Local events API · Per-location events · Multi-location retail

The Saturday farmers market two blocks from your Phoenix store drives the demand mix. Eight feeds know it. You don’t.

You run marketing across 50-1,500 retail locations. Local events drive per-store demand spikes every weekend. The farmers market fills your Phoenix parking lot. The Thursday concert two blocks from store #229 shifts dinner-rush timing. The Sunday marathon closes the road at two of your six metro stores. Eight event sources (Eventbrite, Meetup, Google Events, Facebook Events, Bandsintown, Songkick, Yelp, Allevents) each know parts of this. Your team cannot scan eight feeds across every store every weekend. The per-location event stream is the integration layer that surfaces what matters per store and feeds your content engine, paid-ad targeting, save-flow engine, and per-location social calendar.

Audit your local-event coverage (Tier 1)Explore Fractional CMO operation

Published May 30, 2026

Why brand-level event awareness misses what your stores need

A single real-world event (the Phoenix downtown farmers market) appears in five or more source feeds with non-identical metadata. Eventbrite calls it one thing. Meetup another. Google Events another. Facebook Events as a recurring event with a different time format. Allevents with yet another title. Your operations team that tries to hand-aggregate the 47 events happening within five miles of store #47 this weekend correctly gives up.

The brand-level marketing calendar does not see local events at all. The per-store team sees them but does not have time to act on them. The franchisee notices the foot-traffic uplift on the Saturday recap and wonders why their per-store ad spend was not raised in advance. The opportunity passes weekly.

The gap is not the event APIs. The gap is the operator-side aggregation + geofence + dedup + relevance classifier that turns 47 raw events near store #47 into 4 actionable per-location signals.

We’ve built the per-location event-ingestion layer for retail operators. Here’s what we know.

You probably already have some of the pieces. Your ecommerce platform tracks demand. Your paid-ad accounts can geo-target. Your GBP-management platform can post per-location. The gap is the upstream event-ingestion layer that feeds them all with relevance-scored per-location events from 8+ sources, plus the per- vertical relevance classifier that decides which 4 of 47 events actually matter for each store.

We have built this for multi-location retail operators across verticals. We know which radius applies per vertical (3-mile day-spa, 5-mile family-restaurant, 25-mile destination retailer). We know which event categories produce the highest demand-uplift correlation per vertical (farmers markets + outdoor festivals for food; concerts + sports for hospitality; conventions for hotel). We bring the per-vertical classifier starter so the first 30 days of ingestion has a usable baseline.

How we get from manual feed-scanning to per-location event stream

Step 1 — Tier 1 AI Readiness Assessment (2-3 weeks). We audit your current event-source coverage. We map which per-location radii apply per vertical. We sample the last 30-60 days of per-location demand-spike events and identify which would have been caught by the 8-feed aggregation. Output: the per-location geofence specification, the per-vertical relevance-classifier starter, and a per-channel handoff plan.

Step 2 — Tier 2 AI Swarm Setup Sprint (4-8 weeks). We build the event-ingestion layer end-to-end: source connectors (Eventbrite, Meetup, Google Events, Facebook Events, Bandsintown, Songkick, Yelp, Allevents, plus city-government + local-newspaper feeds), per-location geofence, canonical-event dedup, per-vertical relevance classifier, content-engine + paid-ad + save-flow + calendar handoffs. Your engineering team receives the running system, all source code, all credentials.

Step 3 — Tier 3 Fractional CMO with AI Swarm ( 6-month minimum, 1-2 days/wk). We operate the daily ingestion cycle in production. Extend classifier coverage per new vertical or per new geography. Tune per-location relevance thresholds. Coordinate per-location event-stream feedback with your operations + marketing leadership. Roll up a monthly per-location event-driven-uplift report.

What changes for you

You stop missing the Saturday demand spike at the farmers-market store. The event landed in your stream Thursday; the per-location ad-spend adjustment and per-location social post ran Friday.

You stop having the franchisee email you Monday asking why their per-store ad budget did not match Saturday traffic. The event stream is the documented input; the budget adjustment is the documented downstream action.

You can answer the question your VP of Operations asks every quarterly review: which event categories produce the highest per-location demand uplift in each vertical, and which stores benefit most. The per-location event-driven-uplift rollup is the answer.

You can open a new market with the event-stream live from day one rather than waiting six months for the per-store team to figure out which feeds matter.

