Yes, we find your respondents.
Flickly instantly provides you with access to feedback from over
65 million people globally.
From audience specification to validated sample.
Flickly reaches 65M+ respondents worldwide.
Every response passes four layers of validation.
Studies are fielded and reported within 72 hours.
Two panel sources are held to a single standard.
Our own panel is verified by WhatsApp OTP and email, with device and response-pattern monitoring applied throughout, and is complemented by trusted, leading verified panel partners who profile respondents and screen for duplicates and fraud at panel level.
Weekly enrichment campaigns keep purchase recency, habit frequency and category intent up to date.
We recruit your audience
Share your audience specification and Flickly manages the study end to end: sourcing respondents, drafting the screener, fielding the study, and maintaining quotas throughout. No panel contract is required on your side.
This is recommended where the audience is not directly reachable, or where a read from your own customer base would introduce bias.
Where respondents come from
Flickly’s proprietary panel and verified partners
In addition to our own proprietory panel, we partner with leading verified panel partners globally - instantly giving you access to 65M+ people globally.
Continuous enrichment
Weekly enrichment campaigns keep profiles current, covering purchases made in the last three to six months, habit frequency, and category intent across beauty, fitness, fashion, and hobbies.
Revalidation per study
Before your study opens, we re-ask the key screening questions and match the answers against each respondent’s profile and panel-level data. Any inconsistency results in disqualification and blacklisting.
Can we reach the right audience, and do they qualify?
We build the target audience customised to your brand's requirement. Every respondent is screened against the study’s requirements before their answers count.
Build your target audience
Set the filters and we hold them as quotas across the study, so the shape of the sample does not drift while it fields.
Selected audience
Your specification becomes the quota plan the study is fielded against.
Qualified respondents
Answers are revalidated against profile and panel data. Inconsistencies are disqualified.
Survey
Only qualified respondents reach your questionnaire.
Screener
Study questions and quotas decide who continues and who is closed out.
Data Quality Engine
Every response passes through quality checks before it becomes part of the final dataset. Six checks run on every study, in every market.
IP address validation
IP verification confirms the stated location and prevents repeat entries from the same device.
Duplicate detection
Respondents are de-duplicated across partner panels and our own, so one person counts once per study.
Attention and trap questions
A question with one known correct answer is placed mid-survey. Failing it removes the response.
Response-time monitoring
Completion times are monitored, and respondents moving faster than the questions can be read are removed.
Logic and consistency checks
Answers are checked against one another. Contradictions, including uniform responses across a grid, disqualify the response.
Suspicious response detection
Device and response-pattern monitoring flags behaviour that does not look like a real respondent.
What that means for your data
Never enters your study
Duplicates, respondents flagged for fraud, and anyone failing revalidation are disqualified before the survey opens and blacklisted thereafter.
Pulled during fielding
Failed traps, speeding, contradictions, and suspect device or IP patterns are removed during fielding, and the sample is refilled.
Marked in your export
Borderline responses remain in the dataset with the reason recorded, alongside time in survey, check outcomes, and respondent source, so your team can decide whether to include them.
And, Decision Intelligence
Decision Intelligence turns qualified consumer responses into decision-ready insights, so what you get back is a decision rather than a dataset.