Mastering data compliance: An ultimate guide to consent, privacy, and best practices

We live in an era of data – from minor transactions to the biggest behavioral groundswells. As data becomes more central to marketing and strategy, the issues of data compliance, consent, and intent can become roadblocks. While a swath of companies use customer data management to deliver exceptional experiences, many are still figuring out where to start.

What is data compliance?

Data compliance is an all-encompassing term that refers to a set of practices and industry standards designed to ensure data security and protection, preventing theft, misuse, or loss. This applies to both customer and company data. Data compliance also involves adhering to regulations such as the GDPR (General Data Protection Regulation) and CPRA (California Privacy Rights Act), which govern how data is collected, stored, and managed within organizations.

What is CPRA? California Privacy Rights Act: Basics and Overview

As CPRA and the privacy-first web continue to gain traction, organizations need to adapt. Customers demand transparency about the collection and use of their personal information. Planning now saves you fines and headaches in the future.

So, how do you make sense of customer data?

It can feel that data is infinite. A customer data management plan with a customer data platform can create order and access in real-time.

Customer data solutions can help you turn your data into valuable insights that drive ROI. But to leverage them effectively, you need to understand where you are now. Let’s dig into the finer points of data compliance so that you’re more than ready for what lies ahead.

We’ll start with the importance of data maturity and move into the language around data that impacts compliance.

Determining your customer data maturity

Data insights deepen over time, which is the concept of customer data maturity. When a company integrates data into its process, allowing it to inform customer-facing actions and longer-term planning within the organization, it can then identify opportunities through predictive analysis.

Assessing your data— collection, interpretation, and use —helps to inform what changes to make to your data strategy. 

Start with these questions:

1. Where are your customer data management efforts now?
2. What data are you collecting?
3. For your customers, what is the experience you are delivering?
4. Does your path have a clear destination?
5. Are there specific things or data you need to get there?
6. Can you identify the actions required to achieve your goals?

A journey of 1,000 miles: Measuring your customer data maturity milestones

When you apply a data framework for your organization, it helps you understand how mature your current data strategy is. Most models for measuring data maturity follow four or five distinct levels, giving you a clear sense of where you stand and what steps you need to take to improve.

For this journey, we’ll be looking at a simple 5-level framework that helps you measure how far you’ve come in managing customer data. This model assumes you’ve already started collecting some customer data and guides you toward the ultimate goal— creating a seamless, unified customer experience.

Let’s get started:

• Level 1: Ability to identify and understand your customers’ digital identities
• Level 2: Ability to manage customers’ data privacy and consent preferences
• Level 3: All customer data – offline and online, front-end and back-end, structured and unstructured – is consolidated into unified customer profiles.
• Level 4: Ability to differentiate through data-driven insights
• Level 5: Achievement unlocked: Unified, omnichannel personalization

Those are our guardrails. Most companies will fall somewhere in the middle.

Assuming your goal is to progress to a higher level of maturity, different customer data solutions can help.

Another resource is understanding the language around data compliance, particularly in terms of rules. The more you’re able to strengthen your view of the customer through identity resolution and share insight across your enterprise, the more your data management strategy will illuminate the tactics for data compliance that delivers enduring cx benefits.

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Data compliance: Breaking down legal terms marketers must know

• Digital Identity: The entirety of personal data online that can be followed back to a person— from images and comments on social media to browsing and search history, to online banking and activities on gaming, streaming, or shopping sites.
• Personally Identifiable Information (PII): Representative of any sensitive information connected to an individual that can identify or pinpoint their location.
• Personally Protected Information (PPI): Social security number, home address, date of birth, home phone number.
• Anonymization: The process of removing or obscuring PPI or PII from data to create data sets that inform but do not reveal the identities of the people represented.
• Pseudonymization: This data processing creates a separation between the data subject and the personal data. A person cannot be identified without additional data that is stored separately. GDPR speaks directly to this type of data management.
• Consent: An independently offered indication of a person’s interest through a statement or affirmative action, qualifies as consent around personal data so long as there is an option to withdraw consent.
• Explicit consent: According to the GDPR, this consent requires a written statement or a digital note, the key being that it must be able to be verified, something that would be difficult to do with an oral form of consent.
• Unambiguous consent: This involves knowingly checking a box or agreeing to technical terms.
• Legitimate interest: An unspoken agreement (though enforced by laws like GDPR) that allows a user to trust that companies will use the data they collect for things of use or importance to the individual. It depends on purpose, necessity, and balance: Is there a legitimate interest behind the processing? Is the processing necessary for that purpose? Is the legitimate interest overridden by the individual’s interests, rights, or freedoms?
• First-party data: Data collected by companies through their site.
• Second-party data: Another organization’s first party data then shared or sold to another entity for whom it is second-party data.
• Third-party data: An organization or data aggregator collects, packages, and sells data to other entities.
• Walled gardens: If data collection and storage were like the fable of the three little pigs, a walled garden would be the house built of bricks. It protects and contains everything within it, meaning the data in a walled garden isn’t intended for sharing.
• Dark patterns: Precisely what it sounds like, are tactics or practices intended to trick people on the internet into purchasing, committing to, or signing up for things without clearly understanding that they are doing it.

The privacy-first web is coming, and with it, an inability to be tricky or disingenuous with data. The best plan is to create a culture and framework built around the integrity of relationships we have with customers.

Data compliance across various industries

In industries like healthcare and finance, adhering to data regulations can be challenging due to the sensitive nature of the data handled. Compliance requirements are rigorous and can differ significantly across industry sectors, necessitating a tailored approach to data security and protection. Here’s a look at how data compliance impacts a few key industries:

Healthcare:

• Regulations: Healthcare providers have to follow the Health Insurance Portability and Accountability Act (HIPAA) to protect sensitive patient data like medical records. That means strict rules on access, encryption, and consent.
• Best practices: Strong data encryption, regular risk assessments, and training staff to ensure HIPAA compliance are must-haves. When using cloud services, healthcare organizations need to make sure they’re HIPAA-compliant too.

