Trust
Quality & privacy
Panel data is only worth what its provenance is worth. Consent is the condition of collection, and every quality decision happens in the pipeline — before the data reaches you, with the scores attached.
Consent first
The entry condition, not the disclaimer
Behavioral data collected without informed consent is a liability wearing a dataset's clothes. Everything below is a property of how collection works, which is the only version of a privacy commitment that holds up when someone audits it.
- Explicit opt-in
- Consent is specific to behavioral collection and given in plain language — not inherited from a terms update.
- Pseudonymous by construction
- A panelist is an opaque identifier from the moment of capture. There is no later step where identity is removed.
- No message content
- The accessibility layer is read for structure and interaction, not for the contents of private messages. Network metadata is metadata: no payloads.
- No credentials
- Authentication fields are out of scope for collection, by design rather than by filter.
- Withdrawal stops collection
- A panelist can leave at any point, and collection ends when they do.
Quality in the pipeline
Quality applied after delivery is a report. Quality applied inside the pipeline is a property of the data. Each of these runs on every record, continuously, before anything reaches a feed.
01
Dedupe
The same act observed twice — once on the device, once on the wire — is one event, not two. Corroboration should raise confidence, never inflate counts.
02
Bot & fraud defense
Emulators, automation and implausible behavioral signatures are identified and removed inside the pipeline. Panel fraud is a supply problem, so it is treated as one, continuously.
03
Calibration
Metered behavior is calibrated against known reference points, so a figure is comparable across markets rather than only internally consistent.
04
Weighting
Panel composition is corrected toward the population being described. The weights travel with the data rather than living in someone's spreadsheet.
05
Quality scores
Every record carries the quality signals behind it, so you can filter on them yourself instead of trusting a single upstream pass/fail decision.
Monitors and SLAs
A continuous feed fails differently from a fieldwork project. Nobody notices a market that quietly stopped reporting until a quarterly number looks strange, so the monitors watch for exactly that: volume against its own baseline, composition drift, delivery freshness and schema stability.
Delivery is covered by an SLA rather than best effort, and when something is off you hear it from us before you find it in the data.
- Volume and composition watched against baseline, per market
- Freshness monitored on every delivery surface
- Schema stability enforced — a column does not change meaning
- Quality scores delivered with the records, not summarized away
- Contractual delivery SLAs, with notification on our side first
Right now
Wherever your panel is, it is the middle of someone’s day and the middle of someone else’s night. The Behavix platform is live 24/7 across all time zones, with dedicated infrastructure for each region.
- Los Angeles
- São Paulo
- London
- Berlin
- Mumbai
- Singapore
- Tokyo
- Sydney
Reviewing us as a vendor?
Procurement and privacy reviews ask sharper questions than a product page should try to answer. Ask us directly and we will walk your team through the consent flow, the data handling and the contractual terms.
Talk to us