What is customer data?
Customer data is all the behavioral, psychographic, and demographic information you collect about your customers, such as purchase history, website interactions, stated preferences, and more. This data informs customer profiles that can help you craft personalized experiences that drive loyalty and sales.
Personalized, omnichannel experiences are no longer a nice-to-have. 74% of consumers now expect more personalized interactions from brands, according to Klaviyo’s 2025 future of consumer marketing report.
The benefits of using customer data for B2C brands
Smart brands don’t just collect customer data—they know how to use it to create competitive advantages. Here’s how unified, heterogeneous customer data can help B2C brands stand out:
Smooth customer experiences across multiple touchpoints
Customer data can help you spot and eliminate friction points in your buyer’s journey.
Take your checkout process, for example. Behavioral data might reveal that people most often abandon carts once shipping costs are calculated, after they enter their address. This could be the direct evidence you need to do everything you can to lower shipping costs, or present them earlier in the checkout process. Without this insight, you might never have known why potential sales evaporated at the last minute.
Customer data can also help create consistent omnichannel experiences, whether someone is shopping on mobile, desktop, or in-store. When you can literally see how people bounce from one channel to the next—and how they behave on each—you can start to create integrated experiences that reflect the actual journey your customers are taking, from discovery to post-purchase and loyalty.
More efficient marketing spend and higher ROI
Customer data can help you identify your most valuable segments, so you can direct your resources where they’ll generate the greatest returns. For example, you may want to cross-reference high customer lifetime value (CLV) with an X number of website visits in one month to create a segment of highly engaged VIP customers—then create a lookalike audience to target with ads on Meta platforms.
This precision can boost conversion rates while lowering acquisition costs. Plus, retention marketing to existing customers typically costs far less than acquiring new ones—while also driving substantial revenue growth.
More useful product development and inventory management insights
Beyond marketing, customer data can inform what you sell and how you manage your inventory.
For instance, purchase patterns and customer feedback can reveal opportunities to develop new products or make improvements to existing ones. Historical buying trends help forecast demand more accurately, preventing both costly stockouts and excess inventory.
Customer data can also help you discover natural product pairings for bundles that increase average order value (AOV) while genuinely serving customer needs.
Types of customer data
Not all customer data is created equal. As privacy laws evolve and consumer expectations shift, understanding the distinctions between data types is crucial for building effective marketing strategies and consumer trust.
Zero-party data: the gold standard
Zero-party data is information customers voluntarily and intentionally share with your brand. This is the gold standard of customer data because it indicates that someone wants you to engage with them.
Examples of zero-party data are email addresses, phone numbers, and preferences shared through surveys, quizzes, or profile settings. You can collect this data through preference centers, website forms, onboarding flows, interactive quizzes, and feedback surveys.
Zero-party data is valuable because it creates trust, improves accuracy, and respects privacy since customers are knowingly providing it.
First-party data: your owned information asset
First-party data is information your brand gleans directly through customer interactions with your owned channels. This includes details like:
- Website behavior
- Purchase history
- Email engagement
- Customer service interactions
You can collect first-party data through website tracking, order data, email analytics, and customer service platforms. Unlike second- and third-party data, first-party data belongs exclusively to your company, which means it’s a reliable source of information about how your customers experience your brand.
Second-party data: partnership insights
Second-party data is another company’s first-party data that you can access through partnerships. Think of second-party data as borrowing insights from trusted friends.
Examples include data shared through affiliate programs, co-marketing campaigns, or marketplace performance metrics.
Second-party data can expand your reach and potentially enhance existing customer profiles or identify new audience segments.
Third-party data: the declining resource
Third-party data is collected by entities with no direct relationship to your customers—think data brokers, advertising networks, and public records. While traditionally used to expand audiences, third-party data is declining in value due to browser cookie deprecation, privacy regulations, and declining consumer trust.
Smart brands recognize this shift and are pivoting toward strategies centered on zero- and first-party data collection. This transition not only addresses compliance concerns but often results in higher-quality data that drives more effective personalization.
How to collect customer data: focus on gathering zero- and first-party data
Successful data collection balances personalization at scale with customer privacy. Here’s how you can start to build rich customer profiles through transparent, consent-based approaches.
Connect your CRM with your storefront and mobile app
When your CRM integrates with your storefront, mobile app, and marketing automation tools, you’re in a better position to act on browsing and purchasing data because you have a complete behavioral view of the customer.
For example, someone may have booked an appointment with a spa through a mobile app, but they’ve indicated they prefer to be contacted about updates through SMS. A couple months later, they get a promotional email with a personalized discount for the exact facial they received before.
An integrated system tracks this journey—and makes it possible to act on it. When your customer data can interact with the other platforms in your tech stack, you’re at the start line of a race to differentiate your product with personalized customer experiences at scale.
Use interactive tools that collect zero-party data
Static forms capture basic information, but interactive experiences motivate customers to share lifestyle information and preferences. Some examples include:
- Quizzes: Zero in on customer preferences with a quiz that promises personalization in exchange for psychographic data. For example, a skincare brand might develop a quiz that asks about skin type and nighttime routine—then recommend personalized product regimens based on responses.
- Conversational SMS: Two-way conversational SMS is a great way to collect zero-party data through natural conversation or keywords. For example, someone may text a hotel brand to upgrade their room or indicate view preference. The next time that same person books, the hotel can use data from the previous interaction to suggest a room that reflects these preferences.
