A core shaver range declined 48% in one month across Australia’s largest retailers, with no clear explanation.
Product quality, pricing and distribution were stable, but the packaging had changed from transparent plastic to opaque cardboard. With retailer range-review meetings approaching and shelf space at a premium, the business needed a credible explanation and a practical recovery plan.
Approach & Analysis
- Scan Data: Using Scan (Sales) Data, the decline was confirmed to be across the largest retailers in Australia.
- Consumer Panel Data: Shoppers who previously purchased the range were not re-purchasing the products and were switching to competitors. Other products were performing normally.
- Custom Shopper Research: A survey was conducted with current shoppers of the affected product, and the survey found that consumers couldn't determine what was in the packaging – whereas the old packaging was transparent.
Root Cause
The product and price were fine. The packaging had changed, and the changes were not communicated to the consumer, so consumers no longer understood what they were purchasing.
The Recommendation
A business case was presented to the retailer, along with a plan on how to soften the decline before a new reiteration of packaging comes into the market:
- Redesign the packaging: new packaging will flow into the market in a year
- Updated shelf layout: improve visual hierarchy and place the affected products at a higher eye-level with similarly priced products
- Remove wasted promotions/discounts and optimise the promotional program
Results
Within the next year, the Shaver range reversed from a -48% decline to +18% growth. The company retained the full Shaver range and kept the same amount of space year-on-year.
Skills Demonstrated
- Multi-Source Analysis: combined Scan data, panel data, and survey data to create a cohesive story.
- Business Case Development: translated findings into actionable recommendations for a retail buyer/sales audience.
- Commercial impact: delivered growth to a product range (a +66pt swing) in year-on-year performance for a core product range.
Key Takeaway
The insights came from connecting all three datasets to create a cohesive narrative, and then translating them into commercial recommendations.
Related methods
- A framework for separating the sales result from its underlying cause.
- The data-quality checks I use before relying on multiple sources.
This case study sits within the broader commercial analytics framework for diagnosing sales and product performance.