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Lev Mazin

Lev Mazin

Cofounder and CEO, aytm · Supplier-side

Topics Lev shaped

AI & technology, Insights function & business, Methods, methodology & rigor, Researcher craft & identity, Industry, profession & meta

Episodes

What Lev said — indexed claims

  • In a future of fluid, AI-mediated data access, the hardest problem will be distinguishing trustworthy signal from hallucination — and hallucination won't only mean LLM error; it will also mean comparing data that should never have been compared (different timeframes, contexts, countries) when easy access removes the friction that previously forced careful interrogation. — Ep. 24 · 52:00 · cl-lev-solo-020
  • A plausible near-future model of synthetic data is not LLM-generated mock respondents but AI assistants (Siris) acting as synthetic interpreters of real human telemetry — querying our assistants becomes more reliable than querying us directly, because they will know our likely behavior better than we can articulate it. — Ep. 24 · 42:50 · cl-lev-solo-016
  • Detecting low-quality respondents requires building smart models that triangulate over many signals (the 'sum of all factors' or digital body language) rather than reaching for simple binary rules; data quality is a perpetually multifaceted problem and no blunt instrument will durably solve it. — Ep. 24 · 39:10 · cl-lev-solo-014
  • Crude defenses against AI-generated survey responses (e.g., blocking copy-paste) harm honest, careful respondents — non-native English speakers checking grammar in Word — more than they catch fraud; the right response is multi-signal triangulation, not blunt instruments. — Ep. 24 · 37:55 · cl-lev-solo-013
  • Newcomers entering consumer insights today should make curiosity, hands-on tool experimentation, and LLM literacy their daily practice — knowing both the powers and the limitations of AI tools — while learning the proven methodologies and rules of thumb from those who came before. — Ep. 24 · 46:50 · cl-lev-solo-017
  • The next major game in consumer insights will be reviving the dormant data already accumulated inside large corporations — past studies that lacked the tools to be searchable, comparable, and actionable will finally become accessible, dramatically reducing duplicative new research and surfacing latent value. — Ep. 24 · 49:32 · cl-lev-solo-019
  • Sophisticated research methodologies (MaxDiff, conjoint, perceptual mapping) were historically gatekept by a small army of specialists; bringing them to a DIY platform liberated them for practitioners who couldn't otherwise access them. — Ep. 24 · 18:35 · cl-lev-solo-005
  • The three most common respondent complaints about panel companies — being lied to about incentives (especially being screened out after long surveys with no compensation), enduring overlong convoluted surveys, and privacy breaches — are predictable, addressable, and were systematically designed against in PaidViewpoint. — Ep. 24 · 30:10 · cl-lev-solo-009
  • aytm's core insight was reframing market research as a two-sided marketplace — connecting people with questions to people with answers — rather than as a survey-tooling business; this required building the panel community before launching the product. — Ep. 24 · 12:10 · cl-lev-solo-003
  • There is a meaningful difference between being a panel provider and a panel company: panel companies treat respondents as a commodity to extract ROI from before churn, while a panel provider treats respondents as partners in an ecosystem of trust. — Ep. 24 · 28:20 · cl-lev-solo-008
  • The most precious commodity for any human being is the life of their time; respondents who spend minutes or hours on a survey in exchange for nothing are being demeaned, and panel platforms that allow this are eroding the ecosystem they depend on. — Ep. 24 · 30:40 · cl-lev-solo-010

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