Marketing for the Public Good

What is fully ethical marketing?

Depicts the bidirectional influence of social context (cooperative vs. competitive) and user engagement metrics (hot takes v.s thoughtful consideration). In turn, the users's mindset (more automatic v.s more controlled) is impacted, which feeds into their response to your campaign goals (acting vs. learning)

Fully ethical marketing provides accurate information that is perceived as credible and that helps people to understand your value proposition.

Value propositions reflect both specific features and general human motivations, i.e., for social connection or personal agency.

When an idea is in anyway controversial or strongly associated with an identity – a broader audience can be reached by

(a) appealing to a cross-cutting identity (one that includes “both sides”)

(b) promoting the possibility of social connection with “the other side” by shaping social impressions and personal social goals

This is a central focus of my academic research.

At the same time, one can’t ignore that need for agency – to feel like an individual who is capable of accomplishing valued goals, both specific and general.

To promote a sense of agency:

(a) tailor the complexity of the message to the individual’s motivation and ability

(b) make it clear what understandings are “fit for purpose”

(c) be useful in a concrete way. In other words, make sure your product, person, idea, or behavior offers real value to others.

My scholarly research primarily emphasizes social context. My professional work primarily emphasizes personal agency. Regarding social context, whenever a product could be controversial, I push for branding that builds bridges – e.g., describing a health product as being based in an indigenous herbal tradition but “verified by science.” This strategy could still alienate some people (skeptical scientists, or people skeptical of the scientific method), but it captures the, usually meaningfully large, “middle ground.”

Pushing the envelope, my research is moving towards understanding how to motivate the user to become the “fully ethical marketer.” To be motivated, they must be socially rewarded. To be able, they must be given a user experience that makes it easy to provide accurate and credible information.

One concrete way (under development) is by experimenting with how users can express themselves. Companies are pursuing this in the private sector as well (for example crafting different prompts on a product review cite to elicit higher quality responses). One idea I’ll be implementing in a future academic study is to compare closed ended survey questions that prompt elaboration versus more straightforward rating systems that prompt evaluation. I am also thinking about effective ways of visualizing the results of these closed-ended responses for the public. For example, when deciding whether to visit a restaurant offering a culturally-specific type of cuisine, people may want to see what the overall favorability rating for the restaurant was among those who were new to the cuisine, who had been consuming it for years, or who came from that culture and grew up eating it at home. People may also want to see what flavors struck people as particularly strong, so that they can seek them out or avoid them accordingly. Concrete details, about both the person leaving the review and the food itself, matter.

In the context of customers leaving reviews, social reward could come from knowing that other people share your reaction. However, we can also build in other social rewards, such as badges based on the number of survey questions answered, or, if open-ended responses are incorporated, allowing other users to reward exemplary responses with badges. The badge system efficiently allows people to communicate both concrete information and specific evaluation. It provides the user who left an open-ended review with a sense of social reward and provides the user assigning the badge with a sense of agency.

Of course, user generated content needs to be seen to have a positive impact on behavior. One possibility is to use machine learning to match people with others based not on the views they expressed but the amount of effort they put into expressing them. In this prediction, thoughtful people will give positive feedback on thoughtful posts. There are tradeoffs, of course. Thoughtful people may give less frequent feedback, on average, as they put more time and effort into each act of engagement. However, this engagement will be higher quality and thus often be more meaningful.