The Pickion Signal Score: how we choose and rate products
Every product on Pickion goes through the same process: an AI-assisted screening model built by Pickion reads the public signals around a product — buyer reviews, complaints, refund mentions, offer terms and marketplace data — and a human reviewer checks every result before anything is published.
Last updated: October 13, 2026 · Version 1.0 (experimental)
5pillars
In short
We score every product on five pillars — buyer sentiment, complaint & refund signals, offer transparency, product substance and market traction — using publicly available data. The AI does the heavy reading; a human makes the call. Commission size is never part of the score.
1. How we choose which products to review
We don’t review everything. Each candidate product passes through a four-stage screening funnel before it earns a full review:
DiscoveryCandidates come from the ClickBank marketplace, search demand (Google Trends) and reader suggestions.
Eligibility gatesMinimum money-back guarantee of 30 days, an identifiable seller with working support contact, enough public feedback to analyze, and no medical “cure” claims.
AI-assisted signal scanOur model collects and classifies public reviews and complaints, reads the sales page for red-flag claims and calculates a preliminary Signal Score.
Human deep-diveOnly products that pass the scan get a full review. A human checks every data point, the offer and the refund terms, and writes the final verdict.
Products that fail the gates or score below 2.5 in the preliminary scan are not featured. If a product we already cover drops below that line, we update the review to say so.
2. The five pillars of the Pickion Signal Score
Each pillar is scored from 0 to 5 using the KPIs below. All sources are public, so anyone can check our work.
Buyer sentiment
25%
What real buyers say after purchase — not the testimonials on the sales page.
Net Sentiment Ratio — positive minus negative mentions, divided by all classified mentions.
Average public rating on independent platforms, weighted by number of reviews.
Recency — feedback from the last 12 months counts double.
Sources: Trustpilot, Reddit, YouTube comments, independent forums and review sites.
Complaint & refund signals
20%
How often buyers run into problems, and how hard it is to get money back.
Complaint Index — complaints per 100 public reviews mentioning billing, access, delivery or misleading claims.
Refund Friction Rate — share of complaints saying a refund was denied, delayed or hard to request.
Unresolved complaints on consumer-protection platforms.
Sources: BBB (Better Business Bureau), Trustpilot, Reddit, consumer forums.
Offer transparency
20%
Whether you know exactly what you’re paying for before you pay.
Guarantee length & clarity (60 days scores higher than 30).
Upsell count and whether recurring charges are clearly disclosed.
Claim Risk Score — AI scan of the sales page for exaggerated income or health claims, fake scarcity and fake countdown timers.
Sources: the official sales page and checkout, ClickBank product terms.
Product substance
20%
Whether the product delivers what it promises.
Promise-vs-delivery match — what’s advertised compared with what buyers report receiving.
Completeness & format — usability, organization and access.
Freshness — signs that content is maintained and updated.
Sources: official product information, buyer reports, product previews.
Market traction
15%
Whether the product has a real, sustained track record — a supporting signal, never the main one.
ClickBank Gravity band — a public marketplace indicator of recent sales activity (see table below).
Time on market — products sold for years with stable feedback score higher.
Search interest trend over 12 months (Google Trends).
Sources: ClickBank marketplace, Google Trends, Wayback Machine.
How ClickBank Gravity is converted into a score
Gravity reflects how many different affiliates recently earned a sale from a product. It shows demand, not quality — so we cap its influence and slightly lower the score for extremely high values, which often signal aggressive promotion rather than happy customers.
Gravity
Traction sub-score
How we read it
Below 5
1.5
Little recent sales activity or a brand-new product
5 – 20
3.0
Niche but active
20 – 60
4.0
Established demand
60 – 150
4.5
Strong, proven demand
Above 150
4.0
Very high promotion pressure — checked extra carefully
Health “cure” claims or guaranteed-income claims → overall score capped at 2.9.
Public warning from a regulator (such as the FTC or FDA) → product excluded.
6. What the AI does — and what it doesn’t
The AI model does
Collect and organize public reviews and complaints
Classify each mention by sentiment and complaint type
Flag risky claims on sales pages
Calculate a preliminary Signal Score
The AI model doesn’t
Publish anything without human review
Write fake reviews or testimonials
Decide the final verdict on its own
Know or consider our commission
A human reviewer reads a sample of the source material behind every pillar, corrects misclassifications and can adjust a pillar score by up to ±0.5 with a written reason.
7. Limitations (why we call it experimental)
Refund rates aren’t public. Sellers and marketplaces don’t publish them, so we use complaint and refund-friction signals as the closest public proxy.
Public reviews have bias. Unhappy buyers are often louder, and some reviews online are not genuine. We filter duplicates and suspicious patterns, but no filter is perfect.
Gravity measures sales activity, not satisfaction. That’s why it carries the lowest weight and is capped.
Offers change. Prices, bonuses and terms can change at any time. Always check the official site before buying.
The Pickion Signal Score is an original methodology developed by Pickion. It is not a scientific study or a certification, and it is not affiliated with or endorsed by ClickBank or any other platform mentioned. We refine it as we learn and publish every change below.
8. Changelog
v1.0 — October 2026: first public version. Five pillars, Gravity bands, confidence levels and red-flag caps.