What's Missing in Standard Redis Architecture
Redis stores data efficiently, but there's no system to track user behavior patterns and identify when users become inactive or hit growth milestones.
Standard Redis Flow vs Optimized Skene Flow
Standard Flow
1
User has access to Redis features
2
Features available but usage not monitored
3
No activation prompts for unused features
Skene Flow
1
Monitor Redis usage patterns and feature adoption
2
Identify users who haven't used key features
3
Trigger feature discovery emails with examples and use cases
4
Track feature adoption and send advanced usage guides
Visual comparison of the flows:
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How Skene Fixes This
The Skene infrastructure for Redis tracks user activity and segments users by engagement. It automatically triggers retention campaigns for dormant users and celebrates milestones for active users.
Implementation Comparison
Using Skene Infrastructure
Auto-managed state. Installed via Prompt.
Install via Prompt
cursor.mdc
@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 Redis.Copy Skene Prompt for Cursor
Generated skene.config.ts
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'
}
});