Frequently asked

Why do Eventbrite, Meetup, Google Events, Facebook Events, Bandsintown, Songkick, Yelp, and Allevents not solve this themselves?

Each platform ships a strong local-events API scoped to its own surface. Eventbrite shows you Eventbrite events. Meetup shows you Meetup events. Google Events shows you what Google has indexed. Facebook Events shows you the Facebook graph. Bandsintown + Songkick show music. Yelp + Allevents do partial aggregation. The same Saturday farmers market may appear in five of those feeds with five slightly different titles, five different timestamps, five different venue addresses. None of them ships the multi-source aggregation layer that pulls from all eight (plus city-government and local-newspaper feeds), de-duplicates across sources, geofences per location with a per-vertical relevance classifier, and hands off to your operator content engine. The aggregation is operator-side wiring on top of the per-source primitives.

How does the per-vertical relevance classifier actually decide which events matter for which stores?

Per-location relevance answers: of the 47 events happening within a 5-mile radius of store #47 this weekend, which 4 actually map to your customer demographic + service category + operational impact? A high-end day-spa cares about a wellness expo at the local convention center; it does not care about the youth-soccer tournament at the park. A family-restaurant cares about both. A multi-location operator with 50-1,500 stores cannot maintain 50-1,500 per-store manual classification rules. The classifier is trained on per-vertical relevance signals (event category, venue type, audience-size estimate, day-of-week, time-of-day, per-vertical historical correlation to per-store demand) and produces a per-location per-event relevance score. Per-vertical radius differs (a day-spa cares about a 3-mile radius; a family restaurant cares about 5 miles; a destination retailer cares about 25 miles). The radius is operator-side configuration; the classifier composes on top.

How does dedup work when one event appears across many sources?

A single real-world event (the Saturday farmers market in the Phoenix downtown plaza) appears in five or more source feeds with non-identical metadata. Eventbrite labels it one way, Meetup another, Google Events another, Facebook Events as a recurring event with a different time format, Allevents with yet another title. Dedup joins on (venue coordinates within 50 meters) + (start-time within 30 minutes) + (title cosine-similarity above 0.6) and produces a canonical event-record with the union of metadata across sources. The canonical record is what flows downstream. Operators who ingest without dedup get the same event five times in the content engine, five times in the ad-targeting layer, and five times in the per-location calendar — and the operations team correctly distrusts the data.

What does Completions commit to on Tier 3 if we run this layer in production?

Tier 3 process commitments include: daily multi-source ingestion cycle across all 8 platforms + city-government feeds + local-newspaper feeds; canonical-event dedup with operator-readable cluster reports; per-location relevance score emitted on every event-cluster with per-vertical weight tuning; weekly per-location event-stream report routed to your marketing leadership; per-vertical relevance-classifier retraining quarterly as new event types emerge in your demand data. We commit to the operating discipline. Per-vertical precision is tuned per stack and recorded as engagement KPIs.

Who owns the canonical-event store, the per-location geofence config, and the credentials post-engagement?

Your team owns the canonical-event store, the per-location geofence configuration, the per-vertical relevance-classifier training data, the per-source API credentials, and the downstream-consumer credentials. Completions owns the orchestration knowledge: the multi-source dedup tuning history, the per-vertical relevance-weight tuning, the per-location calendar-integration runbook. At engagement end we transition operational ownership back to your team over 30-60 days with documented handover.

How does the per-location event stream connect to the rest of the marketing stack?

The event stream feeds four downstream consumers. The content engine consumes high-relevance per-location events with positive sentiment and auto-drafts per-location social posts + per-location GBP posts + per-location email-segment campaigns. Paid-ad targeting adjusts per-location Google Ads + Meta Ads geo-targeting + dayparting around event-driven demand spikes (raise bids Saturday morning at the farmers-market store; pause Sunday during the marathon road closures per affected store). The save-flow propensity engine adjusts per-customer per-location offer presentation around event-driven foot-traffic patterns. The per-location social calendar populates with relevance-scored events as scheduling anchors. Four downstream consumers; one event-ingestion contract.

Start with the audit

Tier 1 AI Readiness Assessment (2-3 weeks): we audit your current event-source coverage, sample 30-60 days of per-location demand-spike events, and produce the per-location geofence specification + per-vertical relevance-classifier starter + per-channel handoff plan. If you decide to build, Tier 2 ships the ingestion layer. If you decide to operate it with us, Tier 3 runs the daily ingestion cycle in production. You choose the next step at each gate.