Answers all questions about your lifecycle performance.
Analyst AI monitors campaigns and journeys continuously, builds dashboards on demand, and explains what's driving every metric change.
Trusted by lifecycle teams at
What Analyst AI is built for
Analyst AI helps lifecycle teams measure every campaign against a baseline, explain what moved, and turn the results into the next recommendation.
Revenue attribution on demand
Which campaigns are generating revenue? Analyst AI answers from your warehouse, not a dashboard estimate.
Get the explanation, not just the number
When a metric drops, Analyst AI tells you why — distinguishing between fatigue, frequency, audience size, and data sync issues.
A/B readouts without waiting for the data team
Analyst AI runs experiment comparisons directly from your warehouse and writes the interpretation.
Which two campaigns drove the most revenue per email this quarter?
Analyst AI
I ranked this quarter's campaigns by revenue per email and compared each with last quarter.
- Reactivation: $4.80 per email, up 18% on last quarter
- Win-back May: $2.40 per email, up 6% on last quarter
“Sortment is basically a system that is watching over your users so you don't have to. It identifies patterns, comes up with next steps, and even writes the content to reach those users.”
— Jatin, Co-founder, Topdog
What Analyst AI does
Watches everything. Explains what changed. Tells you what to do.
Catches problems before they show up in revenue
Engagement drops and retention risks surface in Analyst AI before they appear in your weekly numbers. It watches every active campaign continuously — no scheduled pull, no one needing to check.
Analyst AI
I've spotted a drop in your win-back sequence. Campaign delivery is unchanged.
Likely cause: subject line fatigue. The same format was used 4 times in 14 days.
Tells you why the metric changed — not just that it did
Subject line fatigue. Send frequency. Audience exhaustion. Data sync delay. Analyst AI distinguishes between these causes, ranks the most likely ones, and rules out the ones that don't fit.
A/B readouts without waiting for the data team
Compares Group A vs Group B on revenue, conversions, and engagement. Queries your warehouse directly and produces a decision-ready interpretation.
Problems surface in minutes, not at the weekly review
A drop that used to sit unnoticed for 7 days now surfaces in under 15 minutes. The same team gets ahead of problems instead of cleaning them up after the fact.
Time from issue to team awareness (Avg.)
7 days Last quarter
14 mins This quarter
Reads from your warehouse directly
Connects to Snowflake, BigQuery, Redshift, Databricks, ClickHouse, Trino, Postgres and Azure. Answers come from the same data your analytics team uses — not a dashboard approximation.
From player data to deposit growth
Analyst AI helped Topdog identify where users were dropping, surface dormant cohorts, and turn those insights into lifecycle campaigns.
5x Increase in first-deposit conversion
5% Dormant users returned and re-deposited
1 day To connect Redshift and get onboarded
How Analyst AI works
Connect your data once. It monitors continuously and flags what changes.
1 Connect
Connects to your warehouse and your ESP. During onboarding it learns your metrics and baseline benchmarks.
2 Monitor
Watches all active campaigns continuously. When a metric crosses a threshold, it surfaces an alert — no scheduled pull or manual check needed.
3 Explain and recommend
Every alert includes what changed, the most likely cause, and a specific recommended action. Apply the change — Analyst AI monitors whether it works.
Why lifecycle teams use Analyst AI
When your team finds out about problems a week late — or waits days for a data pull.
Early Warning
Analyst AI watches every active campaign continuously. When a metric drops, it surfaces the alert in minutes, not at the next weekly review.
Know before the damage compounds.
Open rate monitoring
Click rate anomalies
Revenue per email alerts
Root Cause
A metric change without an explanation isn't actionable. Analyst AI ranks the most likely causes and rules out the ones that don't fit.
Cut straight to what changed.
Subject line fatigue
Send frequency
Audience exhaustion
Attribution Clarity
Analyst AI returns campaign-level attribution from your warehouse broken down by cohort and time period, not estimated.
Revenue tied to the campaign that earned it.
Revenue per email
Campaign-to-order attribution
Cohort revenue comparison
How teams use Sortment
Add Sortment to Braze, Iterable, or any other ESP without migrating, or use it to replace your CEP entirely.
With your existing stack
Full CEP replacement
Keep your CEP, add Sortment where it helps.
Your warehouse. Your ESP. Sortment sits in between.
Analyst AI connects to your warehouse, explains drops, compares cohorts, builds dashboards, and turns performance questions into clear next steps.
Replace scattered tools with one AI-native CEP.
One platform. Every channel. No handoffs.
Sortment replaces your CEP entirely. Journeys, campaigns, segments, content, analytics, and AI agents all run in one platform. No more coordinating across Asana, Jira, or Slack. No shared resources, no data team tickets, no waiting. Everything your lifecycle team needs to execute, in one place.
FAQs
What does Analyst AI monitor?
Can I ask Analyst AI questions in plain language?
Does Analyst AI build dashboards?
Can Analyst AI explain what's causing a metric change?
Does Analyst AI replace a dedicated analytics team?
See Analyst AI on your own data.
Book a 30-minute call. Analyst AI connects to your campaign data, starts monitoring right away, and surfaces its first findings within a week.
No migration · Works alongside your existing stack