NEWS & COMPANY UPDATES
Product moves, new research and useful ideas. The short version here, the full story at the source.
From Subconscious.ai · Show all companies
Subconscious describes structuring a workshop around questions that can be tested. The approach turns disagreements into study options instead of letting the most senior opinion settle the discussion.
The company describes screening paywall copy with modeled reader groups before using live traffic. The proposed workflow compares segment reactions and then takes selected variants into an actual experiment.
Subconscious looks at email order, tone and calls to action through simulated audience reactions. The article positions the exercise as preparation for a real welcome campaign.
The company describes defining a buying group and varying specific elements of an offer. Its guide emphasizes controlled comparisons rather than asking a model for a broad marketing recommendation.
The company introduces interactive persona simulation and the questions teams can bring to it. It separates the ability to hold a convincing conversation from evidence that the answers fit a research task.
Subconscious examines the different priorities inside a buying committee. It proposes looking at role-specific objections and trade-offs rather than treating a group discussion as one unified buyer.
Subconscious describes a simulated replication of a published climate-policy study. Its account compares modeled responses with the original research, providing a worked example of its evaluation approach.
Subconscious discusses human review and escalation before AI-generated findings enter a client presentation. It recommends setting the rules while designing the workflow, rather than after a disputed output.
The company compares research approaches by the decision being made. Its guide explains how an exploratory question can move from simulation into a recruited study with a sharper brief.
Subconscious uses browser-based Bayesian modeling to separate software architecture from research quality. Its point: where a model runs does not establish whether the study can answer the decision question.
Subconscious discusses Bayesian approaches to marketing questions, including attribution and customer value. It explains why uncertainty ranges still depend on assumptions and do not automatically establish cause and effect.
Subconscious sets out what a buyer should be able to inspect in a vendor's probability model. The focus is on tracing assumptions through to outputs and understanding what evidence tests those assumptions.