Setting up segments
Using preferred channels
Being proactive
Adjusting to lifecycle stage
Leveraging details

1. Set up dynamic segments that update in real time

A customer profile should look like a real-time record of that customer’s interactions with your brand. The richer the profile, the more it tells you about someone’s buying intent, personal preferences, online behavior, and demographics.

To reach this goal, every unified customer profile needs to integrate data from your entire tech stack into a single view that’s also integrated with your omnichannel marketing automation platform. 

The result of this consolidation is the ability to set up and reach dynamic segments such as new subscribers, high spenders, discount shoppers, product category shoppers, customers likely to buy next, and more. 

Dynamic segmentation

Dynamic segments automatically update in real time as customers interact with your brand. You define rules based on attributes and behaviors, and the segments populate or contract as new data is pulled in.

When someone makes a purchase, clicks on a text message, or shows interest in a product, their profile moves in or out of segments based on your predetermined criteria. These real-time adjustments allow for messages that always reflect the needs, preferences, and status of each customer.

For example: 

• A customer who leaves a neutral or negative review automatically enters a churn risk segment for special attention.
• Customers who reach a spending milestone automatically enters a VIP segment with exclusive offers.
• A customer who starts a check-out at least once in the last 5 days but does not complete their purchase automatically enters a high-intent segment for personalized campaigns based on their product interests.

When a customer profile contains a high level of detail, you can deliver hyper-personalized messages to each customer instead of blasting your entire list with messages that are relevant only for a select few. 

Beauty brand esmi Skin Minerals, for example, uses interactive skin quizzes to send personalized skincare education and other messages tailored to the lifecycle of a customer and their level of engagement. As customers produce more data, messaging evolves from simple how-to guides for new customers to time-sensitive SMS reordering reminders and discount codes for seasoned shoppers.

Customer persona segments

Customer persona segments combine behavioral data—such as website visits, message engagement, purchase frequency, and average order value (AOV)—with stated preferences and lifecycle stage to create customer segments that are more useful than ones that imagine shoppers based on demographic data alone.

Customer persona segments may include:

• Millennial high spenders on mobile: millennial-aged customers with high average order value (AOV) who most often purchase on mobile
• Review-driven brand enthusiasts: customers who purchase frequently and refer often, who have also left a certain number of positive reviews
• Category-specific potential customers: subscribers who haven’t yet made a purchase but who frequently browse a certain product category
• Lapsed customers who have shopped in-store: customers who made in-store purchases in the past but haven’t shopped recently

AI segmentation 

AI segmentation is a retrieval method that makes it easy to pull complex segments with a plain language prompt. Once you describe the type of customers you want to reach, AI will automatically generate the segment for you. This is how you can get more specific with your segments and send high-value messages with less manual work.

When using AI to generate segments, make sure to:

• Include consent parameters in the prompt.
• Match the specificity of the segment to an actionable revenue goal.
• Double-check the AI outputs before sending your messages.

Blanket brand Saranoni uses AI to create segments for customers in specific locations, and their team saves 10–30 minutes per segment.

2. Reach customers on the channels they prefer

Customer profile marketing is as much about where your customers engage as it is about how they engage. 

The customer journey is increasingly non-linear, with 77% of omnichannel consumers using 3–4 channels when shopping for non-essential products or services, according to Klaviyo’s online shopping report. 

This is why it’s increasingly important to understand where your customers prefer to receive messages from your brand. Customer profile marketing means storing data about where people browse, interact with messages, and ultimately complete a sale. The emerging result of this data is called channel affinity.

Channel affinity is an AI-powered dynamic view of engagement and shopping behavior. As behaviors shift—for example, a customer stops engaging via email and starts engaging with push notifications after downloading your mobile app—their profile updates automatically. So should your message strategy.

With channel affinity data, you can build campaign segments and adjust flow logic based on each profile’s unique engagement patterns, which empowers you to:

• Reach out to customers on their preferred channel first to increase engagement rates.
• Adapt outreach as the customer journey shifts, reducing message fatigue.
• Create better mobile shopping journeys that reflect how certain segments click.

Women’s intimates brand Thirdlove, for example, uses channel affinity in their abandoned cart flow to ensure multi-channel subscribers get the message where they’re most likely to engage—contributing to substantial growth in revenue from flows.

“We want our customers to hear from us when they want to hear from us, and when they are ready to purchase,” says Leanne Chan, senior director of growth and retention at Thirdlove. “Now we can do that, taking the signals across all of our different platforms and bringing them together.”

