We built Segmentvue because lifecycle marketing was flying blind.
Every growth team we talked to had the same problem: their CRM stored purchase history, their email tool stored opens, and nobody had a single place that connected the two to tell them who was about to churn.
Built by someone who ran the quarterly spreadsheet churn model for six years.
Trevor Washington spent six years leading growth and lifecycle marketing at a mid-size DTC subscription company in Indianapolis. Every quarter, his team exported data from three different tools, stitched them together in a shared Google Sheet, ran a rough churn model based on recency and email engagement, and sent the results to the lifecycle team.
By the time the model ran, a third of the customers it flagged had already cancelled. The signal was real. The timing was wrong by six weeks. A daily-running model would have caught them. No one on the team had the engineering bandwidth to build one.
In 2024, Trevor co-founded Segmentvue with Maya Patel to build the prediction layer that lifecycle teams actually need. Not a generic industry churn model. Not a dashboard tool that produces a chart and stops there. A system that trains on your own behavioral history, scores every customer profile daily, and pushes those scores to wherever your team already works.
We are based in Indianapolis because that is where the team is from. We are bootstrapped because that keeps us focused on building something customers pay for, not on a narrative for investors.
Four people. One product.
Trevor Washington
CEO and Co-Founder
Six years leading growth and lifecycle marketing at a DTC subscription company. Ran the quarterly spreadsheet churn model. Saw the signal arrive six weeks too late. Built Segmentvue to fix the timing.
Maya Patel
CTO and Co-Founder
ML and data infrastructure background. Previously built real-time scoring systems at a fintech. Designed Segmentvue's per-tenant model isolation architecture. Obsessed with score explainability: a propensity score without a reason is noise.
Jordan Chen
Growth Lead
E-commerce analytics background, focused on lifecycle strategy for DTC brands. Bridges the gap between what a prediction model outputs and what a lifecycle team needs to actually run a win-back sequence on it.
Alex Rivera
Data Engineer
Specialized in event streaming pipelines and warehouse ingestion. Built Segmentvue's ingest layer to handle out-of-order events, de-duplication, and schema drift without breaking the model's training data. Your events arrive clean, or we catch the problem before the model sees it.
Three constraints we built the product around.
Propensity scores must be explainable.
We show you the top contributing behavioral signals alongside every churn probability score. No login in 18 days. No email open in 22 days. Plan downgrade 3 weeks ago. A lifecycle team cannot act on "73% churn risk" alone. They need to know which signal to address, and why that signal matters for this customer.
Your customer data does not train anyone else's model.
Each tenant's churn and LTV models are trained exclusively on that tenant's own behavioral history. There are no shared models, no cross-tenant signal pooling, and no use of your customer data to improve predictions for other accounts. Your first-party data stays in your model, isolated.
We do not build campaign tools. We feed them.
Segmentvue does segmentation and churn prediction. That is the full scope. We do not build email editors, attribution reports, or A/B testing modules. We build the prediction layer that makes your existing activation tools smarter. If we started building everything, we would become mediocre at the one thing that actually matters.
We read every email.
For questions about implementation, data privacy, how the churn model works on your specific data structure, or pricing, Trevor or someone on the team replies personally. We do not route support through a bot or a ticket queue first.
Most emails get a same business day response. For urgent technical issues during onboarding, put "urgent" in the subject line and we treat it as priority.