Specialty Retail Traffic Analytics
Building Brick-and-Mortar With Data From Day One
How DTC darling, Balsam Brands, leveraged traffic analytics to launch and scale a strategic retail presence across Balsam Hill and Balsam Hill Studio, achieving 31% labor savings and boosting entry rates up to 10% YoY in physical stores.
Labor cost reduction
Balsam Brands
Entry-rate increase (peak holiday)
Balsam Brands
Balsam Brands is a privately held omnichannel retailer founded in 2006, best known for its flagship brand Balsam Hill, the world's leading retailer of highly realistic artificial Christmas trees and premium holiday decor. Built as a digitally native, direct-to-consumer brand, Balsam Brands is now expanding into physical retail — including its year-round Balsam Hill Studio concept in Hawaii — to create immersive experiences that digital channels alone cannot replicate.
The Challenge
Unlike most retailers who add analytics after opening stores, Balsam Brands wanted to embed measurement from day one. As a digitally native brand entering brick-and-mortar, it had no historical foot-traffic benchmarks, and post-pandemic shifts had made lease-based traffic estimates unreliable. The company needed accurate, real-time data to validate store performance beyond sales alone, to treat stores as measurable marketing assets, to understand the full passby-to-entry-to-purchase journey, and to staff locations efficiently without visiting them from headquarters.
The Solution
Balsam Brands launched its stores with RetailNext Traffic Analytics in place from the outset, standing up dedicated RetailNext environments tailored to its standard and outlet retail models. The team used passby and entry data to run signage and visual-merchandising tests, analyzed traffic by hour and day to align labor with real demand, and used in-store traffic to measure whether external marketing activations actually drove visits.
The Results
Storefront and visual-merchandising tests lifted entry rates by 8–10% year over year during peak holiday periods, and traffic-based scheduling reduced labor costs by 31% while protecting service quality at peak times. Traffic data also let the team quickly invalidate marketing hypotheses — such as airport-focused activations that did not move in-store traffic — and redirect spend toward initiatives that did, building a data-driven foundation for future retail expansion.
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