Last Updated on October 14, 2024 by Jelena Bozic

How to Scale Google & Bing Ads Like an E-Commerce Expert

Jelena Bozic

September 21, 2024

In the world of digital marketing, Google Ads and Microsoft Ads (formerly Bing Ads) are powerful platforms that, when used together, create a dynamic SEM strategy. While many advertisers treat them as separate entities, the most successful SEM professionals understand that these channels complement each other. Insights gained from Google Ads can inform tactics on Microsoft Ads and vice versa, allowing for continuous optimization across both platforms. Whether it's bid strategies, audience targeting, or keyword management, learnings from one platform can help refine and improve performance on the other.

However, in today's hyper-competitive landscape, basic strategies no longer cut it. It's not enough to follow platform recommendations or rely on generic optimization methods. That’s why the top 1% of PPC experts set themselves apart by mastering advanced tactics like dynamic budget allocation, cross-platform automation, and machine learning-powered audience targeting. They’re constantly tweaking their campaigns, making sure every dollar works as hard as possible across both Google and Bing.

To achieve success nowadays, it's crucial to go beyond the basics. In this guide, we'll explore the advanced strategies and techniques that set the top 1% of PPC professionals apart and show how you can apply them to both Google Ads and Bing Ads to drive e-commerce success.

1. Advanced Bidding Strategies

Google Ads:

  • Implement portfolio bid strategies to optimize across multiple campaigns simultaneously
  • Utilize Target ROAS bidding with seasonality adjustments for high-volume periods
  • Leverage advanced bid modifiers for device, location, audience, and time of day in conjunction with automated bidding
Bid adjustments set at the audience level

Bing Ads:

  • Experiment with Enhanced CPC in combination with manual bid adjustments for greater control
  • Implement target CPA strategies with custom conversion windows to align with your sales cycle
  • Use shared budgets across campaigns to allocate spend to top performers automatically

Advanced Tactics:

  • Develop custom bidding scripts for Google Ads to automate bid adjustments based on complex criteria (e.g., weather data, stock levels, competitor pricing)
  • Utilize Google Ads API to create dynamic bid strategies that incorporate real-time data from your inventory management system
  • For Bing Ads, leverage the Microsoft Advertising API to implement more sophisticated bidding logic that the native interface doesn't support

2. Advanced Audience Targeting

Google Ads:

  • Implement custom intent audiences using machine learning-driven combinations of keywords, URLs, and apps
A custom segment in Google Ads targeting people who searched for these keywords or visited similar websites.

  • Utilize in-market audience layering with custom affinity audiences for hyper-targeted prospecting
Observing in-market and affinity audiences inside Search prospecting campaign
  • Leverage Customer Match with recency, frequency, and monetary value (RFM) segmentation

Bing Ads:

  • Exploit LinkedIn Profile targeting for B2B campaigns with highly specific professional attributes
  • Combine Microsoft Audience Network with search campaigns for full-funnel targeting
  • Utilize In-market Audiences with custom combinations to reach users at different stages of the buying journey

Advanced Tactics:

  • Develop a first-party data strategy using Google Analytics 4 and Google Ads API to create highly granular audience segments based on on-site behavior and customer value
  • Implement cross-device retargeting by linking Google Ads with Firebase for mobile app integration
  • For Bing Ads, use Custom Audiences with offline conversion imports to create lookalike audiences based on high-value customer segments

3. Advanced Keyword and Query Management

Google Ads:

  • Implement n-gram analysis to identify high-performing phrase components across match types
  • Utilize BERT-optimized responsive search ads with pinning for controlled messaging
  • Leverage auction-time bidding for query-level optimizations

Bing Ads:

  • Exploit phrase match keywords for broader coverage while maintaining relevance
  • Implement dynamic keyword insertion with default text optimization
  • Utilize broad match modifier keywords (still available in Bing) for controlled keyword expansion

Advanced Tactics:

  • Develop a custom script to automate the process of identifying and implementing single keyword ad groups (SKAGs) for top-performing queries
  • Use Google Ads API to implement real-time keyword bidding based on search query performance and user intent signals
  • For Bing Ads, leverage the Microsoft Advertising API to automate the process of moving high-performing broad match keywords to more specific match types

4. Advanced Shopping Campaign Optimization

Google Ads:

  • Implement Smart Shopping campaigns with product-specific ROAS targets
  • Utilize showcase shopping ads for upper-funnel product category targeting
  • Leverage product partition bidding with inventory-based bid modifiers

Bing Ads:

  • Exploit low competition in certain product categories for cheaper clicks
  • Implement product group segmentation based on performance tiers
  • Utilize Bing Shopping Campaigns' auto-bidding features in combination with manual adjustments

Advanced Tactics:

  • Develop a custom feed management system that dynamically adjusts product titles and descriptions based on performance data and search trends
  • Implement automated price monitoring and bidding adjustments based on competitor pricing data
  • For Bing Shopping, create a script to automatically segment products into ad groups based on performance metrics and apply tiered bidding strategies

5. Advanced Attribution and Analytics

Google Ads:

  • Implement data-driven attribution models with custom lookback windows
  • Leverage Google Cloud Platform for big data analysis of customer behavior across channels
  • Utilize Google Analytics 4 for advanced user journey analysis and predictive metrics
GA 4 advanced user journey analysis

Bing Ads:

Advanced Tactics:

  • Develop a custom attribution model using machine learning algorithms that incorporate both online and offline touchpoints
  • Implement cross-platform attribution by using probabilistic matching techniques for users across Google and Bing
  • Create a unified reporting dashboard that combines data from Google Ads, Bing Ads, and your CRM system for holistic performance analysis

6. Advanced Testing and Optimization

Google Ads:

  • Implement sequential A/B testing for continuous ad copy improvement
  • Utilize Google Optimize for server-side testing of landing pages
  • Leverage drafts and experiments for controlled campaign optimizations

Bing Ads:

  • Implement ad rotation settings with a focus on conversions for quicker optimization
  • Utilize Experiments to test significant campaign changes
  • Leverage Keyword Planner for competitive analysis and opportunity identification

Advanced Tactics:

  • Develop a Bayesian testing framework for more efficient ad copy and landing page optimizations
  • Implement multi-armed bandit algorithms for dynamic budget allocation across campaigns and ad groups
  • For Bing Ads, create a custom testing framework using the API to automate the process of creating and analyzing experiments across multiple campaigns simultaneously

7. Advanced Automation and Scripts:

Google Ads:

  • Develop complex scripts for automated budget pacing and reallocation
  • Implement automated alerts and adjustments based on quality score changes
  • Utilize scripts for automated competitor analysis and bidding adjustments

Bing Ads:

  • Leverage Automated Rules for sophisticated campaign management
  • Implement scheduled imports from Google Ads with custom rulesets for adaptation
  • Utilize bulk API operations for large-scale campaign optimizations

Advanced Tactics:

  • Create a machine learning model that predicts quality score changes and automatically implements preemptive optimizations
  • Develop a custom bidding algorithm that incorporates real-time conversion value data, competitor activity, and inventory levels
  • For Bing Ads, create a suite of PowerShell scripts to automate complex campaign management tasks that aren't possible through the standard interface

8. Cross-Platform Strategies:

  • Implement a unified tracking system that accurately attributes conversions across both platforms
  • Develop a dynamic budget allocation model that shifts spend between Google and Bing based on real-time performance data
  • Create a cross-platform audience strategy that leverages the strengths of each platform's targeting capabilities

Advanced Tactics:

  • Develop a custom algorithm that predicts the incremental value of spending on Bing Ads vs. Google Ads for different customer segments and product categories
  • Implement a cross-platform testing strategy that rapidly iterates ad copy and landing pages across both platforms, using insights from each to inform the other
  • Create a unified bidding strategy that takes into account the different auction dynamics and competition levels on Google and Bing to maximize overall ROAS

Final Thoughts

For a highly technical SEM media buyer, success in e-commerce across Google Ads and Bing Ads requires a sophisticated approach that goes beyond standard platform features. By leveraging advanced bidding strategies, granular audience targeting, complex keyword management, and custom scripts and automation, you can gain a significant competitive advantage.

By implementing these advanced strategies and continually pushing the boundaries of what's possible with both platforms, you can significantly improve your ROAS on Bing Ads while maintaining strong performance on Google Ads. Remember to stay up-to-date with the latest platform features and API capabilities, as these can often open up new opportunities for advanced optimization and automation.

Which advanced strategies have you tried? We'd love to read your comments!

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