generic names (semaglutide, risankizumab, and dupilumab). I also limited my data to the United States to maintain consistency with my airtime data and to keep the data collection process focused.
Additionally, I utilized multiple Google Trends categories, namely web, image, news, Google Shopping, and YouTube searches, to better capture the different ways people may be engaging with the specific terms online.
Furthermore, it’s important to note that Google Trends does not track the exact amount of times a term was searched throughout each month. Instead, it reports data on a relative scale from 0 to 100, where 100 represents peak popularity within the selected time period, 50 indicates half the popularity, and 0 suggests insufficient data. This means that my data reflects proportional changes in interest rather than an absolute search number.
With this in mind, I plan to use these values as indicators of relative public awareness and align them with my other datasets. Additionally, since Google Trends reports data on a monthly scale, I will have to adjust all my airtime and sales data to match this timeframe for accurate comparisons.
If you’re interested in exploring the search trend data, feel free to check it out here:
https://docs.google.com/spreadsheets/d/1W0KJ-N1_Ch1uZXbPoitE0uAwdygc0SF7_c7ogmgqeCs/edit?usp=sharing
With search trends now recorded, the next step is to expand beyond and begin capturing how these drugs show up across social media. Catch you in the next one!
Citations
Google Trends. “Google Trends.” Google Trends, 2025, trends.google.com/trends/.
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Hi Caitlin,
It’s interesting that Google Trends presents you with a scale of popularity for terms instead of exact search data. And it looks like your drug airtime data is also monthly! Will you be getting data for social media published by social media sites themselves, similar to Google Trends, or are they primarily from third-party information organizations?
Hi Aarohi! For the social media sites, I also relied on a third-party information organization since the social media site I selected doesn’t readily provide the accurate number of posts with a keyword.
Hi Caitlin! Your data collection process has been very thorough so far, and you’ve done a great job at considering how drug popularity can be identified. I like how you not only looked at both the brand and generic names, as well as how you incorporated multiple search categories into your data. Since you mentioned that Google Trends provides search frequencies on a relative scale, do you think that this will limit your analysis in any way? Would it be possible to find other databases with these search trends, but with absolute numbers rather than proportional changes?
Hey Chloe! After posting this, I actually found another database with these search trends in absolute numbers funnily enough! If I did still happen to rely on the proportional changes, I think it would’ve limited my analysis though.
Hi Caitlin, great progress! Your methodology seems very detailed and practical. I love the way you explained how you are collecting your data; it was explained very clearly and understandable. Excited to see what your results yield!