Keyword data

`chatgpt`: daily Google search volume

EN-US · Latest daily volume 4,929,772 (as of 2026-11-12)

chatgpt at a glance

Latest daily volume: 4,929,772 (as of 2026-11-12) · Locale: EN-US

vs ~7 days earlier: 1.9%
vs ~30 days earlier: 4.7%
vs ~1 year earlier: -10.7%

Topic groups: AI

In the 12 months to Nov 12, 2026, chatgpt averaged 3,962,824 Google searches a day in the United States.
The busiest day was Feb 4, 2026, with 6,645,415 searches, 1.7× the daily average.
The 30 days to Nov 12, 2026 had 127,456,206 searches, up 6% from the 30 days before (120,437,424).
Tuesday is the strongest day of the week, averaging 4,516,225 searches, 14% above the average day.
The 45-day forecast expects about 4,033,600 searches a day, 5% below the last 30 days' average.

Every figure is calculated from this keyword's daily Google search volume series. API access is available for subscribers. Check another keyword with the free keyword search volume checker.

Overview

Chatgpt is a widely searched AI assistant keyword in the United States. Its latest daily interest reached 4,929,772, with an average monthly volume of 119,738,727. The freshest daily data is from 2026-11-12. Marketers, analysts, and traders use this demand signal to track attention, plan campaigns, and benchmark performance across channels and time.

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Why Is `chatgpt` So Popular?

chatgpt refers to OpenAI’s conversational AI service and brand, the underlying GPT models, and the website/app people use to ask questions and automate tasks. Queries span navigational ("login"), informational (how-to, coding, writing), and commercial/transactional (subscriptions, API). Popularity stems from utility across work and study, constant product updates, integrations, and heavy media attention.

Search Volume Trends

The daily series on this page shows an elevated, stable baseline with sharp, event-driven spikes. Peaks typically align with model releases, feature rollouts, major media coverage, and academic cycles. Recent readings in the millions per day and a very high monthly average indicate entrenched mainstream usage. Short-lived spikes are often followed by higher post-event floors, suggesting durable adoption rather than fleeting hype. Weekday–weekend seasonality is visible; weekdays tend to run higher due to work and education use cases.

How to Use This Data

For Marketing Agencies and Content Creators

Time content drops: Publish during upswings to capture incremental SERP and social lift.
Newsjacking radar: Spikes flag topical angles for briefs, thumbnails, and headlines within hours.
Calendar design: Build weekly cadences around predictable seasonality (e.g., weekday strength).
PR impact: Compare lift vs. baseline the day after a press hit to quantify earned reach.
Attribution clues: Align traffic and CTR with daily demand to refine channel weighting.

For DTC Brands

Budget pacing: Increase bids and budgets into demand surges; taper on troughs.
Conversion forecasting: Use day-level demand as a leading indicator for sessions and CAC.
Creative timing: Launch new ads and offer tests when attention is peaking for faster reads.
Retail signals: Map search interest to help-center volume and staffing on high-demand days.
Partnership planning: Coordinate influencer or affiliate drops to coincide with expected spikes.

For Stock Traders

Attention proxy: Treat search demand as a real-time sentiment gauge for AI exposure.
Event anticipation: Rising momentum can foreshadow product news or coverage cycles.
Post-event drift: Monitor decay rates after peaks to judge durability of narratives.
Cross-asset context: Compare with software usage metrics, developer chatter, or earnings calendars.
Risk management: Use the slope and persistence of demand, not level alone, to avoid chasing headlines.