Four production ML models running on your customer data. Predictions delivered weekly into the tools your team already uses. No BI team, no new dashboard, no guesswork.
Think of Vantage as a junior analyst who works on your customer data every night and delivers a report every Monday. The difference: this one never misses a pattern, doesn't need a salary, and gets smarter every week.
Technically, Vantage is four ML models running on BigQuery and Vertex AI, producing weekly prediction outputs via reverse ETL into Klaviyo, Braze, or HubSpot. But for your marketing team, it is simply this: a weekly signal telling you which customers to save, which to up-sell, and which tactics are actually working before your competitors figure out the same thing._
Identifies customers likely to disengage 30–90 days before it happens.
What this enables Automated win-back flows triggered before the window closes.
Projects per-customer lifetime value from early purchase signals.
What this enables Acquisition decisions grounded in long-run profitability, not first-order ROAS.
Learns each customer's engagement window from historical behaviour.
What this enables Per-customer send scheduling that reduces fatigue and lifts open rates.
Overlays LTV and churn scores on ad cohorts.
What this enables Campaign reporting that shows downstream value, not just clicks and ROAS.
We wire your data sources (Shopify, Klaviyo, ad platforms) into BigQuery via Fivetran or Airbyte. Your data stays in your infrastructure.
All four models run on your customer data in an isolated environment. First predictions generate within two weeks of data access.
Predictions push into your CRM segments and ad audiences via reverse ETL. Weekly formatted reports arrive in your inbox, plain language, ready to act on.
Your data needs to be large enough to train on. If you have 1,000+ customers, six or more months of order history, and Klaviyo, Braze, or HubSpot already active, you meet the threshold. If you're not there yet, we'll tell you exactly what it will take to get there, and when.
We assess your stack and show you what the models would surface before you commit.
45 minutes on synthetic data. You'll see exactly what your clients would receive.