Artistry Brand Improves Launch Forecast Accuracy by 20pts

Case Study: Top Artistry Makeup Brand x DAASH

A top artistry makeup brand was preparing to launch into one of beauty’s most competitive categories: blush.

Historically, launch targets and forecasts were built primarily from internal sales history. Without category size, competitive rank, or retailer-level velocity, the team had little way to know whether a target was too conservative or too ambitious. More than 80% of launches missed forecast targets, creating either excess inventory or out-of-stocks.

The brand needed to answer two connected questions before launch: What could the product realistically sell, and what would it take to get there?

The Result: Top 3 in Blush and 100% Forecast Accuracy

“Competitive rank, velocity, and sales benchmarks powered a launch that reached the Top 3 in Blush with 100% forecast accuracy.”

DAASH allowed the team to model the economics of the blush category before committing inventory and marketing dollars. Competitive sales and rankings established the revenue associated with different positions; retailer-level sales, door counts, and average velocity translated the opportunity into an inventory forecast.

The team could then work backward from its desired market position. One retailer analysis showed roughly $7.8 million in monthly sales for the #1 blush product versus $540,000 for #10. Using the brand’s 3x ROAS benchmark, leadership could connect its target position to the marketing investment required to support it.

The first major launch planned with this methodology reached the Top 3 in Blush and achieved 100% forecast accuracy—a 20-point improvement—giving leadership a repeatable framework for aligning sales, inventory, and marketing decisions with the competitive economics of the category.