Scaling one of NL’s top running stores through strategic Segmentation

How a structured Google Ads account opened the path to profitable scale.

About the Brand

De Hardloopwinkel is a Dutch omnichannel retailer with five physical stores and a leading online presence. Formerly known as Hardloopaanbiedingen.nl, the company rebranded to strengthen its brand identity and customer experience. They carry one of the widest assortments of running shoes in the Netherlands, featuring top brands like Asics, Brooks, and Hoka.

The Challenge

Despite a strong multi-channel presence and extensive product range, De Hardloopwinkel’s paid performance had stagnated. ROAS and revenue plateaued, CAC remained high, and marketing margins were razor-thin.

The account structure, originally built around a Shopping-reliant approach with fragmented brand campaigns, lacked the adaptability needed for scaling. With most of the budget flowing into Standard Shopping and static Search ads segmented across a wide variety of campaigns, there was little ability for algorithms to get smarter, segment performance, or build toward long-term learning.

Our Strategy

Our approach focused on deep restructuring — not just tactics, but architecture, segmentation, and automation logic. This gave the brand full control over performance levers while unlocking scale across the most profitable prospecting campaigns.

1. Intent-Led Segmentation in Performance Max

Rather than relying on generic PMax setups, we designed a segmented structure built around two key axes:

• Product-line segmentation: separating core categories (e.g. Asics vs. Hoka) to control spend and optimize bids per brand.

• Product performance: by running a labelizer script we were able to segment products in different campaign layers based on their performance in comparison to the average.

2. Search Campaign Consolidation

The previous structure had multiple separate campaigns for each major brand (Asics, Brooks, Hoka, Saucony, etc.) — resulting in data dilution and inefficient budget spread.

We replaced this with an future-proof structure:

• 1 Generic search campaign: for discovery queries like “best runningshoes”

• 1 Brand campaign for each major brand: grouped by behavior (e.g., “Hoka Bondi dames” vs. “Asics Gel Nimbus”)

• Dynamic search: for inspiration of new keywords

By consolidating to fewer but data-richer campaigns, we allowed smart bidding to mature, and improved the signal-to-noise ratio for Google’s algorithm.

3. Continuous Growth Roadmap

• Rolled out structured experimentation across all campaign types.

• Ran a number of key experiments such as testing collection pages vs. PDPs for higher CVR on search traffic.

Results

118% Revenue Growth

28% ROAS Increase

71% Spend Increase