Finance:

• Regulations: Financial institutions must comply with regulations like Gramm-Leach-Bliley Act (GLBA), Sarbanes-Oxley (SOX), and PCI-DSS (for payment data), all aimed at securing financial transactions and protecting customer data.
• Best practices: Secure your internal controls, conduct audits, and use multi-factor authentication (MFA) to stay ahead of data breaches.

Retail:

• Regulations: Retailers need to comply with PCI-DSS, which protects customer payment data. Any business processing credit cards must meet these standards.
• Best practices: Secure POS systems, encrypt payment data, and regularly check for vulnerabilities in your payment systems.

Education:

• Regulations: Schools and universities must follow Family Educational Rights and Privacy Act (FERPA), which safeguards student records and personal data.
• Best practices: Implement strong data access controls and cloud storage solutions that protect student information, and ensure transparency in how student data is used.

Government:

• Regulations: Government agencies have to follow the Federal Information Security Management Act (FISMA), which outlines how federal agencies should secure their information systems.
• Best practices: Regular security assessments, continuous monitoring, and strong encryption are essential to protect sensitive government data.

Best practices across all industries:

Generally speaking across all industries, there are a few fundamental or universal strategies that can help keep data safe and compliant:

• Build a compliance framework: Develop clear, industry-specific guidelines that align with your regulatory requirements.
• Routine audits: Regular checks can catch vulnerabilities before they become real problems.
• Employee training: Make sure your teams are up to speed on data compliance and security best practices.

How to effectively use customer data along the customer journey

Once you’ve identified your starting point, the next step on your quest to make the most of customer data and unlock its CX superpowers is to stock your toolbox. Which solutions you choose to invest in will depend on where you fall on that maturity model. As you create a data foundation, you’ll be able to benefit from real-time data including a single customer view. Over time, you’ll be able to track your progress and continue to build your data maturity as you integrate a customer data management plan.

Level 1: Ability to identify and understand your customers’ digital identities

You may need help reconciling your customers’ digital identities. It isn’t enough to collect data, you need to have a plan and a process, a recipe if you will, that turns all those data ingredients into something delicious. Identity and access management solutions can help. Identity resolution unlocks the ability to personalize your customers’ experiences by helping you get to know who they are.

Level 2: Ability to manage customers’ data privacy and consent preferences

Once you are able to recognize your customers and begin personalizing their interactions with your brand, they may be willing to share more of their personal information. It’s critical that you’re able to manage their privacy preferences easily and securely. It’s the first step to building a foundation of trust that drives lasting customer relationships. And breaking that trust will cost you dearly.

If your focus is simply on mastering Level 2, you can use a bespoke consent and preference management solution. Solutions like these help you clearly communicate what data you’re collecting and capture consent from your customers. They also make it easier for customers to update and manage their privacy and consent preferences, a non-negotiable for consumers today. Ultimately, a customer data management plan is an insurance policy for compliance and customer satisfaction.

Level 3: All customer data – offline and online, front-end and back-end, structured and unstructured – is consolidated into unified customer profiles

The next step on the ladder is data unification. That means that all your customer data – from across multiple channels and disparate systems, are brought together into the data foundation of a single database, and used to create dynamic customer profiles.

This is a huge step towards unlocking deep personalization, which has long been a roadblock for many companies. Especially enterprises that manage multiple business units across various regions and departments.

To achieve this, you’ll want to use a customer data platform (CDP).

What is CDP? | Customer Data Platform definition, benefits

Businesses have lots of data - but what do they do with it? Discover how a CDP helps organizations reach customers, identify intent, and personalize messaging to exceed KPIs and bottom line projections.

CDPs are designed to collect, clean, and organize your customer data from your key sources, and store it in a single place which then feeds back into those source systems. (That includes the identity and consent data mentioned earlier.) It’s not a data lake or stagnant repository, though.

When you unify your data, it becomes more actionable and insightful. Your customer profiles become richer – pulling in information from in-store transactions, online service requests, and everything in between.

Customer data management opens doors to opportunities like:

• Personalized communications when product warranties are expiring, up-selling warranty extensions (combining customer purchase and product data which may otherwise be separate)
• Targeted birthday emails that include personalized offers based on past engagements (combining personal, online and offline data)

These types of experiences are becoming more and more expected from consumers. And a CDP helps simplify their execution.

Level 4: Ability to tap into rich customer insights

The penultimate rung on our ladder is about insights. Once your data is centralized and unified in a single place (like a customer data platform), you want to start tapping into your analytics. Using AI and machine learning tools, you can uncover trends and patterns about your customers, products, campaigns, and more.

This is the heart of what it means to demystify customer data. It’s turning large swaths of data points into valuable insights and information.

A CDP can help here, too. By collecting data from across the entire customer journey into dynamic customer profiles (and updating those profiles automatically), you get deeper insights into each customer on an individual level.

We have the technology: Benefit from customer data with a CDP

If you’re waiting for the right moment to embark on your customer data journey, this is it. No matter where you fall on the ladder, there’s no time like the present to begin your evolution.

A CDP is a useful tool in bringing your digital transformation vision to life. It makes sense of your customer data and uncovers deep, valuable insights. Businesses of every size and at every stage of maturity can benefit from that.

Whether you’re ready to go all-in and transform your entire customer data experience, or launch a pilot program with a single channel or territory. We all need to start somewhere. So why not start where you are?