Klaviyo Shopify Segmentation & Personalization: Practical Guide (2025)

Segmentation and personalization are the easiest ways to make your Klaviyo emails feel “1:1” without sending more campaigns. This guide assumes your integration is already connected. If not, start here: Klaviyo Shopify integration setup. For flow templates, see: Klaviyo Shopify email flows.

Klaviyo

integrates with

Shopify

Marketing 4.6

What Data You Can Segment On

With Shopify connected, you can segment by:

• Purchase behavior (order count, AOV, product/category purchased)
• Engagement (opened/clicked in last X days)
• Intent (viewed product, added to cart) if onsite tracking is enabled

Core Segments to Create (Simple First)

Tip: Keep segments broad until you have enough volume to test (otherwise reporting gets noisy).

More Segment Ideas (Once the Basics Work)

These are common Shopify segments that are easy to build and usually useful:

You do not need 20 segments to start. A handful of well-sized segments beats a long list of tiny segments that never get enough data.

How to Build a Segment (Practical Steps)

When you create a segment in Klaviyo, your goal is to define who and when:

1. Start with one core condition (e.g., “Placed Order at least once”).
2. Add a timeframe when it matters (e.g., last 30/60/90 days).
3. Add one exclusion to keep targeting clean (e.g., exclude recent purchasers from promos).
4. Check segment size before you ship a campaign (if it’s too small, results are noisy).
5. Name it clearly so future you understands it (“Engaged 90d - Email”).

If you’re unsure which timeframe to use, default to 90 days for engagement segments and 60-90 days for at-risk segments, then adjust after you see your purchase cycle.

Intent Segments (Browse/Cart) for Faster Wins

If onsite tracking is enabled, intent segments can make campaigns feel dramatically more relevant:

Treat intent segments as “high signal” audiences. Keep frequency low and messaging highly contextual.

Predictive / High-Intent Segments (When You’re Ready)

Klaviyo includes predictive properties for some accounts. Here are practical examples you can model:

High churn risk:
- Predicted churn risk: High
- Has placed order
Action: Win-back series with a strong reason to return

High CLV potential:
- Predicted CLV: High
- Order count: 1-2
Action: VIP-style education + curated recommendations

Segmentation That Improves Deliverability (Not Just Revenue)

Segmentation isn’t only about conversions. It also protects your sender reputation:

• Send most campaigns to Engaged subscribers (opened or clicked recently).
• Gradually re-introduce less engaged subscribers via a re-engagement series.
• Suppress people who never engage to reduce spam complaints and bounces.

This is one of the easiest ways to keep open rates stable as your list grows.

RFM-Lite (A Simple Customer Value Framework)

You don’t need a complicated model to do RFM-style targeting. Start with three simple signals:

• Recency: How recently they purchased (0-30, 31-90, 90+ days)
• Frequency: How many orders they have (1, 2-3, 4+)
• Monetary: How much they spend (above/below your store average)

From those, you can create practical segments:

Even this lightweight approach usually outperforms “send the same newsletter to everyone.”

Personalization Building Blocks

Dynamic product recommendations (template block)

{% catalog product_feed %}
  {% for product in products %}
    <a href="{{ product.url }}">
      <img src="{{ product.image }}" />
      {{ product.title }} - {{ product.price }}
    </a>
  {% endfor %}
{% endcatalog %}

Use this for: recently viewed, best sellers, and related items.

Conditional content (VIP vs first-time)

{% if person.Placed Order|count > 3 %}
  VIP early access: new drops, limited bundles, concierge support
{% else %}
  Start here: best sellers, reviews, and first-order incentive (optional)
{% endif %}

Personalization Map (Segment -> Message)

Use this table as a quick playbook:

Safe Personalization (Avoid Broken Emails)

Two rules prevent most personalization mistakes:

1. Always include a fallback (if you don’t have first name, show a generic greeting).
2. Don’t over-personalize early (use broad relevance like category affinity before deep predictions).

Example fallback greeting:

{% if person.first_name %}
  Hi {{ person.first_name }},
{% else %}
  Hi there,
{% endif %}

Measuring Segment Performance

When you look at results, compare segments on the same campaign type:

• Open rate: subject line + deliverability signal
• Click rate: relevance and offer signal
• Conversion / revenue: landing page + offer + audience fit
• Unsubscribes: frequency and mismatch signal

If a segment has strong clicks but weak conversion, the email is doing its job and your product page or offer likely needs work.

Common Mistakes (Quick Fixes)

• Micro-segments too early: If a segment has only a few dozen people, results swing wildly. Broaden it until you have volume.
• No exclusions: Exclude recent purchasers from promos and exclude unengaged subscribers from most campaigns.
• Personalization without fallbacks: Always add default text and backup product blocks so emails don’t look broken.
• Mixing intent levels: Don’t send the same message to browsers and purchasers. Match the CTA to the intent.
• Changing definitions constantly: Keep segment definitions stable for a few weeks so you can compare performance.

If you’re unsure where to start, build Engaged + VIP first, then iterate. This keeps reporting simple and improvements easy to measure.

Quick QA Checklist

• Segments have enough people to test (avoid micro-segments early)
• Browse-based segments only run if onsite tracking is verified
• Exclusions are in place (recent purchasers, unengaged, etc.)
• Every email has one primary CTA and matches the segment intent
• Dynamic blocks have fallbacks (no broken greetings or empty product blocks)

# List the 5 most recent orders (GraphQL)
curl -X POST "https://your-store.myshopify.com/admin/api/2025-01/graphql.json" \
  -H "X-Shopify-Access-Token: $SHOPIFY_ADMIN_TOKEN" \
  -H "Content-Type: application/json" \
  -d "{\"query\":\"{ orders(first: 5, sortKey: CREATED_AT, reverse: true) { edges { node { id name createdAt totalPriceSet { shopMoney { amount currencyCode } } customer { email } } } } }\"}"

Sources

• Getting started with Shopify (Klaviyo Help Center)
• Klaviyo email benchmarks by industry (2025)