Civis Analytics Launches Toolkit for a Data-Driven COVID Vaccine Campaign

Civis Analytics, a data science firm innovating at the intersection of public good and scientific best practices, today announced the launch of its COVID Vaccine Campaign Toolkit. This resource hub includes key information for organizations looking to use data to inform persuasive and equitable COVID vaccination outreach.

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The toolkit provides guidance on each aspect of an outreach campaign that requires a specific, tailored approach. These include:

1. Messaging and messenger: Results from scientific experiments to guide messaging and spokespeople, so the most persuasive language is used for each audience. This includes new research on employer-specific messaging, conducted in partnership with the U.S. Chamber of Commerce Foundation. Crystal Son, MPH, Director of Healthcare Analytics at Civis Analytics, also shares examples of counterintuitive findings, tangible advice for any vaccine campaign team, and comparisons to Civis research on other vaccine messaging.

2. Resource allocation: An interactive vaccine hesitancy map that visualizes which U.S. counties are most likely to need additional intervention to drive up vaccination rates. This map can guide groups that need to determine where to focus education or outreach efforts.

3. Process: Leveraging best practices from recent 2020 Census outreach campaigns, Civis outlines a five-step process organizations can follow to ensure their vaccine campaign is data-driven and set up for success.

“Vaccine uptake is absolutely critical to herd immunity — which is what we all need to recover from the pandemic,” said Son. “Too often, we assume that a one-size-fits-all approach to public health campaigns can work. We continue to see that the language and messengers that work for one group can backfire with another — so we really need to eliminate our own biases and rely on the data to guide our campaigns. For many of us, this is the most important campaign of our lifetime, and we need to do this right.”

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