What advertising campaigns to set up in Google Ads for promoting an online store

10/07/2025
Google Ads
7 min read

Did you know that over a third of small business owners find it most challenging to determine what truly works in marketing? This uncertainty often leads to budget wastage and hinders the growth of online stores. I have frequently encountered situations where, even with a quality product and competitive pricing, the lack of a clear advertising strategy in Google Ads resulted in low campaign efficiency. This is why Google Ads for an online store has become a tool for me, allowing not only to predictably attract new clients but also to measure every step in the Customer Journey—from the first click to a repeat purchase.

Google Ads today is not just contextual e-commerce advertising. It’s a comprehensive platform that covers search, shopping ads, remarketing, automated Performance Max campaigns, and deep integration with analytics. New AI features, real-time budget optimization, and flexible audience management: all these open unique opportunities for entrepreneurs and marketers for business growth and scaling. In this article, I will reveal in detail which advertising campaigns should be set up for online store promotion, how to avoid common mistakes, and achieve measurable results.

Types of Google Ads Campaigns for Online Stores – Overview and Comparison

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Choosing the type of advertising campaign: a strategic decision that determines the effectiveness of promoting an online store. From my experience, the optimal structure always relies on combining several formats: Google Ads search advertising, Google Shopping campaigns, automated Performance Max, and dynamic remarketing. Each of these tools has its advantages, disadvantages, and usage scenarios.

Google Ads Search Advertising: When and How to Use It

Google Ads search advertising remains the foundation for attracting users with a clear buying intent. It allows the online store to appear in the search results exactly when a potential client enters a relevant query. An important advantage is the ability to work flexibly with keywords: analyze their effectiveness, add negative keywords to cut off non-target traffic, and segment the audience by stages of the Customer Journey.

In practice, I use advanced keyword selection methods, particularly focusing on long-tail queries, which often have a higher conversion rate. The latest updates to Google Ads allow seeing even so-called “private” keywords, low-frequency queries that have previously gone unnoticed but can bring valuable clients, especially for niche stores. For audience segmentation, I recommend Lookalike Audiences—it helps find users similar to your buyers and enhance advertising efficiency.

Google Shopping Campaigns: Features for E-commerce

Google Shopping campaigns are a must-have for online stores selling physical products. They integrate with Google Merchant Center, where a feed with detailed information about each product is formed: name, price, photo, availability, delivery terms (e.g., via “Nova Poshta”). Feed Optimization is a critical stage: the more accurate and complete the data, the higher the likelihood of the ad being shown to the target audience.

Thanks to Product Listing Ads (PLA), products appear directly in Google’s search results, and integration with Conversion Tracking allows precise measurement of each item’s effectiveness.

Performance Max and Smart Shopping: Automation and Multichannel Strategy

Performance Max and Smart Shopping: these are automated campaigns that use AI to place ads across all Google channels: search, YouTube, Gmail, Display Network. They are perfect for scaling when sufficient conversion and audience data have been accumulated. Algorithms autonomously determine where and when to show ads, optimizing bids and budget in real-time.

Performance Max is particularly effective for omnichannel marketing: it lets you reach users at different stages of the Customer Journey using a single budget. At the same time, it is important not to rely entirely on automation: the quality of assets (texts, photos, videos) and clearly defined goals remain critically important for the result.

Google Ads Dynamic Remarketing: Return and Repeat Sales

Dynamic remarketing is a tool for re-engaging visitors who have already interacted with your online store but did not make a purchase. The system automatically selects products the user viewed and displays personalized ads on various Google platforms.

Remarketing scenarios can vary: from reminders about abandoned carts to cross-selling complementary products. For audience segmentation, I recommend using RFM analysis (Recency, Frequency, Monetary Value) and Lookalike Audiences, which helps increase LTV and boost the share of repeat sales.

Structure of Account and Optimization of Google Ads Campaigns for Online Stores

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A well-built account structure in Google Ads is the foundation for effective scaling and budget optimization. For multi-category online stores, it is important to clearly separate campaigns by product categories, segment audiences, and exclude non-target groups.

Building Account Structure: Categories, Campaigns, Ad Groups

I recommend building the account structure based on the principle: product category as a separate campaign, within which ad groups are created for different subcategories or brands. This allows flexible budget management, testing different creatives, and quickly responding to demand changes.

E-commerce audience segmentation is based on user behavior data, purchase history, geography (e.g., separate campaigns for Kyiv, Lviv, Odesa). Competitor analysis in Google Ads helps find new niches and avoid direct competition for expensive queries.

