Competitor media mix map

Tools it calls

Each tool's price and track record across every agent today. Empty means the call worked and found nothing.

# Competitor media mix map

For one competitor domain. Podcast placements and Meta ads are the inputs; channel traffic is the outcome. Lining up their dates is the point.

## 1. Podcast spend

1. Resolve the domain with @[Particle · Company directory](alexandria:particle/companies/search) (`domain`): keep the **company slug**.
2. Get its podcast footprint with @[Particle · Company advertising profile](alexandria:particle/advertising/company/overview): sponsors (brands), shows, placement volume, host-read mix.
3. Chart placements by month for the last 12 months with @[Particle · Ad placements over time](alexandria:particle/advertising/timeseries) (`company_id` = the slug, `interval=month`). Mark **flight starts** and peaks.

## 2. Meta spend

4. Read the Meta side with @[Upspring · Advertiser by domain](alexandria:upspring/advertisers/by-domain): spend grade, creative fingerprint, top ads. Note whether podcast offers (codes, URLs) also appear in Meta ads.

## 3. What moved

5. For the month before and the month after each podcast flight start, read @[Similarweb · Marketing channel shares](alexandria:similarweb/channels/share) (one call per month). Direct and branded search rising after a flight is the podcast signature; paid social rising is Meta.
6. Read @[Similarweb · Traffic and engagement](alexandria:similarweb/web/traffic) with `metrics=visits,unique_visitors` for the same months to size the change.

## Write the map

- **Timeline:** months as columns; podcast placements, Meta posture and channel shares as rows.
- **Read:** which channel's ramp preceded which traffic change, with the caveat that timing is correlation.
- **Implications:** where to contest and where to avoid.
- **Sources:** cite each number to its capability and month. Say what could not be found rather than guessing.

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