8+ years growing brands on KPIs, now with AI
Performance Marketing for Athleisure Brands That Are Done Guessing at ROAS
We build and run paid media, creative, and AI-driven analytics for DTC athleisure brands, measured on blended ROAS, not platform vanity numbers.
Google Ads · Meta · TikTok partners · 8+ years growing DTC brands · results measured in revenue, not impressions
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The Challenge
Growing an Athleisure Brand Past $3M Is a Different Problem Than Growing It to $3M
You got here on founder intuition, a hero SKU that resonated (the legging or jogger that became 40% of your revenue) and paid social that worked before CPMs crept up. That combination stops compounding somewhere between $3M and $5M, and it almost always stalls for the same reason: you're making budget decisions based on last-click ROAS and gut feel instead of blended MER and cohort LTV.
The category has never been harder to navigate. Over 4,500 new athleisure brands launched globally between 2022 and 2024. Vuori just closed an $825M round at a $5.5B valuation. Alo and Gymshark are growing 30%+ year-over-year. You're not competing against Nike. You're competing against well-funded challengers who are chasing the exact same DTC customer, on the exact same platforms, with deeper creative budgets.
Meanwhile, your Meta CPMs keep rising, iOS attribution gaps mean you don't fully trust the numbers your platform dashboard shows you, and every Q4 you face the same brutal math: holiday discounting in North American athleisure averaged 31% depth in 2024, which compresses the gross margin on your highest-volume quarter right when you need it most.
The brands that break through aren't necessarily the ones with the best product. They're the ones that get the measurement right, build creative infrastructure that can actually feed TikTok and Meta at the velocity those platforms demand, and stop renting revenue one campaign at a time.
The Opportunity
The Demand Is There. The Margin Is There. Most Brands Just Can't Capture It Cleanly.
Athleisure is one of the few apparel categories where TikTok has proven itself as a genuine revenue channel, not just awareness. Apparel and accessories clear a 2.49 ROAS on TikTok, the only industry to break 2.0, which means brands that crack the creator-native creative language on that platform are seeing 30–50% lower CAC than their equivalent Meta spend. Most brands in your category are still treating TikTok as an experiment rather than a primary channel.
Email and SMS are generating 20–30% of DTC fashion revenue at a return of $42–$45 per dollar spent. If your Klaviyo flows (abandoned cart, post-purchase, win-back) aren't fully built and segmented by first-purchase product, you're leaving the highest-margin revenue on the table. A customer whose first purchase is your $150 hero legging has a fundamentally different 24-month LTV than a customer who came in on a $30 loss-leader, and your automation should treat them differently from day one.
Influencer-sourced UGC is delivering 30% lower CPA than brand-produced creative. Micro-influencers in specific fitness niches (Pilates, trail running, functional fitness) consistently outperform mega-influencers on cost-per-conversion. The brands building a systematic pipeline of that content and feeding it into paid channels are the ones holding ROAS while everyone else watches their numbers slide.
The window to build this infrastructure before Q4 and the New Year's resolution spike (the two highest-intent periods in the athleisure calendar) is shorter than it feels. Brands that pre-load creative and inventory before December capture the January burst; brands that don't miss it entirely.
What Most Get Wrong
What Most Athleisure Brands (and the Agencies They Hire) Get Wrong
Running on platform ROAS instead of blended MER
Meta's reported ROAS and your actual business performance diverge the moment iOS attribution gaps enter the picture. Brands optimizing to a 4x Meta ROAS may be running a 2.1x blended MER, and won't know it until they try to reconcile ad spend against revenue in their Shopify backend. Decisions made on platform numbers alone are decisions made on fiction.
Ignoring cohort LTV when evaluating acquisition channels
Customers acquired through organic search show 20–30% higher LTV than customers acquired through paid social, but most brands evaluate channels purely on first-order ROAS. This leads to underinvesting in SEO and email (the channels that build repeat purchase rate) and overweighting paid social, which rents customers rather than owning them.
Letting creative fatigue kill TikTok before it starts
TikTok's algorithm punishes creative fatigue faster than any other platform. Hooks need to rotate weekly, not monthly. Brands that launch one or two pieces of creative and wait to see results are effectively opting out of the channel. The algorithm deprioritizes content the moment engagement velocity drops, which happens within days on a static creative set.
