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Michael Paul Kish Google Ads Strategy & Creative Analysis

Relevant suggestions appear first; direct submit searches by the entered name and shows the results
Preview mode shows 10 results on the first screen, with visible dates capped at 2026-05-20. This search actually matched 9 results. Upgrade to membership to view the full set.
Remaining guest searches today: 3 / 6
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Advertiser Info
NameCountry
Michael Paul Kish US
How To Extract Value From This Page

This page can be analyzed from three angles:

1. If you notice the same landing domain appearing repeatedly, search that domain in the landing-domain filter to see how many ads Michael Paul Kish runs to it. In most cases, the more ads a domain receives, the higher the ROI is likely to be, and the more likely it is to be a core offer for Michael Paul Kish.

2. Filter by recent activity to find ads that were still active within the last three days. That usually means the ad is still generating profit for Michael Paul Kish.

3. Filter by campaign duration to identify ads that have survived for more than 30 days, 90 days, or even a full year. Combined with the two signals above, this helps you quickly judge both profitability and stability.

Ad Creatives
9
Preview Creative ID Format Stability First Seen (Beijing Time) Last Seen (Beijing Time) Landing Domain
CR12151375264013615105 Image
479 days
Very Stable
2025-01-27 2026-05-20 google.com Detail
CR07703592275707691009 Image
479 days
Very Stable
2025-01-27 2026-05-20 AI parsing service failed Detail
CR07538946800359571457 Image
479 days
Very Stable
2025-01-27 2026-05-20 google.com Detail
CR09864798679225860097 Image
479 days
Very Stable
2025-01-27 2026-05-20 AI parsing service failed Detail
CR02111960059394129921 Image
479 days
Very Stable
2025-01-27 2026-05-20 AI parsing service failed Detail
CR00536741392966221825 Image
479 days
Very Stable
2025-01-27 2026-05-20 AI parsing service failed Detail
CR00122666963213221889 Image
479 days
Very Stable
2025-01-27 2026-05-20 AI parsing service failed Detail
CR13460901996470992897 Image
463 days
Very Stable
2025-02-12 2026-05-20 google.com Detail
CR13233402079927599105 Image
436 days
Very Stable
2025-01-28 2026-04-08 google.com Detail
Page Summary Currently not ideal for indexing

Michael Paul Kish currently matches 9 displayable creatives in public Google Ads data; the historical archive also maps this advertiser to 1 landing domains.

  • Latest visible activity: 2026-06-19.
  • Sample recurring landing domains: google.com.
  • Use this page to judge whether the advertiser is expanding activity, reusing the same landing network, or worth deeper brand-protection and affiliate investigation.
Activity Trend
The latest visible activity is 2026-06-19, which makes this page active within the last 30 days.
Landing Domain Pattern
This advertiser currently maps to at least 1 landing domains, including google.com.
Stability Signal
The page currently matches 9 creatives. Higher creative volume makes it easier to judge whether this is a short-lived test or a stable advertising program.
Investigation Value
This page is best for competitor monitoring, brand protection, and affiliate review: first check whether the same domains repeat, then decide whether the pattern looks like a brand site, an agency network, or a traffic bridge.
Recommended Next Steps

How advertiser search works

Advertiser search is designed for starting from a brand name, company name, or agency name and viewing that advertiser’s public Google Ads footprint. Compared with a generic creative library, it is better suited for search-ad and brand-bidding research because it connects advertisers with landing domains.

For competitor analysis, start with the primary advertiser and then branch into domain searches using the landing domains they promote most often.

Common use cases

  • Brand bidding monitoring: identify who consistently advertises around your brand terms or related landing pages.
  • Creative research: observe whether a given advertiser’s creative volume or recency has changed sharply.
  • Agency detection: use repeated patterns across multiple brands to infer whether the same agency or network is operating them.

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