National Diabetes Month Isn’t the Best Month for Diabetes Awareness or Engagement
A Statistical Search Analysis of National Diabetes Month
November is National Diabetes Month.
Working for a pharmaceutical advertising firm as a content, search, and analytics strategist means I spend a lot of my day concerned with rising and falling trends across the Internet within specified disease states.
This constant day in and day out effort to understand the search and interest trends of patient populations, caregivers, and medical professionals, has sparked some questions in my mind as to the intended engagement plays across disease state audiences.
With this in mind, I began thinking about National Diabetes Month in the context of how patient vs. caregiver vs. medical professional keyword parsing as top level keywords relate to drilled terminologies and how search indicates population difference within the diabetic community.
For this analysis, I used the following methodology and data sources:
- Location: Worldwide
- Timetable: 5.1 years — October 1st, 2012 to November 4th, 2017
- Search Boundaries: Search Terms, Disorders, Topics
- Search Categories: Web, News, YouTube
- Google Trends
- Google Search Landscape Results
November Isn’t the Best Month for Awareness or Engagement
As you might imagine, as a top level category, both Type 2 Diabetes and Type 1 Diabetes, trend in an almost mirrored pathway with the only major difference being Type 2 Diabetes outperforms Type 1 Diabetes by a factor of 2.5%. Interestingly enough, with November being National Diabetes Month you would expect to see a yearly rise in online searches, based on advertising campaigns and general rise in awareness, when compared to the other 11 months of the year, however this isn’t the true
Instead, you see a pretty steady pattern of Diabetic search trends peaking in October, a month before national awareness.
When you roll both Type 2 Diabetes and Type 2 Diabetes into the mix as a disorder (T2D) and a topic (T1D), on top of a search term (measured differently), the results grow in volume yet mirror in relation:
The same is true for News searches:
The same is true for YouTube search activity:
Deeper Search Trends
The above approach centered on top level search terminologies to highlight trends across a 5.1 year time table. Now, while it is true most keyword based searches will bubble up to the top level keyword in a category (“Type 2 Diabetes Insulin Pumps” falls under the hierarchy of “Type 2 Diabetes” and more generally, “Diabetes”) the more interesting results begin to emerge when looking at long tails + natural voice search results.
Take for example the following five drilled Type 2 Diabetes keywords:
- Type 2 Diabetes Treatment
- Type 2 Diabetes Cure
- Type 2 Diabetes Medications
- Type 2 Diabetes Pumps
- Cure for Type 2 Diabetes
As you will notice, all hinge on the same variation yet as a wildcard, the last search term flips the equation of:
Disease State + Context
Context + Disease State
Taken from a 30,000 foot view, the results of search trend analysis mirror the aforementioned study of disease state awareness.
However, when you dig into the data, the results suggest in terms of drilled keyword context, November and October play a similar role to one another wherein long tails and natural voice search trend more even across months than high level category awareness.
With this data, a question needs to be asked: even though we are currently heading into what one would expect would be peak diabetic population awareness and engagement, if marketing/advertising/pharmaceutical companies wait until November to conduct a marketing push, have they missed their window by 31 days?
The data would suggest yes with high level relevance and somewhat with contextual deeper awareness/activation.
Maybe it’s time to rethink how and more importantly, when, the diabetic population is activated and engaged.
Brad Yale can be reached at email@example.com for comment.
While he understands the want to follow national days/months and gut feelings, he believes data rigor should be applied to every marketing decision.