Proactive Brand Management in Regulated Industry
A publicly traded, federally regulated industry was historically slow-reactive to public relations events. A reactive approach to brand management significantly increased regulatory, financial, and reputational risk while also increasing the potential for sanctions on core product pricing. To mitigate these risks, the team was tasked with developing a proactive response and brand management model using customer segmentation modeling and social medial tracking.
To understand customers at a more granular level, an unsupervised machine learning model was developed to group individuals into 14 distinct segments based on likely response to certain marketing campaigns and level of passion for key issues (environment, legislation, etc…). To further strengthen the model, the team used ProxyPoll – a proprietary and non-invasive technique leveraging online behavior to understand issue specific customer sentiment.
Leveraging historic brand management events, paired with social media tracking, a public response forecast model was developed to estimate the potential reputational impact of emerging issues (i.e. bad press). By understanding the risk from the moment they started, the client was able to proactively target customer segments with positive marketing campaigns to minimize the negative effectives bad press. This rapid response was further aided by a Customer Insights & Public Perception Dashboard, which provided near real-time data to the executive and marketing teams.
Other Applicable Industries: Finance, Healthcare, Manufacturing, Politics, Government
Skills: Customer Segmentation Modeling, Social Media Tracking, Public Response Forecast Modeling, Proactive Brand Management, ProxyPoll, Survey Design & Analytics, Dashboarding