CRM Analytics

(CRA)

The reporting layer on top of your customer data: pipeline health, forecast accuracy, cohort retention, churn signals and customer lifetime value. It reads the same records the CRM writes, so there is no export and no lag.

Pipeline Forecasting Cohorts Churn LTV Attribution

Key Features

The reporting layer on top of your customer data: pipeline health, forecast accuracy, cohort retention, churn signals and customer lifetime value.

Pipeline Analytics

Conversion by stage, time in stage, and where deals actually stall. Win and loss reasons aggregated instead of buried in notes.

Forecasting

Weighted and committed forecasts by rep, team and period, measured against what actually closed.

Cohort Retention

Group customers by acquisition period, channel or segment and watch how each cohort behaves over time.

Churn Signals

Rules and scores that flag accounts going quiet before they leave, based on order cadence and engagement.

Customer Lifetime Value

LTV per customer, segment and channel, built from real order history rather than an assumed average.

Campaign Attribution

Tie revenue back to the campaign, source and territory that produced it, across every channel the customer used.

How It Works

Three stages, end to end.

01

Read, do not export

Analytics runs on the same records CRM, OMS and Commerce write. There is no nightly export to go stale.

02

Segment and compare

Slice by cohort, segment, channel, rep or territory, and compare periods without building a new report each time.

03

Act on the signal

Push a segment straight back into a campaign, a price list or a loyalty tier instead of exporting a list.

Integration Flows

See how CRM Analytics connects with other Kubrik ERP modules.

Pipeline → Forecast

Opportunity (CRM) Stage Weighting Forecast (CRA) Actuals

Orders → LTV

Order History (OMS) Customer (CRM) LTV (CRA) Segment

Signal → Action

Churn Score (CRA) Segment Campaign / Offer Retention

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