Open Questions
These are items from the March 2026 training sessions where the transcript is garbled, the source is unclear, or the information contradicts itself. Nothing on this list should be asserted as fact elsewhere in these docs until confirmed with a subject-matter expert.
Other pages link here when they hit an ambiguity rather than guessing.
1. Garbled competitor name near the synthetic-survey discussion
Section titled “1. Garbled competitor name near the synthetic-survey discussion”The transcript references a competitor tool around the topic of synthetic research; the trainer says something like “there are a lot of these — Centigrade, send-it, Centimet” before landing on what sounds like a product name. It is unclear whether this is a real competing platform, a mis-transcription of a known tool, or simply transcription noise from a rambling sentence. (S1, ~line 210)
To confirm: Is there a specific synthetic-survey competitor the trainer was naming? What is its actual name?
2. “Super demo”
Section titled “2. “Super demo””the trainer mentions “super demo” in the context of marketing materials and the resource site: “We have metadata and stuff, so we’ll use the same slide for super demo.” It is not clear whether “super demo” is a named product feature, a specific internal asset, or a general term for a demonstration recording. (S1, ~line 278)
To confirm: Is “super demo” a named internal asset or product feature? Where does it live?
3. Portfolio vs segment vs brand vs the GEICO “profile”: exact relationship
Section titled “3. Portfolio vs segment vs brand vs the GEICO “profile”: exact relationship”Throughout the sessions, the trainer uses “portfolio,” “segment,” “brand,” and “profile” in ways that sometimes overlap. The GEICO example in particular blurs “the GEICO profile I created for you” with “the GEICO segment” and “the GEICO portfolio.” (S1, ~lines 146–148, 269)
To confirm: Is a portfolio always one brand? Can a portfolio contain multiple segments or brands? What exactly is a “profile” in this context?
4. “Prophet” client: real client or mis-transcription
Section titled “4. “Prophet” client: real client or mis-transcription”In the session 2 logo-testing discussion, the trainer mentions “our one of our client, Prophet” who was trying to do logo testing. “Prophet” may be a real client name, or it may be a mis-transcription of “Profitwheel” (the company name) or another client. (S2, ~line 562)
To confirm: Is “Prophet” a real client name? Or is this a reference to Profitwheel or another party?
5. Internal research support contact: exact address
Section titled “5. Internal research support contact: exact address”the trainer mentions an internal research support email as “research-internal@profit.com” or similar, and also references someone named “Paul” or “Paolo” who can answer questions about research types. Both the address and the person’s name are garbled in the transcript. (S2, ~lines 451–453)
To confirm: What is the correct email address for internal research support? Who is the contact person?
6. Compliance acronym “IDSS”
Section titled “6. Compliance acronym “IDSS””In session 1, the trainer describes Consumr.AI’s compliance posture: “We are IDSS, ISO, every every bit compliant of everything because we don’t take first-party data ourselves.” “IDSS” does not correspond to a widely recognized data-privacy or information-security certification. It may be a transcription error for ISMS (Information Security Management System), ISO 27001, SOC 2, or another standard. (S1, ~line 68)
To confirm: What specific certification(s) does Consumr.AI hold? Is “IDSS” a real acronym in this context?
7. Resource-site domain
Section titled “7. Resource-site domain”The transcript references the platform’s external documentation/release-notes site in two different ways: “resource dot configure RTI” and “resource dot consumer dot AI.” These docs currently use resource.consumr.ai as the canonical domain, but this has not been confirmed against the live URL. (S1, ~line 244; S2, ~line 451)
To confirm: What is the correct URL for the resource/release-notes site?
8. “Distribution layer / superimposing” mechanic
Section titled “8. “Distribution layer / superimposing” mechanic”When explaining the audience-panel-brief segment creation method, the trainer says the platform “superimposes” the ACS (census) distribution onto the Meta audience distribution to correct for the fact that Meta covers only 60–70% of the US population. The mechanics are described loosely; it is not clear whether “distribution layer” is a named feature in the UI, a backend calculation, or a conceptual description of the methodology. (S2, ~lines 271–273)
To confirm: Is “distribution layer” a named UI feature? What exactly does the superimposition calculation do?
9. “Audience is learning” and “fallback strategies”
Section titled “9. “Audience is learning” and “fallback strategies””Two small phrases that appear during the twin-creation flow and are not fully explained:
- “Audience is learning”: displayed when a first-party audience is attached during creation. Is this a feature status message? What does it mean for the build?
- “Fallback strategies”: the trainer mentions the platform uses fallback strategies during the 30–40 second brief-to-inputs conversion step. What are these strategies? (S2, ~lines 125, 153)
To confirm: What do these status states mean? Are they user-visible features with documented behavior?
10. 60-researches combination (6 pillars × 10 segments): automated or conceptual?
Section titled “10. 60-researches combination (6 pillars × 10 segments): automated or conceptual?”the trainer describes a scenario: “If my there are 6 pillars and there are 10 segments that cover 90% of US, how many combinations do we have? 60. I need to run a research on 60 researches, and then combine them.” It is unclear whether the platform automates this combination (running all 60 and synthesizing), or whether this is a manual planning exercise the user orchestrates. (S2, ~lines 17–19)
To confirm: Is there a platform feature that combines multi-pillar, multi-segment research automatically? Or is this a manual workflow?
11. Multi-persona output: feature or coincidence
Section titled “11. Multi-persona output: feature or coincidence”During session 1, a session attendee asks about “the three personas that we saw.” the trainer’s response suggests she was looking at reports that happened to be selected together, not a deliberate “three personas” feature output. But it is ambiguous whether there is a formal multi-persona output mode. (S1, ~lines 121–122)
To confirm: Is there a named feature for generating multiple personas simultaneously, or does this happen only when multiple reports are manually selected?
12. Long-term vs short-term memory mapping (intent vs mentions)
Section titled “12. Long-term vs short-term memory mapping (intent vs mentions)”the trainer says the AI twin concept uses “two sets of memories,” intent report and mentions report, with one functioning as long-term memory and one as short-term. The mapping is stated but not made explicit in the transcript. (S1, ~line 92)
To confirm: Which report is long-term memory and which is short-term? Is this mapping documented in the platform?
13. Design tools the trainer referenced
Section titled “13. Design tools the trainer referenced”During a design discussion, the trainer references “Stitch,” “AI Studio,” and “Figma”; a session attendee says she uses Figma; the trainer says “this one just creates designs and you can export to Figma,” and mentions “AI studio” as another option. It is unclear whether “Stitch” or “AI Studio” are internal Consumr.AI tools, third-party tools the trainer personally uses, or references to external products. (S2, ~lines 530–534)
To confirm: Are “Stitch” or “AI Studio” internal or officially recommended tools? Or are these the trainer’s personal tooling choices?