- Advanced web forms: For example, customizable web forms can make SMS double opt-in easy by generating a one-time code that auto-fills. Pre-filled forms that automatically apply discounts can personalize and improve the checkout experience.
Don’t forget customer service data
The customer relationship doesn’t end at checkout, and neither should data collection. Here are a few post-purchase touchpoints that can collect zero- and first-party data:
- Post-purchase surveys: Use this tool to gather satisfaction metrics and preference details while the purchase experience is still fresh. Questions like, “Would you recommend this product to a friend?” can be a fast indicator of satisfaction and help determine a follow-up plan for retention.
- Loyalty programs: Programs structured to reward profile completion—”Earn 500 points for completing your style preferences”—motivate customers to share additional details in exchange for something tangible.
- Customer service conversations: When customers reach out with questions or issues, they often reveal preferences, pain points, and future purchase intentions. Capturing these insights requires a system that logs conversation content and connects it to customer profiles.
3 tips for putting customer data into action
1. Automate personalized customer journeys
Imagine 5,000 customers each receiving a message that feels crafted just for them—not because you manually created 5,000 unique messages, but because your CRM transformed the data into scalable, personalized flows.
For example, let’s say someone visits your high-end blender product page 3 times in one month without purchasing. This might trigger an automated sequence that delivers product comparisons, customer reviews, and a limited-time offer at key moments.
These messages flow across channels based on engagement—perhaps starting with a browse abandonment email, continuing with an SMS if the email goes unopened, and leading to a retargeting ad showing the exact product they considered.
This connected approach to personalization at scale only works when you have unified customer profiles.
2. Develop real-time response automations
Customer intent has an extremely short half-life—the window between “I’m interested” and “I’ve moved on” might be minutes, not days.
This fleeting opportunity means audience segments must update instantly when behavior changes. When a customer moves from browsing to purchasing, your CRM should immediately recognize this change so that messaging remains relevant. These critical moments often determine conversion success—miss them, and you’re likely catching customers after they’ve filled the need elsewhere.
A B2C CRM like Klaviyo processes behavioral data instantly and makes it easy to trigger messages that reflect change without manual intervention.
3. Create a feedback loop for continuous improvement
Rather than guessing whether product reviews or user-generated content drives more conversions, use A/B testing to get concrete answers.
B2C brands can test variables like subject lines, send times, content types, call-to-action placements, form pop-up timing, etc., isolating one element at a time to determine which factors truly influence behavior.
The most sophisticated brands A/B test marketing assets across the entire customer journey to clarify which data-driven initiatives deliver the greatest ROI. This continuous measurement process creates a cycle: better data leads to better targeting, which produces better results, which generates more insightful data for future campaigns.
7 essential features for actionable customer data profiles
1. Data retention capabilities
Choose a platform that stores customer data indefinitely. That way, you can see every shopper’s full history and identify seasonal patterns over long periods of time, like who purchases holiday decorations every December.
2. Predictive analytics functionality
AI-powered predictions, like expected date of next order and customer lifetime value (CLV) forecasts, can help you proactively engage customers before they lapse. When you can send targeted offers just before a customer’s predicted next purchase date, you’re speeding up time to repeat purchase and increasing retention rates.
3. Granular product data
Product variant details matter a lot when you want to be precise with your product recommendations. Coffee isn’t just coffee—it’s medium roast, whole bean, Ethiopian origin, and purchased in 12-ounce bags. These specifics make future recommendations more relevant.
4. Flexible date ranges
Rather than preset time windows, flexible date selection lets you analyze data based on your actual business needs. You may want to compare this year’s spring sale with last year’s, but you may also want to compare your own promotion periods that deviate from seasonal norms.
5. Event-based segmentation
When you can build audience segments based on specific actions within defined periods of time, you’re creating more targeting opportunities for your brand. This event-based approach helps you identify and reach customers based on their actual behaviors.
For example, you may want to target customers who purchased a specific item within the last 3 days with a cross-sell automation you know has boosted sales with another segment.
6. Comprehensive acquisition tracking
Platforms that track acquisition details can help you identify, for example, which Facebook ad variation brought in your highest-value customers. When you understand exactly which channels and campaigns drove each customer to purchase, that means you’re really using your acquisition data to optimize marketing spend.
7. Unified customer views
When you can see all your customer data—from marketing to customer service—all in one place, that means every person on your team is operating with an optimal amount of information to improve the customer experience.
When your customer support team can see someone’s skincare quiz results, for example, they’re much better equipped to offer personalized service that addresses real pain points. This is what it takes to differentiate a brand in a competitive market—above and beyond service that makes customers feel seen.
Make customer data your competitive advantage
Remember that behind every customer profile sits a real person with unique preferences and needs. The brands that thrive aren’t just collecting more data—they’re developing a deeper understanding of their customers as individuals.
When you deliver personalized experiences that feel almost intuitive, customers notice. These meaningful interactions build loyalty, increase purchase frequency, and ultimately drive higher CLV.
Centralizing your customer data in Klaviyo, the only CRM built for B2C, brings these insights together in one place, creating true personalization at scale through comprehensive profiles that update in real-time.
Start putting your customer data to work and transform transactional relationships into lasting connections that drive sustainable growth.