Treating the hero SKU as the whole acquisition strategy
The legging or jogger that drives 40%+ of revenue is a powerful hook, but building all prospecting creative and ad sets around a single SKU creates fragility. When that product faces a return-rate spike (and in athleisure, 24–50% return rates are the norm, not the exception), the entire acquisition funnel is exposed. Brands need creative and campaign architecture that builds the brand, not just the SKU.
Hiring agencies that bring a generic DTC playbook instead of athleisure-specific creative judgment
An agency that doesn't understand that 'squat-proof' and '4-way stretch' are table-stakes copy language (not differentiators) will produce creative that reads like every other activewear brand. In a category with 4,500+ competitors, generic positioning is invisible positioning. The cost isn't a bad ad; it's wasted spend on creative that never had a chance to convert.
Why Now
Why the Brands That Move Now Will Be Harder to Catch in 12 Months
Most DTC athleisure brands are running the same paid social playbook they were running in 2021: a Meta-heavy budget, a handful of creative assets refreshed quarterly, and a Klaviyo account that's half-built. That playbook is getting more expensive and less effective every quarter as CPMs rise and the category gets more crowded.
The shift happening right now is that AI has made it practical for a focused operator (not a brand with a 20-person in-house team) to test creative at the velocity TikTok demands, catch attribution errors before they compound into bad budget decisions, and build personalized email sequences that actually segment by cohort LTV instead of treating every subscriber the same. These are things that used to require headcount. They don't anymore.
The timing factor for athleisure specifically: Q4 and the New Year's resolution window (January 1–15) are the two highest-intent, highest-conversion periods in the calendar. The brands that enter Q4 with a tested creative library, a clean attribution setup, and automated email flows already generating repeat purchases will compound those periods. The brands that try to build infrastructure in November will spend Q4 firefighting instead of scaling.
This isn't about being early to AI for its own sake. It's about the fact that a disciplined operator using these tools now can run creative testing cycles, attribution monitoring, and LTV-based audience segmentation that a competitor without them simply cannot match at the same cost. That gap widens every month it goes unaddressed.
The Mechanism
Where AI Actually Creates an Edge for Athleisure Brands (and Where It Doesn't)
Real productivity, not AI theater. Here's where it actually moves a number for athleisure brands.
Creative
What AI does: AI-assisted creative briefing and rapid iteration: generating multiple hook angles, copy variations, and visual concepts per week so the team can test at TikTok's required velocity rather than producing one creative set and hoping it holds.
The result: More creative concepts tested per week means finding the hooks that drive purchases faster, and retiring underperforming creative before it drags down ROAS, instead of running the same ad until the algorithm buries it.
Why it matters here: In athleisure, creative IS the product demo. A legging ad that doesn't show the fabric moving, doesn't address squat-proof performance, and doesn't match the aesthetic of the specific fitness tribe you're targeting will not convert, no matter how well the campaign is structured. The brands that can test 10 creative angles a week instead of 2 find the winning message before their competitors do.
Analytics
What AI does: Blended MER tracking and attribution monitoring across Meta, TikTok, Google, and email: catching the gaps between platform-reported ROAS and actual Shopify revenue, and flagging when a misfiring pixel or broken UTM is inflating numbers.
The result: Budget decisions made on accurate blended data instead of platform-reported last-click ROAS, which means spend goes where it's actually working, not where the dashboard says it's working.
Why it matters here: Post-iOS 14, the gap between what Meta reports and what actually happened in your Shopify backend can be 30–50% on some campaigns. An athleisure brand making budget decisions on platform numbers alone is flying blind. Catching a misfiring pixel early, before you've scaled spend against false data, is often the single highest-ROI intervention in the entire account.
Digital Ads
What AI does: AI-driven budget pacing and bid optimization across Meta and TikTok: shifting spend toward the campaigns, audiences, and creative combinations that are generating the strongest blended ROAS in real time, and pulling back from underperformers before they waste the week's budget.
The result: Ad spend that follows actual performance signals rather than a static monthly budget allocation, so the highest-converting creative and audience combinations get more fuel and the rest don't drain the account.
