We don't publish vanity metrics. Every number on this page comes from active fashion brand accounts — blended ROAS, new customer CAC, and GMV growth from paid channels only.
Key performance statistics
Fashion GMV driven across all client accounts — paid channels only
Average blended ROAS across fashion clients (fashion industry average: 2.8x)
Fashion brands scaled from mid-market to 8-figure annual GMV
Average CAC reduction within the first 90 days of paid media engagement
Average new customer ROAS (nROAS) — cost of acquiring first-time buyers
Average BFCM revenue lift vs. same brand's prior year — across all fashion clients
ROAS Benchmark
nonetime fashion clients vs. fashion industry average — by ROAS type
Grouped bar chart comparing nonetime fashion client ROAS against fashion industry averages. Blended ROAS: nonetime 4.2x vs industry 2.8x. New customer ROAS (nROAS): nonetime 2.9x vs industry 1.9x. Retargeting ROAS: nonetime 6.3x vs industry 4.1x.
ROAS by Channel
Average ROAS per paid channel — nonetime fashion client median
Horizontal bar chart showing average ROAS by paid channel for nonetime fashion clients: Retargeting and DPA at 6.3x, Meta and Instagram at 4.5x, Google Shopping at 4.1x, TikTok Ads at 3.6x.
Seasonal ROAS Trend
Monthly blended ROAS — nonetime fashion clients vs. industry average (full calendar year)
Line area chart showing monthly blended ROAS throughout the year. nonetime fashion clients (lime line) consistently outperform the fashion industry average (dashed line). Both show a significant BFCM spike in November, with nonetime clients reaching 7.4x versus industry average 5.1x. nonetime clients range from 3.6x in July to 7.4x in November.
A streetwear DTC brand was stuck at 1.7x blended ROAS despite heavy Meta spend. We audited their Advantage+ campaign structure, rebuilt prospecting with nROAS-segmented creative testing, and shifted DPA overlays to collection-level catalog creative. Result: 5.1x blended ROAS and 42% lower CAC within 60 days.
A premium accessories brand was running a single undifferentiated PMax campaign with no audience signals and no brand exclusions. We separated asset groups by collection, built purchaser audience signals, and excluded branded search. ROAS went from 1.4x to 3.8x and GMV grew 180% in one season.
A fast fashion brand with zero TikTok presence wanted to test the channel. We handled full TikTok Shop integration, CPAS campaign setup, and creator seeding for performance UGC. 47 Spark Ads tested in 90 days, 9 scaling. Result: TikTok now accounts for 22% of total paid GMV and 2.8x attributed CPAS ROAS.
A multi-brand fashion boutique had historically under-indexed on BFCM — no pre-BFCM audience warm-up, no budget phasing, no creative ready in advance. We built an 8-week BFCM campaign plan across Meta and Google Shopping. That November was 2.8x their prior year BFCM revenue with a 4.6x blended ROAS on peak days.
nonetime understood fashion immediately. They didn't try to apply a generic DTC playbook — they knew the seasonal calendar, they understood creative fatigue cycles for fashion, and they built our Meta structure around nROAS from day one. ROAS went from 1.7x to 4.8x in a quarter.
Our Google Shopping was completely broken — one PMax campaign with no audience signals, losing to competitors on every key product. nonetime fixed our product feed from scratch, separated campaigns by collection, and rebuilt our bidding strategy. Within two months we went from 1.4x to 3.8x ROAS on Google alone.
TikTok was a mystery to us — we couldn't tell if it was working or not. nonetime set up proper attribution, got us onto TikTok Shop, and ran 47 creative tests in our first quarter. Now we know exactly what's working and TikTok is our fastest-growing paid channel by GMV.
We'd never had a proper BFCM strategy — just turned up budgets the week before and hoped. nonetime built us an 8-week plan, warmed our audiences, had creative ready for every phase, and we ended up with 2.8x our prior year BFCM revenue. That one campaign more than paid for the entire year's fees.