Klaviyo

Remark’s Klaviyo integration helps you turn shopper conversations into better-targeted email and SMS marketing. Once connected, Remark can send rich shopper context into Klaviyo, and Klaviyo can send email engagement signals back into Remark.

Shopify Custom Pixel

Make sure your Shopify permissions and pixel setup are in place before going live.

What the integration does

At a high level, the integration has two jobs:

It sends shopper context from Remark into Klaviyo so you can personalize messaging based on real conversations, recommendations, and buying signals.
It brings Klaviyo email engagement data back into Remark so your team can see whether a shopper opened, clicked, bounced, or unsubscribed.

That means Klaviyo gets richer profile data, and Remark gets better visibility into how marketing emails are performing for each shopper.

How Klaviyo fits into your stack

If you use Shopify, the cleanest setup is:

Shopify syncs your catalog into Klaviyo
Remark syncs shopper context, conversation data, and recommendation data into Klaviyo
Remark uses product external_id values so recommended products can line up with your Klaviyo catalog records

Remark does not build or manage your Klaviyo product catalog. If you want product-aware emails in Klaviyo, be sure to install the Shopify app in Klaviyo and let Remark supply the shopper context around those products.

Connecting Klaviyo to Remark

Remark connects to Klaviyo through OAuth in the dashboard. This gives Remark a secure connection to your Klaviyo account without relying on a long-lived private API key workflow. After connection:

Remark stores the connection and refreshes tokens automatically
Existing legacy API-key installs can be migrated to OAuth
Remark can auto-provision certain Klaviyo assets, including Remark universal content blocks for approved experts

When profile data updates

Profile sync is designed around meaningful shopper activity, especially completed conversations. In practice, that means Klaviyo profiles are updated after Remark has enough context to send useful information instead of partial noise.

Data flow at a glance

Direction	Data type	Purpose
Remark -> Klaviyo	Profile properties	Enrich Klaviyo profiles for segmentation and personalization
Remark -> Klaviyo	Event data	Trigger flows and measure shopper actions tied to Remark
Klaviyo -> Remark	Email engagement events	Show opens, clicks, bounces, and unsubscribes in shopper context

Profile properties synced from Remark

Native Klaviyo fields

Klaviyo field	Typical Remark source
`first_name` / `last_name`	Shopper name learnings
`phone_number`	Shopper phone learnings
`locale`	Shopper language
`image`	Profile image when available
`location.address1` / `location.address2`	Mailing address learnings
`location.city` / `location.region` / `location.country` / `location.zip`	Mailing address or location learnings
`location.timezone`	Shopper timezone
`location.ip`	Shopper IP when available

Remark custom profile properties

Property	Type	Meaning
`remark_last_conversation_timestamp`	string	ISO timestamp of the latest synced conversation
`remark_conversation_tags`	string[]	Smart tag titles associated with the conversation
`remark_recently_recommended_products`	object[]	Recently recommended products with product metadata
`remark_expert_name`	string	Expert name associated with the shopper interaction
`remark_expert_follow_up`	string	AI-generated follow-up copy when available
`remark_shopper_language`	string	Shopper language
`remark_shopper_device_type`	string	Device type such as mobile or desktop
`remark_shopper_region`	string	Most recent known region
`remark_shopper_buying_intent_level`	string	Buying intent level from Remark
`remark_shopper_top_category`	string	Strongest current category interest
`remark_interests`	string[]	Consolidated interest-type learnings
`remark_shopping_categories`	string[]	Categories the shopper is shopping for
`remark_product_styles`	string[]	Product style preferences
`remark_product_use_cases`	string[]	Intended use cases
`remark_product_features`	string[]	Desired product features
`remark_product_materials`	string[]	Material preferences
`remark_product_budget`	string	Budget signal
`remark_shopper_height`	string	Height when relevant to fitment
`remark_shopper_weight`	string	Weight when relevant to fitment
`remark_shopper_gender_preference`	string	Gender preference when captured

Some properties are only present when Remark has enough data to populate them. Sparse profiles are normal.

`remark_recently_recommended_products` shape

This field is especially useful for lifecycle marketing because it carries both recommendation context and a catalog identifier.

[
  {
    "name": "Alpine Touring Boot",
    "external_id": "12345",
    "why_recommended": "Matches the shopper's fit and terrain preferences"
  }
]

For Shopify stores:

external_id is the key product identifier Remark sends for product-aware sync
Be sure to install the Shopify app in Klaviyo
Remark adds the shopper and recommendation context; it does not create the catalog itself

What events Remark sends into Klaviyo

Remark can send event-based signals into Klaviyo for automations and reporting.

