A New Measurement Model for Digital Health Behavior Change Campaigns

Background:  While traditional campaign evaluation methods are necessary for evidence of behavior change, gathering insights at the rapid pace required for digital channels poses a challenge.  This abstract submits a measurement model that has been used in multiple state and federal digital health marketing campaigns. The model accounts for the need to continuously optimize digital campaigns, and outlines metrics that can be used indicators of overall campaign performance.

Program background:  As is often the case in digital health marketing campaigns, access to published evaluations of previous campaigns, such as those in tobacco control, are severely limited.  Without ready access to pre- and post-digital campaign evaluation data, a model was developed to ladder campaign performance metrics back to established behavior change models and indicate progress. The model is based on two campaign objectives, awareness and engagement. These objectives are then broken into actionable goals that bridge between marketing objectives and a behavior change model. The result is a rapid performance evaluation that can be reviewed on a monthly and quarterly basis to assess campaign status and optimizations.

Evaluation Methods and Results: 

Campaign activities are broken into 3 separate elements:

• Message Awareness - A measurement of the behavior change message delivery based on different channels and media formats. This measure is stated in terms of impressions, video impressions, or for more traditional channels, GRPs. These metrics can be evaluated based on a Reach & Frequency goal within a specific community or audience.
• Passive Engagement - An engagement wherein an audience is mostly observing content, interacting only occasionally. In relation to behavior change theory, the individual is seen as beginning to consider and perceive a behavior differently. Passive engagement examples include Liking and Favoriting campaign content, which may or may not encourage dialogue. Examples of metrics used to evaluate goals are click-through-rate, video completion rate, website visits, likes, clicks, etc.
• Active Engagement - An engagement wherein an audience is participating with campaign content and posts from other users. In relation to behavior change theory, the individual is seen as internalizing the behavior change message given the longer, more substantive interaction or experience. Active engagement examples include sharing, Re-Tweeting, and commenting on campaign content. Examples of metrics used to evaluate goals are shares of website content or pages, completion of an online event experience, shares, retweets, etc.

Conclusions:  Aligning a behavior change campaign to an awareness and engagement measurement model allows for early and more frequent access to data, with opportunities to optimize digital campaigns. Optimizing digital campaigns at frequent intervals, when metrics are linked to actual behavior change goals and theory, can increase the likelihood a campaign affects its target behavior.

Implications for research and/or practice:  This measurement model demonstrates an option to measure campaign success on a more frequent and iterative basis. This allows for more frequent and rapid campaign optimizations and the ability to deliver performance reports relating back to behavior change without having to rely solely on longer term, traditional evaluation studies.