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Exclusive Methodology
Sorftime isn't just a data API — it's a recommendation engine built on 9 years of seller data and proprietary algorithms. These features don't exist in any other marketplace intelligence tool.
Every traditional seller tool works the same way:
Filters: minPrice ≥ $10 AND maxReviews ≤ 500 AND minRating ≥ 4.0
Problem: A $9.99 product with 800 sales/month and 4.6 stars? Deleted. Invisible.
Sorftime uses composite index full-ranking. Every product scores on every dimension. A product that's "weak" on one dimension but outstanding on others still surfaces. No product gets eliminated by a single threshold. The seller sees the complete ranking and makes their own decision.
This sounds simple — it's not. Building stable composite indices that work across 40+ marketplaces and millions of products requires proprietary weighting models calibrated against real seller outcomes.
What it is: A composite recommendation score that ranks products by "hidden profit potential" — how likely a product is to deliver strong margins with low entry barriers, low ad competition, and manageable review thresholds.
What it isn't: A per-dimension breakdown calculator. HPI is a relative recommendation score, not an absolute metric. Higher = better overall profile. The algorithm looks at what traditional filtering misses.
Why it's exclusive: Most tools show you what you asked for (filter by price, sort by sales). HPI shows you what you didn't ask for — products that are profitable but invisible under conventional filtering rules. Think "low reviews but solid sales," "low ad spend but healthy margins," "mediocre rating but high repeat purchase rate."
Where: potential_product MCP tool → Invisible Profit methodology card
Example: A non-slip yoga mat at $29.99 with 4.6 stars, only 13 reviews, but 106 units/month — HPI 13.44. Low review barrier, low ad competition, strong margins. Traditional tools would filter this out because "reviews < 50." HPI catches it.
What it is: A multi-dimensional composite score for evaluating low-price marketplace opportunities on Amazon Haul. Assesses 12 dimensions across demand, competition, costs (capital/logistics/operations/after-sales), and margin potential — compressed into a single "Low Price Market Index" score.
Why it's exclusive: Most tools treat "low price" as a simple price filter. The Low Price Index evaluates whether a low-price category is viable as a business — factoring in not just demand and competition, but the full cost structure (logistics, operations, returns/after-sales) that determines whether thin-margin products can actually be profitable.
Key dimensions: Market demand · market trend · seller profile · monopoly/competition · market volatility · new product opportunity · capital cost · logistics cost · operations cost · after-sales cost · margin headroom
Where: Multi-dimension Market Selection → Low Price Index mode
What it is: Identifies products selling at significantly different prices across Amazon and Walmart — arbitrage opportunities that exist because few sellers operate on both platforms simultaneously.
Why it's exclusive: Sorftime is one of the only platforms with deep data coverage on both Amazon (14 sites) and Walmart (US). Cross-platform price gap analysis requires consistent product matching across marketplaces — a data engineering problem most tools can't solve.
Where: Cross-Platform Gap methodology card → Cross-Platform Overview
Each card is a weighted composite index that full-ranks opportunities. No hard thresholds. No blind spots.
| Category | Cards | Exclusive Indices |
|---|---|---|
| Comprehensive (8) | Market Panorama, Competitor Deep-Dive, Keyword Strategy, Blue Ocean Finder, Listing Audit, Review Mining, Pricing Position, Traffic Structure | Hidden Profit Index ⭐, Pain Point Severity Index |
| Tactical (12) | Invisible Profit, Low-Review Winner, Brand Gap Entry, Keyword Scatter, Lightweight Profit, Seasonal Position, Variant Gap, New Product Burst, FBM Arbitrage, Cross-Platform Gap, Poor Listing Grab, Price Band Sweetspot | Product Potential Index ⭐, Cross-Platform Price Gap Index ⭐, Brand Monopoly Vulnerability Index |
See Methodology Overview for the full breakdown.
| Traditional Tool | Sorftime |
|---|---|
| You set filters → tool shows matches | You describe your goal → AI agent applies methodology cards → scores everything |
| Hard thresholds hide borderline products | Full-ranking — you see every candidate ranked |
| Single-dimension sorting (by sales, by price) | Multi-dimension composite scoring |
| You figure out the analysis strategy | 20 pre-built analysis frameworks, each with weighted dimensions |
| "Here's the data" | "Here's the data + here's what it means + here's what to do next" |
Test date: 2026-08-03 | Data: Amazon US "kitchen storage" | Tool: sorftime-seller-agent
potential_product(search_name="kitchen storage", price_min=15, price_max=45,
month_sales_volume_min=200)
This tells the HPI engine: "only show me kitchen storage products between $15-45 with >200 monthly sales."
Result: 20 products returned. Looks fine. But:
| What was lost | HPI Rank | Price | Sales | Reviews | Killed by |
|---|---|---|---|---|---|
| 3-Tier Under Sink Organizer, Metal Pull-out | #1 | $59.99 | 1,872 | 90 | price_max=45 |
| Berglander Vertical Dish Rack 14" | #7 | $8.99 | 444 | 73 | price_min=15 |
Damage: The price_max=45 filter eliminated the #1 highest-HPI product. The price_min=15 filter eliminated the #7 HPI product. The seller never saw either. Both are genuine hidden gems — one "premium but worth it," one "cheap but high volume."
potential_product(search_name="kitchen storage", NO filters) → TOP20 by potential_index
→ Cross-reference 4-tier risk filter (exclude hard-blocked categories only)
→ Then analyze: which products would hard thresholds have eliminated?
Result: The seller sees ALL 20 products ranked by HPI, plus a clear annotation: "These 2 products ranked in the TOP10 but would be invisible to threshold-based tools. Here's why HPI sees value in them."
The Hidden Profit Index exists precisely to find products that traditional filtering kills. Every hard threshold you add before HPI ranking directly contradicts the methodology. The correct sequence is:
1. Full HPI ranking (no filters)
2. Safety exclusion (risk categories only)
3. Detail analysis (why does this product rank high?)
4. Flag what thresholds miss (show the seller what they wouldn't have seen)
Never: price > X AND reviews > Y AND sales > Z before HPI ranking.
- Methodology Overview — All 20 cards with descriptions
- 25 Sourcing Strategies — Complete product sourcing playbook
-
Amazon Overview — Key tools including
potential_product - Use Cases — Real seller scenarios using exclusive indices
- Glossary — Terminology reference
- 🆕 Closed-Loop Selection ← Full pipeline
- 📖 Case Study: Water Bottle ← Real data example
- Loop & Goal Templates ← 58 automation recipes