3. Proactively boost repeat purchases with predictive analytics

Detailed customer profiles aren’t just a snapshot of past interactions. They’re also a window into what each customer is likely to do next. 

By capturing the right customer profile data, you can use predictive analytics that anticipate behavior, trigger timely campaigns, and deliver personalized offers. 

Channel affinity is one example of that, but there are plenty of others you can use in campaign segments or as triggers for automated flows. For example:

• Predicted lifetime value (LTV): Predicted LTV estimates the total revenue a customer may generate over their relationship with your brand. It can help you identify high-value customers and tailor loyalty perks or exclusive offers to their spending habits.
• Churn risk: Predicted churn risk tells you which customers are likeliest to lapse, so you can proactively re-engage them through personalized win-back or sunset flows. 
• Predicted next order date: Predicted next order date forecasts when a customer is likely to purchase again, so you can send them offers they’re ready to act on.

Fresh seafood company Svenfish uses predictive analytics to reward high-value customers whose forecasted CLV is more than $200. As a result, they’ve reduced their win-back segment and improved margins. 

The brand also segments customers based on purchase history, recent engagement, or interest in the day’s fresh catch. This means they can send targeted campaigns to only those customers most likely to engage with a product, reducing wasted sends and making sure messaging feels personalized. 

4. Adjust messaging to customer lifecycle stage

Klaviyo’s 2025 future of consumer marketing report found that 74% of consumers expect brands to personalize their experiences in 2025. But today, personalization is about moving beyond a first name shout-out and engaging with contextual lifecycle targeting.  

By centralizing customer profile data like purchase history, browsing behavior, engagement, and predicted analytics, you can accurately deduce each customer’s current buying intent. Here are some tips for targeting by lifecycle stage:

• Share relevant reviews with shoppers in the consideration stage. If a subscriber has browsed a product multiple times, proactively send them a review of that product on the channel they’re most likely to engage on. Home fragrance brand Happy Wax, for example, uses AI to automatically insert the most relevant customer reviews in their abandoned cart emails.
• Address customer pain points during the conversion phase. When customers are close to making a decision to purchase, consider sending educational content that’s also considerate of their spending threshold. Women’s apparel brand Cara Cara, for example, uses RFM segmentation to send educational content to churn-adjacent groups, while engaged customers receive text messages or quick product updates.
• Modify post-purchase messages based on channel affinity data. For example, someone whose channel affinity shows they prefer email probably wants their order confirmations via email, even if the majority of your customers prefer receiving order confirmations via text. 

Across the customer lifecycle, beauty brand Tatti Lashes uses text messaging to engage customers at key moments. They’ve incorporated text messages into their existing flows, and they apply subscriber preferences and behavior-based splits to determine what each customer receives.

Customers also receive a text on their birthday with a personal message and an exclusive offer code. And during Black Friday, lash fans who’ve subscribed to SMS receive a text message giving them early access to the best deals—a major incentive from a brand that doesn’t typically offer discounts.

5. Get even more personal with custom profile properties

When you’re collecting a lot of customer profile data, it creates an exciting opportunity to leverage data that’s unique to your business. 

Customer profile properties like the ones we’ve covered so far are important no matter your industry or vertical: channel affinity, predicted LTV and churn risk, support tickets opened and resolved, AOV, reviews submitted, loyalty points, and more.

But custom profile properties empower you to collect virtually any type of information you want about a contact, then use that information to tailor your content, create segments, or filter your flows. They can mean more effective targeting—and more effective targeting can translate to higher revenue and lower customer acquisition costs.

Dental brand Smile Brilliant, for example, pulls over 150 custom profile properties into their B2C CRM, many of them via forms. It’s valuable data they use to hyper-personalize their marketing for each individual subscriber.

Smile Brilliant’s dentist recommendation flows, for example, let patients know when their dentist has recommended products for them. The brand sets the dentist name, practice name, product names, and more in each message with personalization tags based on each subscriber’s custom profile properties.

Operationalize customer profile data with a B2C CRM 

Customer profile marketing isn’t just about collecting data. It’s about using that data to create meaningful, personalized interactions that drive revenue. 

With integrated profile data, predictive insights, and dynamic segmentation, you can anticipate customer needs, reach them on the channels they engage with most, and deliver messages tailored to their journey.Turn your customer profiles into opportunities to create meaningful, personalized interactions at every touchpoint. With Klaviyo B2C CRM, your messages move beyond one-size-fits-all. They’re targeted, timely, and built for impact.aviyo is the only B2C CRM, designed to deliver personalized cross-channel journeys that scale.