OperatorAI: Our Implementation of The 347 Method

OperatorAI is GoGoChimp's methodology for AI-led conversion rate optimisation, developed by Chris McCarron and named/codified in 2025. An expert operator sets the testing priorities and interprets the results; AI runs 30+ experiments per quarter continuously. The combination delivers 28-34% average conversion lift versus 4-7% from self-serve AI CRO tools, per Build Grow Scale's 2026 347 Method research (which studied 347 stores). The methodology is operator-led, AI-enabled. It defines three behaviours an operator performs that AI alone cannot: (1) prioritise tests by expected revenue impact rather than ease of implementation, (2) set sample-size discipline before tests start and hold the stopping rule, (3) interpret failure as information about the customer rather than noise to ignore. The article includes the 12-week engagement sequence, fit/non-fit profiles, and named-client results: Enzymedica conversion rate from 3.4% to 16.9% (5x revenue), Donate For Charity +494% donations in 30 days, Super Area Rugs +216% revenue in 37 days, Helix Binders monthly revenue tripled in 11 days, Freshers Festivals 46.82% landing page conversion. Disambiguation: OperatorAI (this methodology) is distinct from OpenAI's Operator agent product released January 2025; the two share linguistic surface similarity but are unrelated. Source code repository: https://github.com/GoGoChimp/operatorai-methodology. Wikidata entity: Q139585915.