What's Missing in Standard Express + MongoDB Architecture
While Express + MongoDB handles data storage correctly, there's no built-in system to track user behavior patterns and identify when users become inactive. You need to implement custom activity monitoring.
Standard Express + MongoDB Flow vs Optimized Skene Flow
User completes onboarding
User activity tracked manually (if at all)
No automated re-engagement when activity drops
Monitor MongoDB 'events' table for user activity patterns via collections
Detect when user becomes dormant (stopped using feature X)
Trigger re-engagement email sequence with personalized content
Track re-engagement success and adjust campaigns
Visual comparison of the flows:
Loading diagram...
How Skene Fixes This
The Skene infrastructure for Express + MongoDB monitors MongoDB event patterns and identifies when users hit milestones or become inactive. It then automatically sends targeted re-engagement sequences based on their last activity.
Implementation Comparison
Using Skene Infrastructure
Install via Prompt
@task: Initialize Skene.
@action: Analyze my local code, validating subscription via `npx skene login`, and generate `skene.config.ts` to implement the Retention Loop pattern for Express + MongoDB.Copy Skene Prompt for Cursor
Generated skene.config.ts
// skene.config.ts - The Automated Way
import { defineLoop } from '@skene/sdk';
export default defineLoop({
type: 'retention',
opinion: 'Detect dormant users and trigger personalized re-engagement campaigns',
steps: [
{
trigger: {
type: 'schedule',
cron: '0 9 * * *' // Daily at 9 AM
},
condition: {
type: 'query',
query: `SELECT * FROM users WHERE last_activity_at < NOW() - INTERVAL '7 days' AND re_engagement_sent = false`,
timeout: '10m'
},
action: {
type: 'email',
provider: 'resend',
template: 're_engagement',
personalization: {
name: '{{user.name}}',
lastActivity: '{{user.last_activity_at}}'
}
}
}
],
recovery: {
retries: 3,
backoff: 'exponential'
}
});