OpinionReady

Data quality

Recruitment sources, ranked by how much fraud they carry

Where a panel member came from predicts their behaviour better than almost anything you can measure once they are inside.

People checking their phones while waiting in a public lobby

Outline. Each heading below carries one line saying what the section has to establish. Expand each into two to four paragraphs, put at least one number or worked example in the piece that nobody else could publish, then delete this note.

Fraud is not evenly distributed across a panel. It concentrates by acquisition channel, and the channel is known at signup — long before any behavioural signal exists.

The channels, and what each one selects for

Organic search, referral, paid social, incentive affiliates. Describe the person each attracts.

Affiliate traffic is where the concentration is, and why

Payment per signup creates the incentive. Say it without pretending the channel is unusable.

Cost per member against cost per usable complete

The cheap channel stops being cheap once removal rates are priced in. Show the arithmetic shape.

What changes if you screen harder at the door

Front-loading verification versus catching it later, and what each does to conversion.

Why the split is almost never published

It is the question that separates suppliers, which is exactly why it is answered vaguely.

Publishing ours

State the intent and the caveat: the number has to come from the platform, not from a claim.

Filed under Data quality

Who wrote this

OpinionReady Method Desk — Panel operations and data quality

The people who run the exchange day to day — supply operations, quality review and the payout queue. These notes come out of work we had to do anyway, written down because the same questions keep arriving from buyers and from members.

Written from our own operating record: the screening calls, field estimates and payout runs described here are ones we make on this exchange, not secondhand summaries of research done elsewhere.

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