Event	Typical trigger	Common use
`remark_conversation_completed`	A shopper conversation finishes	Post-conversation follow-up flows
`remark_product_recommended`	Remark recommends a product	Recommendation follow-up or browse-to-buy journeys
`remark_activator_clicked`	Shopper clicks into the Remark experience	Top-of-funnel or engagement automations
`remark_high_intent_detected`	Remark detects a strong buying signal	Fast-moving high-intent journeys
`remark_blog_post_viewed`	Shopper views a Remark-generated blog post	Content interest or nurture flows
`remark_smart_tag_applied`	Remark AI applies a smart tag	Behavioral segmentation
`remark_learning_created`	New structured learning is persisted	Preference-based automations

Representative event payloads

`remark_product_recommended`

{
  "product_name": "Alpine Touring Boot",
  "product_external_id": "12345",
  "remark_lead": "lead_abc123"
}

`remark_blog_post_viewed`

{
  "blog_post_id": "post_123",
  "title": "How to Choose the Right Touring Setup",
  "url": "https://www.example.com/blog/touring-setup",
  "topic": "touring",
  "featured_products": [
    {
      "name": "Alpine Touring Boot",
      "external_id": "12345"
    }
  ]
}

`remark_smart_tag_applied`

{
  "tag_id": "tag_123",
  "tag_title": "High fit confidence",
  "tag_description": "Shopper gave specific fit preferences",
  "confidence_score": 0.94
}

`remark_learning_created`

{
  "learning_id": "learning_456",
  "learning_type": "interest",
  "learning_key": "skiing",
  "learning_value": "powder skiing",
  "prettified_string": "Interested in powder skiing",
  "confidence_score": 0.91
}

`remark_conversation_completed`

The conversation-completed event is typically paired with the richest profile update. Use it when you want Klaviyo flows to react to a finished conversation and then read the latest profile properties for personalization.

What Klaviyo sends back into Remark

Remark also ingests email engagement data from Klaviyo.

Klaviyo engagement	Meaning inside Remark
Opened	Shopper opened a marketing email
Clicked	Shopper clicked a marketing email link
Bounced	Email delivery bounced
Unsubscribed	Shopper unsubscribed from email marketing

Remark uses these events to enrich the shopper timeline and filters inside the dashboard. Your team can see recent engagement activity alongside conversation and browsing behavior, which gives a better read on whether a shopper is still engaged.

Typical use cases

Common ways to use this integration include:

Building segments based on shopper intent, preferences, or recent conversations
Following up after expert conversations with more relevant product or category messaging
Using Remark recommendation context in campaigns and flows
Understanding whether a shopper who talked to an expert is also engaging with marketing emails

What to expect from the data

Not every profile will contain every field. The exact shape depends on what the shopper actually shared or did. For example:

Some shoppers will have recommendation data but no location data
Some will have category and product-interest learnings but no phone number
Some profiles will gain more detail over time as more conversations happen

That is expected. The integration is designed to accumulate useful context over time rather than require every field upfront.

Notes and edge cases

remark_expert_follow_up may not be populated on every profile, especially where backfill would require generating new AI content.
Some product objects may omit external_id if the upstream product identifier is unavailable, but catalog-aware usage works best when it is present.

Getting Started

Guides

API

Integrations

Shopify Custom Pixel

What the integration does

How Klaviyo fits into your stack

Connecting Klaviyo to Remark

When profile data updates

Data flow at a glance

Profile properties synced from Remark

Native Klaviyo fields

Remark custom profile properties

`remark_recently_recommended_products` shape

What events Remark sends into Klaviyo

Representative event payloads

`remark_product_recommended`

`remark_blog_post_viewed`

`remark_smart_tag_applied`

`remark_learning_created`

`remark_conversation_completed`

What Klaviyo sends back into Remark

Typical use cases

What to expect from the data

Notes and edge cases

Getting Started

Guides

API

Integrations

Documentation Index

Shopify Custom Pixel

​What the integration does

​How Klaviyo fits into your stack

​Connecting Klaviyo to Remark

​When profile data updates

​Data flow at a glance

​Profile properties synced from Remark

​Native Klaviyo fields

​Remark custom profile properties

​remark_recently_recommended_products shape

​What events Remark sends into Klaviyo

​Representative event payloads

​remark_product_recommended

​remark_blog_post_viewed

​remark_smart_tag_applied

​remark_learning_created

​remark_conversation_completed

​What Klaviyo sends back into Remark

​Typical use cases

​What to expect from the data

​Notes and edge cases

What the integration does

How Klaviyo fits into your stack

Connecting Klaviyo to Remark

When profile data updates

Data flow at a glance

Profile properties synced from Remark

Native Klaviyo fields

Remark custom profile properties

`remark_recently_recommended_products` shape

What events Remark sends into Klaviyo

Representative event payloads

`remark_product_recommended`

`remark_blog_post_viewed`

`remark_smart_tag_applied`

`remark_learning_created`

`remark_conversation_completed`

What Klaviyo sends back into Remark

Typical use cases

What to expect from the data

Notes and edge cases