Leading Pharmaceutical Manufacturer
Transforming marketing with customer insights and leveraging machine learning to classify marketing images.
Credera and a leading pharmaceutical manufacturer designed and implemented a data science workbench to enable personalized marketing through actionable customer behavior insights and implemented an image recognition model to identify key characteristics in marketing images.
At a Glance
A leading global pharmaceutical manufacturer wanted to improve ad performance through advanced analytics, data science, and machine learning to identify the concealed links between campaign performance, ad performance, placement performance, and their associated correlations. The manufacturer engaged Credera to develop the data enablement, enrichment, and transport structure that powered data science models and insights that led to improved marketing effectiveness and reduced content cost.
Shifting strategy requires new processes and technologies.
The manufacturer is shifting their marketing focus from the primary care provider (PCP) to consumers and wanted to better understand the individual while optimizing the marketing budget.
Historically, marketing content was sometimes not labeled or labeled with key image features in a non-standardized, manual process, resulting in time-consuming and inconsistent content labeling. The lack of reliability limited downstream analytics use cases and insights. The manufacturer partnered with Credera to identify key features in marketing images using AWS Rekognition and create dashboards and visualizations with AWS QuickSight.
Automating marketing processes for increased content identification.
Through partnership with the pharmaceutical manufacturer, the Credera team:
Implemented a metadata-driven approach to load various sources into a common data model for scalable analytics on the AWS-powered platform leveraging S3, Lambda, Glue, and Redshift resources.
Designed QuickSight dashboards that contain key performance indicators and insights for the effectiveness of personalized marketing.
Leveraged AWS Rekognition to identify hundreds of key features in marketing ad images to better describe an ad’s content.
The Rekognition API enabled an automated process to upload the identified ad contents into a database for downstream use cases.
Achieving deep marketing insights and increased speed from data analytics.
As a result of the partnership, the pharmaceutical manufacturer:
Developed a deep understanding of consumer behaviors, interest, demographic characteristics, and brand interactions.
Improved customer targeting through more personalized marketing content.
Increased marketing return on investment via near-real-time insights on the effectiveness of consumer marketing tactics.
Created a standardized and objective evaluation of the marketing ads, which could be utilized to inform the future creation of ad content.
Established a connection between ad content and existing consumer data to enable more accurate analytical insights and better decision-making processes.
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