The Revenue Stack That Doesn't Fight Itself.
Most revenue teams maintain parallel customer records — Salesforce's "Account" and Shopify's "Customer" never quite agree, and the marketing audience and helpdesk view are off too. Aeion runs CRM + Commerce + Marketing + Helpdesk + AI on one tenant database with one customer record. Lead-to-revenue attribution works because the data is actually unified. Abandoned-cart AI, deal coaching, and churn prediction all see the customer's full history.
The Pain You're Feeling
Revenue stacks fail in predictable places.
The Native Aeion Stack
Five modules running against one tenant database with one customer record.
The Integration Pattern
Concrete examples of how the modules compose without engineering glue.
What You'll Actually See
Operational outcomes customers in this pattern report.
The Migration Playbook
Realistic sequence for replacing the existing revenue stack.
Where This Pattern Isn't the Right Fit
Honest about where the revenue stack pattern doesn't apply.
Frequently Asked Questions
Yes. Common pattern: Aeion ships abandoned-cart AI, churn prediction, and helpdesk-CRM unification while Salesforce remains the canonical sales tool. Bidirectional Singularity sync keeps both in agreement. Many customers run this for 6-18 months before full migration.
Yes — scoring blends who the lead is (title, company size, industry) with what they've actually done (email opens, link clicks, form submissions, document downloads), weighted toward real engagement over firmographics. Score history is kept and versioned, so reps see the trajectory, not just a snapshot, and scores recalculate on a regular cadence so stale leads drop out of the pipeline automatically.
Singularity auto-detects custom fields from the source schema and maps them onto your contacts and accounts. No data loss; any conflicts surface in the field-mapper UI for you to resolve before import completes.
For most teams, yes. Email + SMS + push + AI-personalized templates + audience segmentation built on the same customer table as commerce. Where you'd keep an external tool: very complex multi-step automations or industry-specific email templates with strict deliverability requirements.
Aeion's AI sees the customer's full history (CRM, commerce, marketing engagement, helpdesk satisfaction). Klaviyo sees only Klaviyo's data. Recovery rate is typically higher because the personalization is informed. See /commerce for the abandoned-cart AI architecture.
Yes — plan-entitlement gating doubles as a feature-flag system for staged rollouts. Aeion isn't a dedicated A/B platform like Optimizely; for randomized controlled experiments with full statistical-significance testing, you'd pair with Optimizely or Statsig.
Customers report a meaningful revenue lift from the combined effect of: better lead scoring (more sales-ready leads), better abandoned-cart recovery (more captured orders), better churn prevention (lower revenue leak), better cross-module visibility (faster deal cycles). Individual results vary widely with starting baseline.
Phased migration keeps both stacks live in parallel during cutover. Read-only sync from legacy systems means no missed orders, no lost leads. Zero revenue interruption is achievable; the trade-off is the operational complexity of running two stacks during the overlap. The migration playbook above documents the standard sequence.