Closing the loop on attribution
How Gildan used Scintilla to make smarter media and merchandising decisions
Data can explain past performance, but it’s most valuable when it’s used to inform future decisions. Gildan, a leading apparel manufacturer, put that principle into practice when they set out to improve how they evaluate media investments and merchandising opportunities at Walmart.
While the applications were different, both approaches shared the same goal of turning data into better business decisions.
The opportunity: Moving beyond retrospective reporting
When running campaigns, Gildan had to wait four to six months for attribution results, which meant they were missing opportunities to optimize investments while campaigns were still live. The brand needed a timelier way to measure incremental sales and a deeper understanding of how advertising across platforms influenced purchases at Walmart.
Meanwhile, Gildan was exploring a new fashion-forward underwear brand to attract younger, more style-conscious Walmart shoppers. But before committing to the launch, the team needed to determine whether enough stores met the criteria to support the brand at scale.
The approach: Connecting insights to action
Gildan developed an agile measurement system that combined daily sales and media data from Scintilla and other platforms. Using causal attribution models that accounted for factors like pricing, promotions, and ratings and reviews, the new system helped the team identify which investments generated incremental sales rather than relying solely on return on ad spend (ROAS).
These insights now feed weekly recommendations to media agencies, enabling adjustments to campaign bids, budgets, and tactics in real-time.
The analysis also uncovered the impact of cross-channel advertising on Walmart sales. While Walmart Connect search generated 53% of incremental Walmart sales attributed to media, nearly half were generated by other media channels, including TikTok and Amazon ads, as well as Amazon and Target search.
By capturing these cross-channel effects, Gildan gained a more complete picture of media performance to better allocate advertising budgets.
With Scintilla, we saw data could move from simply reporting on what happened to influencing what we do next to make better decisions
Evaluating assortment opportunities before launch
Gildan also used Scintilla to evaluate whether a new underwear brand could succeed at Walmart. The team used the Store Sales & Inventory report in Channel Performance to identify stores in targeted metropolitan markets and assess sales performance, then leveraged Performance in Detail within Shopper Behavior to analyze store-level demographics, including age, income, ethnicity, and price sensitivity.
By combining these insights, Gildan assessed stores against criteria including location, sales volume, foot traffic, and customer demographics. The analysis revealed that far fewer stores than expected met all the needed requirements. Without enough qualified locations to support a meaningful launch, Gildan and Walmart decided to pause the initiative, avoiding an unnecessary major investment.
The results: Better decisions, stronger investments
Both use cases showed how Scintilla insights helped Gildan make more informed decisions.
For media, daily data and weekly optimization recommendations replaced months-long reporting delays, helping Gildan direct spending toward higher-performing campaigns. The team also reported improved return on investment (ROI) across multiple brands and platforms.
For merchandising, Gildan and Walmart avoided a potentially costly launch by identifying store-fit challenges upfront, reducing the risk of excess inventory, markdowns, and wasted resources. The analysis also helped distinguish limited store suitability from a lack of customer demand, preserving the opportunity for a future launch.
