The Viral DNA Engine, specified
The Engine is a closed loop that turns high-volume UGC into a ranked, revenue-attributed format library. It ingests your brand, constraints, tracking setup and content history, tags every asset to a format/angle/hook/CTA/creator, scores everything with the Rabk Rate Score, and publishes exactly 3–5 formats worth scaling. Views are treated as diagnostics; revenue and conversion-chain efficiency decide outcomes.
Inputs & outputs
What goes in, what ships out
Required inputs
- A · Brand + Offer
- App name, category, pricing model, conversion events (install, signup, trial, purchase, subscription), value props, differentiators, proof points, objections, 2–5 ICP segments with their pains, outcomes and intent lexicon seeds.
- B · Constraints
- Platforms (TikTok, Reels, Shorts), geos, compliance and brand-safety rules, production budget, turnaround time, creator availability.
- C · Tracking setup
- MMP or equivalent, UTM conventions, deep links, event schema (install, signup, purchase, trial, subscription, refund), conversion windows D0/D1/D7/D30.
- D · Content library (optional)
- Past posts with views, watch time and any conversion metrics for warm-start scoring.
Outputs
- Viral DNA Report
- 3–5 winning formats, why they win, and the conversion chain that proves it.
- Production Queue
- Next 30 days of posts by format, creator, angle and hook.
- Experimentation Plan
- Hook, angle, offer and landing-flow tests with stop-loss rules.
- Dashboard Spec
- Rabk Rate leaderboards, conversion-chain views, cohort revenue.
- Self-Improving Loop
- Weekly and monthly templates that update the format library.
Data model
Every asset links to an outcome
Four linked tables. If a field can't be joined back to revenue, it doesn't belong in a decision.
ContentAsset
id · platform · post_date · creator_id · format_id · angle_id · hook_id · cta_id · length · caption · hashtags · geo · spend
Performance
views · 3s_views · avg_watch_time · completion_rate · shares · saves · comments · profile_clicks · link_clicks
Attribution
installs · signups · trials · purchases · subscriptions · revenue · refunds · D0/D1/D7/D30 cohorts
Derived
CVR_view→click · CVR_click→install · CVR_install→signup · CVR_signup→purchase · revenue_per_1k_views · revenue_per_post · payback_proxy
Rabk Rate calculation
Each component is percentile-normalized within the account, weighted, then mapped onto a 300–850 band so scores stay comparable as revenue scales.
Rabk = 300 + 550 × (0.40·revenue_index + 0.30·chain_index + 0.20·stability_index + 0.10·quality_index)
Decision rules
Codified, not discretionary
These rules run before anyone's opinion enters the room.
Top performers by revenue_per_post AND revenue_per_1k_views, with no conversion step below its guardrail floor, Rabk ≥ 700, minimum N met, and stability across two consecutive weekly windows.
Views in the top quartile while installs/purchases sit in the bottom quartile → flagged Vanity Format, capped at exploration budget, cut if a second window repeats.
N = 30–50 posts per format per week as the starting floor, adjusted to traffic. Below floor, the format is 'Insufficient' — never 'losing'.
If total volume is under floor, the only prescribed action is raising volume. No edit-level tinkering is allowed to consume the cycle.
Exactly 3–5 formats are published as Viral DNA. If evidence is insufficient, the Engine emits a Data Gap Plan / 30-Day Signal Plan instead.
70–90% of output to winners, 10–30% to exploration, permanently. Winners are re-verified weekly or lose their allocation.
Workflow
Diagnose → Generate → Launch → Measure → Extract → Scale → Self-improve
01 Diagnose
- Verify tracking integrity: deep links fire, UTMs consistent, events deduped.
- Lock event definitions and conversion windows before any posting.
- Map 2–5 ICP segments to search/intent clusters and objection lists.
- Build a starter library of 10–20 candidate formats across intent stages.
02 Generate high-intent formats
- Per ICP, produce angles: problem-aware, solution-aware, comparison, objection, proof, tutorial, story, contrarian, myth-busting.
- Every format must carry a conversion path and one measurable CTA.
- Assign IDs at creation: format_id, angle_id, hook_id, cta_id.
03 Launch volume
- Deploy 600–1,500 posts/month across the creator roster (or proportionally scaled).
- Reject any asset missing tags — untagged posts are unmeasurable and don't ship.
- Distribute evenly across formats so no format starves for sample.
04 Measure
- Daily ingestion of platform performance and MMP conversion events.
- Rolling 7/14/28-day leaderboards by format, creator, angle, hook and CTA.
- Cohort revenue at D0/D1/D7/D30 so short-window wins aren't over-credited.
05 Extract Viral DNA
- Rank by Rabk Rate, filter on minimum N and two-window stability.
- Publish 3–5 format cards plus creator briefs for replication.
- Document the failure modes that killed near-miss formats.
06 Scale
- Shift 70–90% of production to winners with coordinated daily volume.
- Hold 10–30% for new formats and variants so the library keeps refreshing.
- Expand winners by variant, not by rewriting the winning structure.
07 Self-improve
- Weekly: update hypotheses, retire losing variants, expand winning variants.
- Monthly: refresh ICP insights, landing pages and app-store conversion inputs.
- Quarterly: rebase Rabk thresholds against the new revenue distribution.
Dashboard spec
Six views, one question: what pays?
Rabk Leaderboards
Format, creator, angle, hook and CTA tables sorted by Rabk with N and stability badges.
Conversion Chain
Funnel per format: view→click→install→signup→purchase with guardrail floors marked.
Revenue Cohorts
D0/D1/D7/D30 revenue and refunds by format and post date.
Vanity Radar
Scatter of views vs. revenue_per_1k_views; the high-view/low-revenue quadrant is the kill list.
Volume Monitor
Posts/day vs. required floor per format, with an alert when sample size is at risk.
Experiment Board
Live tests, window, decision date, and automatic stop-loss status.