🚦 Google ADs Signals - How ‘Signals’ Affect Results Coming From Google ADs Greatly 📊

About this Video

• Video Title: 🚦 Google ADs Signals - How ‘Signals’ Affect Results Coming From Google ADs Greatly 📊
• Channel: Guaranteed PPC
• Speakers: Corey Zimman
• Duration: 00:27:25

Introduction

This video explains how "signals" in Google Ads significantly impact campaign results. The speaker, Corey Zimman, emphasizes that most users don't utilize signals to their full potential and details how understanding and implementing signals can drastically improve ad performance and ROI. He focuses on two types of signals: those used in demand gen and PMax campaigns and those used to optimize smart bidding.

Key Takeaways

1. Signals in Google Ads are crucial: They act as training data for the Google algorithm, helping it learn which audiences are most likely to convert, thus optimizing ad delivery and ROI. Improper signal use leads to wasted ad spend and lost opportunities.
2. Two main types of signals exist: One is used in demand generation (Gmail, YouTube) and Performance Max campaigns, where you directly provide Google with data on likely converters (e.g., competitors' products, demographics). The other involves using conversion data (purchases, add-to-cart, etc.) to train the smart bidding algorithm.
3. Competitive signals are highly effective: Including competitor products as signals in PMax campaigns directs ad placement to users already searching for those items, maximizing efficiency and profitability. This is applicable to other platforms like Amazon Ads (ASIN targeting).
4. Comprehensive tracking and audience segmentation are key: Setting up detailed conversion tracking (time on site, add-to-cart, checkout progress, etc.) and segmenting audiences based on these actions provides Google with richer data to optimize bidding and ad delivery.
5. Iterative optimization is essential: The speaker advocates for a phased approach to optimizing smart bidding. Start by prioritizing leads or add-to-cart actions initially, then gradually shift to purchase optimization as sufficient conversion data accumulates.