Bid Optimization and Budgeting: Achieving Maximum ROAS

Bid optimization balances the cost of acquiring a customer (CPA) and the value of a purchase (ROAS). Smart Bidding (Target CPA, Target ROAS, Maximize Conversions) allows Google to automatically adjust bids based on conversion probability data. It is crucial to have properly set up conversion tracking; otherwise, automation will not deliver the expected result.

For predicting campaign effectiveness, I recommend using historical data, considering demand seasonality, and distributing the budget between core and experimental campaigns. This helps minimize risks and gradually increase investments in the most profitable directions.

Conversion Tracking and Analytics: Integration with Google Analytics and BI

Conversion tracking is a critical element for measuring advertising effectiveness. Integrating Google Ads with Google Analytics and Google Tag Manager provides deep insights into user behavior, traffic sources, and drop-off points. For multi-channel analytics, I suggest connecting BigQuery or other BI systems, which allow building complex attribution models and analyzing LTV.

Data-Driven Attribution is a modern approach to distributing value among various touchpoints, which is especially important for e-commerce with a long decision-making cycle.

A/B Testing of Ads and Pages: Enhancing Conversion Rates

A/B testing is a mandatory practice for boosting conversion rates. I regularly test different variations of headlines, descriptions, images, and landing pages. For process automation, I recommend using Google Ads scripts and third-party tools to track KPIs. This enables quick identification of the most effective creatives and scaling them with a bigger budget.

Practical Scenarios and Advanced Strategies for Scaling E-commerce in Google Ads

Illustration for the section "Practical Scenarios and Advanced Strategies for Scaling E-commerce in Google Ads" in the article "What Advertising Campaigns to Set Up in Google Ads for Promoting Online Stores"
Scaling an online store in Google Ads requires a comprehensive approach: multi-campaign strategy, CRM integration, automation, and risk management.

Multi-Campaign Strategy: Budget Distribution Among Search, Shopping, and Remarketing Campaigns

An effective multi-campaign strategy involves distributing the budget among search, shopping, and remarketing campaigns depending on the Customer Journey stage. For example, the main budget is allocated to Shopping and Search for attracting new clients, and remarketing for returns and repeat sales. Multi-channel analytics helps evaluate the impact of each campaign on overall sales and optimize budget distribution.

Integration with CRM and Ad Personalization

CRM synchronization opens up opportunities for deep ad personalization: you can create segments based on purchase history, launch special offers for loyal customers, and use Lookalike Audiences to find new buyers similar to the most valuable ones. This increases ad relevance and boosts ROI.

Automation, Scripts, API: Enhancing Efficiency and Managing Risks

Automating routine processes is the key to scaling. Google Ads scripts allow automatic bid adjustments, stopping ineffective ads, and distributing the budget based on results. API integration enables connecting external analytics systems, CRM, or inventory, which is particularly relevant for large online stores with a wide assortment. This reduces the risk of human errors and allows quick responses to market changes.

Trends and Future of Online Store Advertising in Google Ads

Online store advertising in Google Ads is becoming increasingly automated, data-driven, and personalized. AI and Machine Learning are already optimizing bids, selecting audiences and creatives, and attribution models allow precise measurement of each channel’s contribution to the overall result. A key trend: integration of all touchpoints into a single ecosystem, ensuring transparency and control over advertising investment effectiveness.

Key Takeaways and Practical Steps for Entrepreneurs, Managers, and Marketers

    Illustration for the section "Key Takeaways and Practical Steps for Entrepreneurs, Managers, and Marketers" in the article "What Advertising Campaigns to Set Up in Google Ads for Promoting Online Stores"Illustration for the section "Trends and Future of Online Store Advertising in Google Ads" in the article "What Advertising Campaigns to Set Up in Google Ads for Promoting Online Stores"

  • Start with Search and Shopping campaigns for quick target traffic attraction and hypothesis testing.
  • Use Performance Max for scaling once sufficient conversion and audience data has been accumulated.
  • Optimize account structure for product categories and audience segments.
  • Implement Smart Bidding and regularly analyze ROAS for each campaign.
  • Integrate Google Analytics, Merchant Center, and CRM for full control over the Customer Journey.
  • Test creatives and pages through A/B testing, use scripts for automation.
  • Distribute budget among different campaign types and adjust it based on seasonality and results.
  • Implement personalization based on CRM data and Lookalike Audiences.
  • Use BI systems for LTV analysis and long-term planning.
The effectiveness of Google Ads for online stores is the result of systematic work, deep analysis, and continuous improvement. Business owners who implement these approaches achieve measurable results, transparency, and confidence in every investment.