
Hardware

Using Krunchbox data, CROSSMARK identified the highest-impact SKUs by analysing top performers by both unit sales and dollar value.

Dead stock reports highlighted products that had not moved for 12 weeks or more, allowing teams to pinpoint inventory opportunities at store level.

Field teams visited 155 stores to optimise stock, replenish priority SKUs and implement data-driven adjustments that improved sales performance.

Increasing in-store visibility and education created an opportunity to drive sales and reach customers beyond Pelican’s traditional target market.

The hardware team was upskilled with sales training and objection handling to confidently promote Pelican products in store.

The campaign achieved 150% of target, secured additional displays nationwide, and generated valuable data to support expanded ranging discussions.

“Working with CROSSMARK on our recent off-location project was a huge achievement. The team were very collaborative, brought great ideas and ensured follow-up to ensure and measure success. They provided regular feedback and implemented it in a timely manner with instant results. With their extensive Bunnings knowledge and experience, we will definitely leverage this to run another project together very soon. Thanks again CROSSMARK Hardware Team.”
Driving growth
Across a long standing partnership, our solution rolled out in three phases:
We focused in on the top 20 SKUs by unit sales and top 20 SKUs by dollar value, creating a combined priority list of 32 key SKUs after removing duplicates. This allowed us to focus our efforts where they mattered most and would have the greatest impact.
By using Krunchbox’s dead stock reports, we were able to pinpoint SKUs that hadn’t moved in a specific store for 12 weeks or more.
Our field teams visited a total of 155 stores over a 4-week period, addressing identified dead stock and ensuring the targeted SKUs were optimised. This included adjusting stock, replenishing key items, and capturing all actions taken to measure their impact. The SKUs worked in each store were unique and driven by what the data was telling us.





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