GRAS Analytics Framework
MakeUsWell created a platform of dynamic scores and segmentations. Our framework’s corresponding software and augmented analytics can be applied to consumers in the North American vaccination market.
- Ranks, scores, and predicts the likelihood of individuals and different segments to get any COVID-19 vaccine.
- Matches these people or segments with the right marketing messages and incentives to convert them. Consumers choose to get vaccinated as a result of segmentation, targeting, communications, and incentives.
COVID-19 uncovered, exaggerated, and amplified numerous issues in American society. Economics, identity politics, gender, and race are the major drivers of our societal malaise.
We do this without increasing the mental anguish, lack of empathy, stress, anger, and vitriol that people are feeling or acting out towards others.
MakeUsWell is working with healthcare companies and private equity firms to launch this product.
GRAS and HOPE have
- Variety of data sources—100+ and growing. Includes structured and unstructured data from the open Internet. And places like Twitter, Reddit, and Nextdoor. We also interviewed 100+ people.
- Built and refined with consumer data in the pandemic world. Not with anachronistic pre 3/15/20, old normal era info.
- Simple (not simplistic) applications, scores, and front-ends.
- Combined with sophisticated statistical engines and algorithms now in use. And have been applied to hundreds of cases in dozens of verticals.
- Not healthcare data or scores—so no HIPAA compliance issues.
- Can be—but no need to be—combined with patient clinical or insurance claims data.
The model development and validation samples used real-life market data. Our analysis showed incremental benefits of using the model vs. the same old, mass market approach to vaccinations.
The objective is to target Americans by their likelihood to take one of the COVID vaccines. We also factor in the probability of different marketing messages to increase Americans' mental malaise. The less likely this event, the higher the score, or the better the segment.
GRAS is an acronym for Geography, Race, Autonomy, and Social.
The United States has approximately:
- 50 states and territories
- 175 Combined Statistical Areas (CSA)
- 317 cities with populations greater than 100K
- 392 Metropolitan Statistical Areas (MSA)
- 3,006 counties
- 41,692 zip codes
Mathematically the permutations and combinations of these geographical variables are very large. (50 10) has an order of magnitude in the billions.
Sometimes we segmented on a state level. In Manhattan we sliced the Upper West Side to below 72nd street vs. above. Mountain View was further sliced by proximity to Google's campus.
Race is a complex, multi-factorial issue in 2021 America. Analyzed data from multi-racial population segments. And calculated metrics related to proportions and indices amongst different races.
Analyzed the top anti-vaccination Twitter voices. Most were selling something—books, get-rich-quick scams, unlicensed medicine. They sold directly or through followers or bots. But mixed in with the anti-vaccination crowd's lies and hidden financial interests were kernels of truth and accurate facts.
The fervently pro-vaccination segments also lied. They often stated things like: "Once you're vaccinated, the immunity from COVID lasts forever, even new strains." Or, “skip your second Pfizer shot, and you'll still be at 85% protection—I don't really understand what that means, but it should be close enough."
This was a tricky optimization dimension. We wanted to rank people based on their ability to think, and exercise their agency while making informed choices.
An overwhelming majority of Americans consume, create, relate, transact, and make decisions on various social media—Instagram, YouTube, Nextdoor, Pinterest etc… Used our augmented analytics to pinpoint areas where the online social behavior was impacting (good and bad) real-life vaccination behavior.
Communication Construct Components = HOPE
The acronym for the framework's second part is HOPE: Hemingway, Orwellian, Paternalism, and Elide Partisanship.
HOPE automates and infuses intelligence in how and what MakeUsWell communicates to the consumers and segments targeted and scored in GRAS. HOPE matches individuals in similar score ranges or segments to customized cadenced communications. HOPE generates copy for chats, emails, SMSs, and web pages.
Simple—not simplistic—is the only way to go. The CDC, state, and local governments communicate with complexity. MakeUsWell simplifies concepts and advice. Simple says easy but does hard.
They started circa March, 15, 2020. Government officials at the federal, state, and local levels, from both parties practiced and refined the art and science of Orwellian communications. They preached propaganda, disseminated disinformation, and denied the truth. This caused the public to lose most or all —depending on the specific segment—their trust in our government.
MakeUsWell inverted this so all our copy, marketing, and communications are not Orwellian. No distortion or doublespeak.
Public health officials and politicians perfected paternalistic pandemic practices. Often they restricted Americans' freedoms, supposedly to protect us. And then scolded us when we challenged government or public health officials.
Our communications are designed to be non-paternalistic. Give the people all the facts and admit the unknowns and the risks.
A lot of Americans believed that the November, 2020 elections would eliminate much of the identity politics and related culture wars. If anything it's accelerated the political fighting.