The AMALYZER — the database foundation under every Amazon SEO workflow.

The Extension solves the single-ASIN workflow. Run it ten times and the Extension's per-page workflow stops scaling — the operator becomes the bottleneck. The AMALYZER is the layer underneath that turns per-page workflow into bulk operation: a queryable database of every keyword, every rank, every category, every history.

What the AMALYZER actually is

• A continuously refreshed keyword index. Hundreds of millions of search terms per market, refreshed on a rolling schedule. Each search term carries volume, click share, conversion share where available, and the top-100 ranking ASINs.
• A rank-history database. Daily rank for every tracked ASIN against every relevant keyword, going back years for accounts that have been on the platform.
• A category structure. Browse-node tree, refinement-filter mapping, and per-category keyword-volume distributions — the data behind every benchmark in the rest of the Module.
• A relationship graph. Synonym clusters, "shoppers also searched" links, brand→product relationships — the network the algorithm uses internally.

The portfolio-scale workflow

1. Bulk ASIN upload. Upload a CSV of every ASIN in the portfolio. The AMALYZER attaches the current keyword set, rank history and competitor cohort to each.
2. Category-wide opportunity scan. For each ASIN, surface every keyword where the ASIN currently sits between rank 11 and rank 30 — the position where a small SEO improvement can vault the listing onto the first page. These are the highest-ROI candidates to rewrite first.
3. Cross-portfolio competitor pull. Identify the competitor ASIN that most threatens each of your ASINs. Pull their full keyword set. The intersection-difference is your portfolio-wide gap list.
4. Bulk indexation check. Across the entire portfolio, run an indexation pass on every ASIN's top 50 keywords. Lost-indexation rows are the bulk-prioritised copy-fix queue.
5. Roll-up reporting. Per-brand, per-category, per-launch-cohort metrics on rank distribution, indexation health and keyword coverage. The numbers stakeholders ask for, available on demand.

Why the database layer matters more than the UI

• Cross-product analysis. "Show me every ASIN in the portfolio that ranks for at least 5 keywords above 100,000 monthly searches" is a database query. Without the database, it's a week of manual work per ASIN.
• Time-series questions. "Which keywords drifted in the last 60 days?" is unanswerable without daily snapshots stored over time.
• Competitor longitudinal. The same database tracks competitors over time. Detecting that a competitor relaunched a listing with a new keyword set 17 days ago is data work, not detective work.
• Decision automation. Rules — "alert me when any ASIN drops out of the top 10 on a tracked keyword" — only work because the data exists in a queryable form.

How the Extension and the AMALYZER divide labour

• Extension. Per-page, real-time, decision-support. The operator working on one listing.
• AMALYZER. Cross-portfolio, historical, programmatic. The team working on a hundred listings.
• Shield. Continuous monitoring. The alerting layer that tells the operator when to open the Extension or the AMALYZER in the first place.

Single-ASIN brands use the Extension and occasionally Shield. Mid-portfolio brands lean on Shield with periodic AMALYZER analysis. Agencies and enterprise sellers operate primarily inside the AMALYZER with Extension for ad-hoc deep dives.

The handoff to Episode 17

Both the Extension workflow (Episode 15) and the AMALYZER workflow produce keyword data, in different shapes. Episode 17 covers merging the two — the synonym-list-from-harvest with the AMALYZER's indexed-keyword-set — into the single working sheet Module 8 receives.