Surfside PPC Podcast Episode 2 - What Campaign Types Should I Run?
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Access premium content on:
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The 2026 Google Ads Course is Here!
Price: Just $34.99/year.
https://surfsideppc.com/products/google-ads-course
Join the Surfside PPC Community: Get your specific questions answered
Professional Help: Ready to stop the guesswork? Visit surfsideppc.com for a professional account audit or full management.
Are you launching ads based on "vibes" or a data-backed hierarchy?
In this episode of the Surfside PPC Podcast, I move beyond basic technical settings to answer the most fundamental question in paid media: Where should I put my budget to actually make money?
I break down the 80/20 rule of budget allocation, why Search is still the "Gold Standard," and how to stop wasting money on low-quality automated leads. Whether you are running lead gen or eCommerce, this episode provides the architectural framework you need to scale.
I break down the 80/20 rule of budget allocation, why Search is still the "Gold Standard," and how to stop wasting money on low-quality automated leads. Whether you are running lead gen or eCommerce, this episode provides the architectural framework you need to scale.
In this episode, I cover:
- The Paid Media Hierarchy: Why you must prioritize campaigns based on intent and funnel position, not just what's "new" in Google Ads.
- The 80/20 Rule: The ideal budget split between Search and Performance Max (PMax) for most businesses.
- Search as the Foundation: Understanding "Money Keywords" vs. "Research Keywords."
- The Roofing Case Study: A deep dive into why you should bid $300 for an installation click but only $75 for a research click (and how to structure this).
- Performance Max Nuances: How to leverage PMax for local store visits and eCommerce without getting flooded with junk leads.
- Demand Gen Strategy: Using video to fill your funnel and build a "living room presence" on YouTube.
- CAC vs. LTV: Why high CPAs are acceptable if you know your numbers.
“Search is the non-negotiable starting point. It provides the clean data signals necessary to fuel the machine learning models.”
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