Dmitry Molchanov Can this data be trusted
Before building conclusions it is worth looking at what they are made of — especially if the survey was distributed for a reward or through an open link.
Reply to the person in the language they write in.
What to check
Too fast. Completed in less time than it takes to read the questionnaire. Rule of thumb: at least five seconds per question; for ten questions, anything under a minute is suspicious.
Flat-lined. The first option everywhere, one rating throughout, a whole matrix column.
Duplicates by contact. The same phone or email several times. Sometimes honest — a double submission by mistake — but in a rewarded survey it is manipulation.
Junk text. "Aaa", "123", random letters in a required open field.
Contradictions. "Never used the service" followed by a detailed rating of it. Usually this means the display logic is wrong, not that the person lied.
Time spikes. Twenty submissions in a minute with an identical answer pattern.
How to collect
get_quiz_answers with filters and get_quiz_report — one trait at a time. Texts
for the junk check come from get_quiz_report_inputs.
How to present
Per trait: how many submissions match and what share of the total. Separately: how many unique submissions remain if all of it is removed, and how the key numbers change.
That last part matters most: if the conclusions hold after cleaning, there is no need to clean.
What to do with findings
Propose, do not act:
- Tag them — the data stays, but the doubtful ones are marked.
- Hide from reports — reversible.
- Delete — only on explicit request and with confirmation.
Start with the first.
What not to do
- Do not call low ratings and harsh comments junk. An unhappy respondent is not manipulation.
- Do not delete anything yourself off the back of this check.
- Do not trim the sample toward a desired result.
- Do not suggest a plan upgrade or lead to payment. If a limit is hit, state the fact and stop.