Google Trends and the "honey bee season"

Here I'm using Google Trends to see whether Google search words correlate with the "bloom season" or "honey bee season".  My use of Google Trends is an interesting works in progress and its utility is yet to be determined.   Google Trends filter using: 

• Google search words
• date
• location 

Web marketers use Google Trends to purchase Google Ads.   In public health, data scientists use Google Trends and other social media to track COVID-19 symptoms (loss of taste or smell), suicide risk and food poisoning.

I picked my "honey bee season" search words and time range in a trial-and-error manner and arrived at these choices:

Google Trends search words & why

• "bee removal" - surrounded by quotes, this filters for these two words in this order.   Here I'm using this as a surrogate for the "bloom season" or "honey bee season" and trying to avoid other Google searches which include the "bee" search word  (for example, spelling bee).
  

Google Trends time range & why

• 5 year range - accumulates search results into weekly bins which reduces noise
  

Viewed at United States scale, Arizona, California, Florida, Texas and Nevada are top contributors to these Google search words.   These data points are noisy with the lowest number of Google searches at the start of each year.   I used a triangle (saw tooth) curve fit as dashed lines and the peak signal date appears on the graph.

I choose 4 states that are located in the eastern third of the continent, which stack more or less south-to-north and which have sufficient data points to analyze.  State based data points are even more noisy than the combined states data points.  I set my noise concerns aside and fit each year using my triangle curve method.  In general and consistent with the south-to-north bloom calendar, Georgia or North Carolina peak first and Pennsylvania or Michigan peak last.

Georgia	North Carolina	Pennsylvania	Michigan
April 1, 2017	August 26, 2017	August 12, 2017	August 19, 2017
June 30, 2018	July 28, 2018	September 2, 2018	August 19, 2018
April 6, 2019	April 20, 2019	September 7, 2019	August 18, 2019
May 10, 2020	April 4, 2020	August 22, 2020	August 22, 2020
(week number)	(week number)	(week number)	(week number)
13	34	32	33
26	30	36	34
14	16	36	34
20	14	34	34