Daily Google Search Volume for coffee near me

Overview

Coffee near me reflects high-intent local discovery, especially on mobile in the United States. On 2025-08-27, the keyword recorded 404,343 searches, contributing to an average of 13,446,525 monthly. Use this page’s daily granularity to time campaigns, staffing, and inventory to peak demand in neighborhoods. Optimize creatives, offers, and local listings accordingly daily.

Why Is coffee near me So Popular?

Coffee near me is a local-intent query combining a product category (“coffee”) with proximity (“near me”). It signals immediate in-person purchase intent: finding a café, drive‑thru, or espresso bar close by, often on mobile or via voice assistants. The intent is primarily transactional/commercial. It’s popular because coffee consumption is habitual, phones are location-enabled by default, and search surfaces instant maps, hours, ratings, and offers that shorten the path from intent to visit.

Search Volume Trends

On this page, daily volumes sit in the high six figures, while the average month reaches into eight figures—evidence of durable, year‑round demand. The daily series typically shows pronounced weekday morning spikes (commute and workday routines), softer weekends, and seasonal lift in late summer/fall and winter. Short, sharp pulses often align with seasonal beverage launches, promotions, holiday travel, and weather events. Use the zoom controls to inspect outliers and confirm whether spikes revert or reset the baseline.

How to Use This Data

Use daily granularity to plan precisely. Focus on when and where demand concentrates, not just how much. Activate, measure, and iterate around observed peaks and troughs.

For Marketing Agencies and Content Creators

  • Schedule ads and content to the exact hours/days with local peaks; tailor creatives to “open now,” “drive‑thru,” and seasonal drinks.
  • Sync Google Business Profile updates (posts, offers, photos) to high‑volume windows to maximize visibility in map packs.
  • Build editorial and influencer moments ahead of recurring seasonal surges; validate lift by comparing adjacent days.
  • Localize landing pages and CTAs by city/ZIP where daily demand concentrates.

For DTC Brands

  • Align retail co-op promotions and sampling with peak neighborhood demand to increase store traffic and sell-through.
  • Forecast staffing and inventory for owned stores or partners using daily curves; pre-position seasonal SKUs before spikes.
  • Trigger dynamic offers or limited-time bundles when demand exceeds baseline; pause when demand decelerates.
  • Optimize last‑mile delivery and click‑and‑collect readiness on expected surge days.

For Stock Traders

  • Track week-over-week and year-over-year daily momentum as a nowcast for foot traffic to major coffee chains.
  • Flag event-driven spikes around seasonal launches and holidays; compare magnitude and decay to prior seasons.
  • Combine DSV with weather/mobility data to build short-term signals; monitor regional divergences ahead of comps commentary.
  • Use reversions from spikes to baseline to gauge sustainability of promotions and potential impact on near-term results.