One platform. Behavioral data, living segments, and churn predictions that update while your customer sleeps.
Segmentvue is a prediction-first customer data platform. It ingests behavioral events from your stack, builds segment populations that update in real time, and trains a churn and LTV model on your own data. Every customer profile carries a daily-updated propensity score your team can act on.
First-party data in. Unified profiles out.
Segmentvue ingests behavioral events from your storefront, payment processor, and web app into a single unified customer profile. Page views, order completions, email opens, plan changes, and cancellation attempts all land in the same timeline. That timeline is what the prediction model reads.
JavaScript SDK
One script tag. Tracks page views, custom events, and user identity. Call Svue.track() for the events that matter to your lifecycle model: order completions, logins, plan changes, cancellation clicks.
SQL Sync
Connect directly to Postgres, BigQuery, Snowflake, or Redshift. Write a query that returns customer events, set a sync schedule, and Segmentvue treats your warehouse rows as behavioral history. No ETL tooling required.
Webhook Ingest
Point your Shopify or Stripe webhook at your Segmentvue ingest endpoint. Order events, subscription renewals, and payment failures arrive in real time and feed directly into your customer profiles and segment membership calculations.
Svue.init('wk_your_write_key');
// Identify a user
Svue.identify('user_123', {
email: '[email protected]',
plan: 'growth'
});
// Track an event
Svue.track('Order Completed', {
order_id: 'ord_456',
revenue: 89.00
});
Rule-based and AI-surfaced segments
Write conditions against any behavioral attribute in your unified profile: last order date, email open rate, login frequency, plan tier, feature adoption count. Combine conditions with AND/OR logic, name the segment, and Segmentvue keeps it current as events arrive.
The AI Clusters tab surfaces patterns without requiring a SQL query or a data analyst. Natural-language prompts like "find customers who look like they will churn in 60 days" return a live segment with a member count badge and the top contributing signals.
Trained on your behavioral history. Not a generic industry model.
Your churn model, isolated to your tenant
The churn propensity model and LTV forecast are trained on your tenant's own event history. No cross-customer data sharing, no generic industry benchmarks applied. A subscription company's churn signals look different from a DTC brand's churn signals. Your model learns yours.
Every score includes confidence bands. When a customer's propensity score moves across a threshold, segment membership updates and your activation sync fires. You see the shift before your next weekly report, not after.
Score explainability: "Why is this customer at risk?" Top contributing signals: no login in 18 days, no email open in 22 days, plan downgrade 3 weeks ago. A propensity score without a reason is just noise. We show the reason.
Reverse ETL to wherever your team activates.
Segmentvue is not a campaign tool. It is the prediction layer that feeds your campaign tools. Segment membership and churn scores sync out to your ESP, CRM, and data warehouse so every downstream tool acts on current data.
Email ESP (one-way)
When a customer's churn propensity score crosses 65%, Segmentvue adds them to your win-back sequence automatically. The At-Risk segment syncs to Klaviyo, Braze, or Iterable on the schedule you set. No manual list export.
CRM (two-way)
Write the daily churn score and current segment name back to a contact field in Salesforce or HubSpot. Your account manager sees the risk level before the renewal call. Behavioral events from the CRM flow back into the unified profile.
REST API
Fetch segment membership and propensity scores for any customer by ID. Use it for in-app personalization, to populate suppression lists, or to feed a downstream BI tool with prediction signals that belong next to your cohort retention charts.
Cohort health, LTV trends, churn rate by segment.
Track member count changes, average LTV per segment over time, and cohort retention curves that show you where a given acquisition month is heading. Export as CSV or push via webhook to your BI tool. Segmentvue is the prediction layer, not the reporting destination. Use it alongside whatever you already have.