AI Self-Growth System
Cross-Promotion Engine
PremiumThe best ad slot is your own product interface.
Cross-Promotion Engine: Keep Users in Your Gravity Field
"When you have 10 products, you already own your own ad network."
What you will get in this chapter
- Minimum viable cross-promotion system (MVS)
- Cross-promotion SOP and placement strategy
- Core metrics and acceptance criteria
One-sentence definition
Cross-promotion = recommend the right product at the right time.
When users finish the current task, it is the best time to recommend.
Minimum viable cross-promotion system (MVS)
| Step | You need | Acceptance result |
|---|---|---|
| Placement | One result-page placement | CTR >= 3% |
| Rules | Complementary tool matching | Clear conversion |
| Tracking | UTM/event tracking | Conversions measurable |
Qualified signal: cross-site activation >= 5%.
Cross-promotion SOP (standard process)
- Define complements: tool A pairs with tool B
- Pick placements: result page / completion page / pre-exit
- Create recommendation cards: title + value points + CTA
- Track: UTM + conversion events
- Optimize rules: adjust based on CTR and conversion
Placement strategy
- Result page: highest conversion
- Header menu: global exposure
- Footer fallback: rescue traffic
Principle: do not interrupt tasks; recommend after completion.
Core metrics (must track)
Definition (default):
- Time window: unless stated otherwise, use the last 7 days rolling.
- Data source: use one trusted source (GA4/GSC/platform console/logs) and keep it consistent.
- Scope: only the current product/channel, exclude self-tests and bots.
| Metric | Meaning | Pass line |
|---|---|---|
| Cross-CTR | Recommendation CTR | >= 3% |
| Cross-Activation | Cross-site activation | >= 5% |
| Exit Rate | Exit rate change | down >= 10% |
| LTV Lift | LTV lift after cross-promo | >= 15% |
Acceptance checklist
At least one result-page placement is live
Recommendation rules are defined (complementary matching)
UTM/event tracking can measure conversion
Common mistakes
- No context -> users ignore
- Recommend too early -> interrupt the main task
- No tracking -> no optimization
Community case addendum (from developer communities)
The following are public community shares. Metrics are self-reported or taken from public pages and are not independently verified:
- HN Show HN: CrossPromo Club provides newsletter cross-promotion. The author says it supports partner discovery and "single link auto matching" for cross-promo. Link: https://news.ycombinator.com/item?id=45669326
Summary
Key takeaways
1. Place recommendations at the task completion moment.
2. Recommendation relationships must be complementary, not random.
3. No tracking means no optimization.
Next chapter, we will cover Asset Reuse -- make matrix expansion faster and cheaper.
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