Why it matters here: Athleisure demand has real seasonality (the New Year's resolution spike, the Q4 holiday window, the August back-to-school lift) and CPMs spike during those same periods. A brand that can dynamically allocate budget toward what's working during a high-intent window captures more revenue per dollar than a brand running a flat monthly spend regardless of what the data is showing.
What AI does: AI-assisted Klaviyo flow optimization: segmenting post-purchase sequences by first-purchase product (hero SKU buyer vs. loss-leader entry point), personalizing win-back timing based on cohort LTV, and identifying which subscriber segments have the highest repeat purchase probability.
The result: Email and SMS that treats a $150 hero legging customer differently from a $30 entry-point customer from day one, building toward the 24-month LTV of each cohort instead of sending the same broadcast to everyone.
Why it matters here: Email generates 20–30% of DTC fashion revenue at $42–$45 per dollar spent: the highest-margin channel in the stack. For an athleisure brand with a meaningful return rate (24–50% is typical), the post-purchase sequence is also the primary tool for turning a returned-item customer into a retained one. Brands that automate this well build repeat purchase rate; brands that don't are perpetually paying to reacquire the same customer.
Conversion Optimization
What AI does: AI-reviewed product page and landing page analysis: identifying friction points in the path from ad click to purchase, testing size-guide placements, social proof positioning, and product video placement, with continuous monitoring rather than a one-time audit.
The result: Higher conversion rate on the traffic you're already paying to acquire, which directly improves blended ROAS without increasing ad spend.
Why it matters here: In athleisure, fit anxiety is the primary conversion barrier: a shopper who isn't confident the legging will fit or perform as described will add to cart and abandon. Brands that surface the right trust signals (UGC reviews, size-inclusivity callouts, return policy visibility) at the right moment in the product page convert a meaningfully higher share of paid traffic. A 32% conversion rate improvement on existing traffic, as Ravean achieved, changes the economics of every campaign in the account.
Ready to see what this looks like for your athleisure brands business?
No obligation. A senior strategist will show you exactly where the wins are.
The Strategy
How Paid Media Should Actually Be Run for an Athleisure Brand
The strategic mistake most athleisure brands make is treating Meta as the whole strategy and everything else as a side experiment. The right architecture treats each channel as doing a specific job, and measures the whole system on blended MER, not any single platform's reported number.
Meta (Instagram and Facebook) is your prospecting engine at scale. It reaches the broadest relevant audience and is where you build the top of funnel, but it requires a constant pipeline of fresh creative, because creative fatigue on Meta is measured in weeks, not months. Dynamic product ads with frequently refreshed UGC and influencer content are the mechanism; a static creative set is a slow bleed.
TikTok is the highest-upside discovery channel for athleisure specifically: the only category clearing a 2.49 ROAS on the platform. But TikTok rewards creator-native content, not repurposed Meta ads. Hooks need to rotate weekly. The brands winning on TikTok are treating it as a creative-first channel, not a placement to toggle on after Meta is 'figured out.'
Google Brand Search captures the high-intent buyers that Meta and TikTok created: the person who saw your legging on Instagram, thought about it for three days, and is now typing your brand name into Google. This channel should never be underfunded; it's capturing demand you already paid to generate.
Email and SMS are the LTV engine. Klaviyo flows (abandoned cart, post-purchase, win-back) are infrastructure, not campaigns. They should be segmented by first-purchase product and cohort, not batch-and-blasted. This is where a $150 hero-SKU customer gets treated differently from a $30 entry-point customer, and where repeat purchase rate is built or lost.
Influencer and UGC content is the creative input for everything else. Micro-influencers in specific fitness niches (Pilates, trail running, functional fitness) consistently outperform mega-influencers on cost-per-conversion. Building a systematic pipeline of that content, rather than one-off influencer posts, is what separates brands with a creative advantage from brands that are always scrambling.
The one number that governs this
The governing KPI is blended ROAS: total revenue divided by total ad spend across every channel. Platform-reported ROAS is a directional signal, not a decision-making tool. Every budget conversation, every channel allocation, every creative test is evaluated against what it does to the blended number.
How We Help
What We'd Actually Do for Your Athleisure Brand
Here's how we'd sequence the engagement for a DTC athleisure brand. We don't run generic DTC playbooks. The strategy above is built for how athleisure brands actually grow, and the execution maps directly to it. We take on a limited number of clients so every account gets senior attention, and we measure our success by what happens to your blended ROAS and cohort LTV, not by how many reports we send you.
