AI in Healthcare Marketing: How to Balance Personalization and Privacy

Imagine receiving an email with a highly tailored, proactive care plan that is based on your own unique biological makeup and health trajectory. Or a mobile alert prompting you to log into your patient account profile to see the most precise treatment options that consider your lifestyle factors, genetics and medical history. Suggestions created just for you, with medications that have the least amount of side effects or drug interactions.

AI has the potential to be revolutionary in healthcare marketing. So why are healthcare organizations hesitant to adopt this new era of technology? For one, AI needs to use highly sensitive patient data in order for its systems to operate effectively. This introduces complexity in data privacy and compliance. While AI solutions are evolving to remain compliant, the regulatory landscape is complex and can trigger significant adjustments to workflows and processes. Change management takes time. 

While marketing in a world of HIPAA, GDPR, and other privacy regulations, healthcare companies must be vigilant with their AI approach. Put on your consumer hat for a second. How would you want private data about your health being used? The biggest challenge healthcare organizations face with AI is using new technologies to deliver personalized, proactive and thoughtful experiences without compromising the privacy of healthcare professionals and patients. 

In healthcare, even inferred data can trigger ethical and legal concerns as it is sensitive health information. Targeting a patient with relevant resources for diagnosis support can be in violation of privacy laws. Patients and providers expect (and deserve) confidentiality and discretion. If a patient or healthcare provider explicitly opts in to share their data for marketing purposes, that’s all well and good.

However, if a company does not have the means to capture this data, or if the subscriber has not opted in, there are still ways to thoughtfully market to these users while protecting their privacy. 

You can do this by following a few simple Dos and Don’ts for healthcare organizations: 

3 best practices for AI in healthcare marketing

DON’T: adopt an over-targeting approach that feels invasive to consumers or providers

DO: include a preference center for all marketing opt-in instances that allows the subscriber to dictate how much of their data they are comfortable with you using for marketing to them. Only use necessary data fields for campaigns. 

DON’T: misuse or over-collect personal health data

DO: live the proverb “less is more”. Only capture what is absolutely vital for targeting and be mindful of how you use it later. Put yourself in the mindset of the consumer. When building personas or segments, use de-identified or aggregated data. Content-driven outreach still performs well and should be used in place of behavioral targeting.

DON’T: use inferred data (i.e. AI suggesting health conditions from behavior)

DO: only action off of data that has been explicitly provided to you for marketing purposes. Follow transparent data practices: explain what data is used and why. Healthcare is personal. Treat this relationship as you would any relationship. Trust comes first and there’s always a give and take. Offer a value-add in exchange for data. 

How Salesforce can help

Salesforce offers AI capabilities for personalization in healthcare marketing, including:

1. Health Cloud: Create a unified patient view with data from billing systems, patient portals and EHRs (Electronic Health Records). Salesforce analyzes this comprehensive dataset to provide more accurate insights. Marketers can then create highly relevant, personalized campaigns based on those insights.  
2. Data Cloud: Use predictive analytics and segmentation to create targeted communications with healthcare providers based on their specialty or prescription behavior. 
3. Marketing Cloud Engagement has efficient campaign automation and engagement scoring, which aid in personalized content for subscribers based on their interests and demographics. Effective testing tools like Send Time Optimization and Engagement Frequency cater to the subscribers’ preferred cadence and time to receive a marketing email. 
4. Marketing Cloud Intelligence is a centralized platform to integrate, analyze and visualize data from various marketing channels and track ROI.
5. Salesforce Shield is a set of security tools specifically designed for industries with strict compliance requirements. Shield offers a Platform Encryption feature which encrypts sensitive data within Salesforce, a Field Audit Trail, which ensures data integrity by tracking changes to data over time and Event Monitoring which helps detect suspicious activities such as unauthorized logins or bulk data exports, in real time. 
6. Access Controls and Permissions: Salesforce user permissions, profiles and roles have the option to set access with a “least privilege” approach. This ensures that employees can only access the data needed to perform their jobs. 
7. Data Masking: Data masking can be used in Salesforce development and testing environments to obscure sensitive PHI (Protected Health Information). This allows teams to work with realistic data without compromising patient privacy. 

Note: this is not a comprehensive list. For the most relevant solutions for your business, contact your Salesforce Account Manager.

Following these simple steps can not only ensure your brand’s compliance with privacy regulations but also strengthen brand trust and loyalty with healthcare providers and consumers. Consumers are not only receptive to this type of targeting – they have come to expect it.

It’s important to upskill your internal marketing teams with ongoing compliance training. Invest in privacy practices alongside your AI tools to secure a more valuable, formidable personalization experience for your entire subscriber base. After all, we can’t let retail have all the fun!