How OMcollective boosted Torfs ROAS & revenue with Channable’s automation

Torfs, one of Belgium’s most iconic footwear and fashion retailers, wanted to scale online sales efficiently across its 250+ brands and 15,000+ SKUs. By partnering with OMcollective and leveraging Channable’s automation suite, Torfs unlocked a smarter and fully scalable performance marketing strategy that helped to boost their ROAS, revenue, and conversion rate.

This success story explains how Channable enabled Torfs to automate Search and Shopping campaigns, introduce intelligent product scoring, and drive measurable growth.

Key results

Growth in Google Shopping and PMAX measuring from 01/07 – 30/11 YoY with OMcollective's live scoring model.

• +27% in revenue

• +29% in ROAS

• +66% in CR

• Value per conversion remained stable

The challenge

With more than 15,000 active products, Torfs needed a performance setup that:

• Reduced manual campaign management

• Prioritized high‑value products

• Ensured visibility for long‑tail and seasonal inventory

• Scaled across Flanders & Wallonia

Their previous Shopping setup relied heavily on category-based and margin-based bidding. Key signals such as seasonality, sale status, bestseller trends, and profitability were not fully utilized.

A fully automated performance strategy

1. Automating search ads with Channable’s text ad generator

OMcollective used Channable to dynamically create ads with:

• Keywords

• Ad groups

• Responsive Search Ads

• Product URLs

• Brand & type‑level coverage

Result: Every brand and shoe type receives automated, accurate, and constantly updated ads, without manual management.

2. A score‑based Shopping & PMAX structure

To improve product prioritization, OMcollective built a custom scoring model using Channable Insights. The model assigns weighted values to five key variables, tailored per market and product group, creating a dynamic distribution across products with labels A, B, C, and D as an example.

This flexibility allows OMcollective to shift focus between sale and non-sale periods and adapt quickly to new collections, ensuring more budget and stronger bids are always allocated to the most valuable products.

Variables for scoring

• Insights Label

• Sale Status

• Sell-Through Rate

• Target Audience

• Stock Levels

• Profitability

• Bestseller Status

• Sale Status

• Seasonality

This model determines which bucket a product enters, ensuring high-value products receive more aggressive bidding while still maintaining visibility for dormant or niche SKUs.

Distribution Example:

• Label A – 11.5%

• Label B – 36.3%

• Label C – 21.8%

• Label D – 30.4%

3. Structured, phased implementation

The new structure was rolled out in phases, starting with research and model design, followed by building and refining the scoring logic in Channable Insights. After switching the Shopping structure, performance was closely monitored and optimized, with Performance Max segmentation rolled out once the model proved effective.

The impact

Business growth

• Torfs increased overall sales by 4% in 2024 (online + in-store)

• Torfs.be now performs at the level of 17 physical stores

• More on Torfs success and growth strategy can be found in their article with De Tijd

Performance growth (2025 vs 2024)

• +27% in revenue

• +29% in ROAS

• +66% in CR

• Value per conversion remained stable

These improvements were supported by automation, intelligent segmentation, and feed-based decision-making, alongside ongoing optimization and strategic campaign management.

FAQs

How did Channable help Torfs scale its campaigns?
By automating Search Ads creation and enabling dynamic Shopping segmentation for 15,000+ products.

What made the scoring model effective?
It aligned bidding strategy with product value by combining insights from Channable Insights with key feed-based signals such as seasonality, sales status, profitability, and bestseller performance.

Can other retailers use this approach?
Yes, any large catalog benefits from score-based segmentation.

Did PMAX work with the scoring buckets?
Yes. OMcollective utilized separate PMAX and Shopping campaigns for each bucket \ label. This structure allowed them to maintain granular control over budgets and bid strategies per bucket, rather than just segmenting by asset groups.

What part of Channable delivered the biggest impact?
The Text Ad Generator and Insights-powered scoring model.

Looking Ahead

As Torfs continues to scale, they plan to build on the strategies that delivered the strongest results. The combination of dynamic Search automation, score‑based Shopping segmentation, and data‑driven optimization through Channable Insights proved essential to improving both efficiency and ROAS.
Here’s what worked best for them:

• Channable’s Text Ad Generator for fully automated Search Ads creation

• Channable Insights to build a product scoring model and prioritize high‑value SKUs

• Shopping & PMAX feed optimization using rules-based automation and detailed product data enrichment

What’s next for Torfs

Going forward, Torfs and OMcollective will continue refining their product scoring, expanding automated campaign outputs, and scaling PMAX segmentation, ensuring every product consistently reaches the right audience at the right moment.

Ready to take your performance marketing to the next level?
Start your free trial or book a demo today.