ChatGPT — OpenAI's conversational AI assistant

ChatGPT is OpenAI's conversational AI assistant — the most-used AI product on the internet and the de facto reference point for the entire LLM category.

What ChatGPT actually is

ChatGPT is OpenAI's conversational AI product, launched on November 30, 2022 and reaching 100 million users within two months — the fastest consumer product adoption in history at that time. OpenAI was founded in December 2015 by Sam Altman, Elon Musk, Ilya Sutskever, Greg Brockman, and others; it became a capped-profit company in 2019 and received a $1B investment from Microsoft that year, expanded to ~$13B by 2023. By 2026, OpenAI is valued at $150B-$300B in private markets, generates approximately $15B-$25B in annual revenue, and has 400M+ weekly ChatGPT users.

ChatGPT's underlying models in 2026: GPT-4, GPT-4 Turbo, GPT-4o (omni — text, voice, vision in one model), GPT-4.5, and GPT-5 (released 2025). The models are accessible via the ChatGPT consumer product (free tier with GPT-4o-mini, ChatGPT Plus at $20/month with GPT-4o, ChatGPT Pro at $200/month with extended capabilities and o1/o3 reasoning models), via the OpenAI API for developers, and via Microsoft's Azure OpenAI Service for enterprise.

Product surface area

CHATGPT CONSUMER UI + APPS CHATGPT SEARCH AI-POWERED SEARCH API DEVELOPERS + ENTERPRISE OPERATOR AGENTIC + COMPUTER USE FIG. 01 RGM® · BLUEPRINT

FIG. 01 — ChatGPT product surface

ChatGPT's surface in 2026: the consumer chat product (web, iOS, Android, macOS, Windows apps), ChatGPT Search (the search-engine product launched 2024), Custom GPTs (user-created assistants), GPT Store (marketplace for custom GPTs), Operator (the agentic computer-use product launched January 2025), Voice Mode (low-latency conversational voice), Vision (image upload and analysis), DALL-E 3 image generation, Sora video generation, Whisper transcription, Advanced Data Analysis (Python-in-chat for data work), and the underlying OpenAI API for developers.

How marketers actually use ChatGPT

ChatGPT in marketing in 2026 is most-used for: content drafting and ideation (briefs, outlines, headline variants — note: Google Helpful Content updates have penalized unedited AI content, so the workflow is AI-draft then human-edit), research and competitive analysis (synthesizing publicly available information about competitors, categories, and trends), data analysis via Advanced Data Analysis for CSV exports and ad-hoc analytics, copy variants for paid creative (10-20 hook variants per concept in seconds), customer-research synthesis (interview transcripts, support tickets, review summaries), and code generation for marketing engineering work (GTM tag templates, BigQuery SQL, dbt models).

What ChatGPT is NOT good for in marketing: writing finished long-form content without heavy editing (Google penalizes thin AI content), competitive intelligence that requires real-time data (use ChatGPT Search or Perplexity instead), and creative work that requires deep brand-voice understanding (the output is generic without extensive prompting and brand-voice fine-tuning).

RGM Experts Say

Most teams either use ChatGPT not enough or way too much. The teams using it not enough are still drafting from scratch — leaving 4-8x productivity on the table. The teams using it too much are shipping unedited AI content and watching their SEO rankings collapse on Helpful Content updates. The right pattern: AI-draft, human-edit, AI-iterate on hook variants and headlines, human-finalize. The human-in-the-loop is non-negotiable for anything that ships.

ChatGPT Search — the AI search competitor

ChatGPT Search launched in October 2024 and now handles 300-500M daily queries — making it the second-largest AI search product after Google AI Overviews. For brands, ChatGPT Search is a meaningful citation channel — see our Generative Engine Optimization Ultimate Guide for the full discipline. The crawler is OAI-SearchBot; the retrieval-and-synthesis architecture is similar to Google AI Overviews but with different ranking weights and citation behavior.

Tracking ChatGPT Search citations is harder than tracking Google rankings — OpenAI doesn't expose query-level citation data to brands. The pragmatic measurement: daily monitoring of priority queries via manual or scripted query execution, plus referral traffic monitoring from chat.openai.com referrers in GA4.

API and developer use

The OpenAI API powers most third-party AI applications and is the foundation for most marketing-tech AI features built since 2023. API pricing in 2026 varies by model: GPT-4o costs roughly $2.50/$10 per million input/output tokens; GPT-5 costs higher for the higher-capability tier; o1 and o3 reasoning models cost meaningfully more for long-thinking queries. For marketing operations, the API enables custom AI features in CRMs, lifecycle platforms, and analytics tools — most modern marketing tools have OpenAI integrations.

Enterprise considerations: data sent to ChatGPT API by default is not used for model training (per OpenAI's API terms since 2023), but data sent to the consumer ChatGPT product may be. Enterprise customers typically use ChatGPT Enterprise (custom plan with data residency, SSO, admin controls) or Azure OpenAI Service for stronger data governance.

ChatGPT vs Claude vs Gemini vs Perplexity

The 2026 LLM landscape: ChatGPT (OpenAI) — broadest user base, strongest brand recognition, deep ecosystem of integrations and custom GPTs. Claude (Anthropic) — preferred by many developers and writers for output quality and longer context; strong on coding and analytical tasks. Gemini (Google) — integrated into Google Workspace, Search, and Android; strongest multimodal capabilities. Perplexity — research-oriented AI search with strong citation discipline. Meta AI — integrated into WhatsApp, Instagram, and Messenger with massive reach but conversational rather than productivity-focused.

The right tool depends on use case. For marketing operations specifically, we typically run a multi-LLM stack — ChatGPT for ideation breadth, Claude for long-form drafting and analytical work, Gemini for Google Workspace integration, Perplexity for research, with Operator and Computer Use products for agentic workflows.

RGM Experts Say

Most marketing teams pick one LLM and standardize on it. The brands compounding AI productivity are running multi-LLM stacks — different models for different tasks, with an internal documentation layer that helps the team route work to the right tool. The cost is trivial (each subscription is $20/month per seat); the productivity uplift is meaningful because each model has distinct strengths and weaknesses.

How we work with this technology

We use the tools that fit the job. If our approach feels aligned with your business, apply for an engagement.