Retour

Alexander Del Rossa

Alexander Del Rossa Success Story: Driving Efficiency and ROAS with Targeted Google Ads

Alexander Del Rossa

About Alexander Del Rossa

Alexander Del Rossa is a luxury sleepwear and loungewear brand that celebrates the comfort of home. Their premium collection includes plush bathrobes, silky pajamas, and nightgowns designed to elevate bedtime routines with luxurious fabrics and thoughtful craftsmanship. With promotions like automatic discounts on higher-value orders, Del Rossa offers customers both comfort and value.

Alexander Del Rossa

Notre approche

Notre approche

Del Rossa faced the challenge of scaling up sales through Google Ads while maintaining or improving their Return on Ad Spend (ROAS). They wanted a strategy that would allow them to reach a broader audience without sacrificing profitability, as their higher-end pricing required effectively conveying product value to potential buyers. After previous attempts with Google Ads that yielded limited success, they needed a targeted, data-driven approach.

WeAdU’s Strategy and Implementation

We created a tailored approach using feed-only Performance Max (PMax) campaigns to maximize reach, streamline ad spend, and enhance the campaign's efficiency by focusing on high-value, high-ROAS products. Here’s how we helped Del Rossa succeed with Google Ads.

What We Did:

  1. Feed-Only PMax Campaign for Full-Funnel Reach:

In the PMax, we start with one feed-only Asset Groups per product type.That allows us to target the best network in terms of conversion rate, Google Shopping, and gather quality data about people interested in buying our products. It also allows us to show product-specific ads to past visitors via the Dynamic Remarketing feature. Later, once an Asset Group generated enough conversions, we start adding more Assets to expand our reach to other networks (Search, Display, Youtube and Discovery) based on high-quality conversion data.

  1. Segmenting Products by Performance for Focused Spending:

Based on data from the PMax campaign, we segmented Del Rossa’s product categories into high, medium, and low-performing groups. Top-selling items, like plush robes and premium pajamas, received more budget and exposure, while lower-performing segments were allocated reduced bids or transitioned to separate Standard Shopping campaigns for further refinement​. By focusing ad spend on the highest-performing products, we maximized ROAS while ensuring that each dollar was spent on products with the highest sales potential.

  1. Smart Bidding with Target ROAS:

We implemented Target ROAS Smart Bidding to help Google’s AI dynamically adjust bids based on real-time data. This strategy ensured ads were shown to users most likely to convert, particularly for high-value products, helping us maintain profitability while scaling up sales.Smart Bidding allowed Del Rossa to control ad costs effectively, prioritizing ROAS-focused bidding to increase conversions from high-intent users.

  1. Three-Tier Campaign Strategy for Underperforming Products:

For underperforming products in the PMax campaign, we applied a three-tiered shopping campaign approach. High-priority campaigns with minimal bids acted as filters, while medium-priority campaigns targeted broader keywords, and low-priority campaigns captured remaining, less competitive searches​. This three-tier structure enabled us to continue promoting all products without overspending, improving ROAS by focusing on the most relevant search terms for each product segment.

  1. Using Dynamic Product Ads for Seasonal Campaigns:

We utilized Dynamic Product Ads (DPA) to highlight seasonal items and special promotions. By dynamically adjusting ads to feature best-selling products during peak times, like the holiday season, we ensured Del Rossa’s ads resonated with seasonal buyer intent. This tactic aligned ad content with peak shopping periods, helping drive higher conversions from customers actively searching for luxurious and gift-worthy items, like bathrobes and pajamas.

  1. Audience Layering with Intent-Based Targeting:

We used audience signals tailored to reach users interested in home comforts, luxury apparel, and loungewear. By combining Customer Match with Google’s audience signals, we reached new customers with similar interests and reconnected with previous customers or site visitors. Audience layering ensured that ads were highly relevant, increasing click-through rates and engagement from users already aligned with Del Rossa’s brand and product value.

  1. Weekly Performance Reviews and Real-Time Adjustments:

We conducted weekly performance analyses, adjusting bidding strategies, audience targeting, and budget allocations based on data trends. By tracking KPIs like conversion rate and average order value, we ensured that the campaign adapted dynamically to sustain ROAS and growth.Continuous optimization kept ad performance in check, allowing us to make quick changes based on real-time data, ensuring that Del Rossa’s campaigns remained agile and effective as they scaled up.

Alexander Del Rossa

Les résultats

The Result:

Through a combination of feed-only PMax campaigns, advanced bidding strategies, and targeted audience layering, Del Rossa saw substantial improvements in both ROAS and sales volume. The approach allowed them to reach new customers and retain profitability, proving that with the right strategy, Google Ads can effectively drive growth even in competitive markets.

The focused approach to high-performing products and dynamic seasonal adjustments contributed to consistent growth and established Google Ads as a viable, scalable channel for Del Rossa’s business.

Rejoignez des centaines de
commerçants en ligne qui ont réussi en tirant parti de Google Ads

97%

des clients
voient leur ROAS augmenter

$63.4 Billions

des revenus traçables
dans l'ensemble de notre portefeuille

$5.3 Billions

Conversions generated

Découvrez nos résultats
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.

Plus d'études de cas

Toutes les études de cas