Attribution & Analytics Setup
Before we touch a dollar of ad spend, we fix the measurement layer: blended MER tracking, pixel health audit, UTM architecture, and Shopify revenue reconciliation against platform-reported numbers. Every decision we make after this is made on data you can trust.
Paid Social (Meta & TikTok)
We rebuild or restructure your Meta and TikTok campaigns around a creative-testing cadence that matches what those platforms actually reward: multiple hook angles per week on TikTok, dynamic product ads with fresh UGC on Meta, budget pacing tied to your seasonal calendar rather than a flat monthly allocation.
Creative Strategy & Production Briefing
We build the creative brief infrastructure: UGC briefs for micro-influencer partners, hook frameworks for TikTok, and a testing matrix so you know which creative angles are winning and why, not just which ad ID has the best number in the dashboard.
Google Ads (Brand Search & Shopping)
We make sure you're capturing the high-intent demand your paid social spend is generating: brand search campaigns that don't leak to competitors, and Shopping campaigns structured around your hero SKUs and margin tiers.
Email & SMS (Klaviyo)
We build or audit your Klaviyo flows (abandoned cart, post-purchase, win-back) and segment them by first-purchase product so your LTV-building automation treats a hero-SKU customer differently from a discount-entry customer from day one.
Conversion Rate Optimization
We review your product pages and landing pages for the friction points that kill athleisure conversions specifically (fit anxiety, size guide placement, UGC review positioning, return policy visibility) and test improvements continuously, not as a one-time project.
AI Systems & Reporting
We build the AI layer into the work where it creates real edge: automated creative performance monitoring, blended ROAS dashboards that reconcile platform data against Shopify, and audience segmentation signals fed by cohort LTV data, so the account improves continuously rather than only when someone manually pulls a report.
Who's Behind This
Who we are, and what makes us different
Sagum is a performance marketing agency founded in January 2017 in St. George, Utah. We've spent 8+ years growing real brands and being judged on KPIs, not vanity metrics.
We deliberately limit how many clients we take so each one gets senior attention. We treat your numbers like our own, we never run generic playbooks, and your strategy is built for your business, because shouldn't your brand's marketing be custom to your brand?
Sagum.ai is our AI arm: the same proven operators now build AI into the work wherever it creates real edge, not as theater, but as leverage applied with discipline.
- 8+ years growing brands on performance KPIs, not vanity metrics
- Limited client roster, with senior attention on every account
- An extension of your team; your success is tied to ours
- Custom strategy per brand, never a generic playbook
- AI built in where it moves a number; judgment over hype
“Sagum is a performance marketing agency that's spent 8+ years growing brands by treating their numbers like our own. We take on few clients, never run generic playbooks, and now build AI into the work wherever it creates real edge, not hype. Your strategy is built for your business, and our success is tied to yours.”
“Sagum roughly doubled our bottom line. They treat the work like it's their own business.”
Proof
$255k → $555k in 2 months, ROAS 2.9x → 5.5x+
Nickel & Suede
Challenge
Nickel & Suede, a DTC accessories brand, was generating revenue but had hit a ceiling on ROAS: the kind of plateau where more spend doesn't produce proportionally more return, and the creative library has been running long enough that the algorithm is working against you.
What we did
We rebuilt their Meta and TikTok creative strategy around rapid testing (multiple angles per week instead of a static set) and restructured the campaign architecture to let the best-performing creative combinations scale while cutting off the underperformers before they dragged down the blended number.
Result
Revenue went from $255k to $555k in two months. ROAS moved from 2.9x to 5.5x, peaking at 7.95x. Site conversion rate improved 34%. These aren't platform-reported numbers. They're what happened in the business. Full case study at sagum.com/case-studies/.
- Revenue
- $255k → $555k (2 mo)
- ROAS
- 2.9x → 5.5x+ (peak 7.95x)
- Site conversion
- +34%
If Your Blended ROAS Isn't Where It Should Be, Let's Find Out Why
No obligation. We'll look at your current channel mix, attribution setup, and creative cadence, and tell you honestly where the gap is. If we're not the right fit, we'll say so. If we are, we'll show you exactly what we'd do.
Sagum · January 2017 · St. George, Utah · 8+ years