New collection launch analytics: The first 14 days playbook

The first two weeks after a collection launch determine its trajectory. Strong starts build momentum—bestsellers emerge, marketing finds its footing, and inventory decisions become clear. Weak starts require immediate intervention before problems compound. Either way, you need to know which situation you’re in.

Most fashion brands check sales numbers during launch week but lack systematic approaches to interpreting them. Is 50 units in three days good or bad? Does slow traffic mean marketing failed or timing was wrong? When should you intervene versus wait? Without a framework, these questions get answered by gut feeling instead of data.

This playbook covers exactly what to measure during the first 14 days, when to measure it, and how to turn those measurements into decisions.

Why the first 14 days matter

Collection performance curves get established early. Products that start strong typically stay strong. Products that start slow rarely recover without intervention. The first two weeks don’t just indicate performance—they often determine it.

Early data enables meaningful action. Discovering a bestseller in week one lets you consider reorders before stockouts. Discovering a problem in week one allows fixes before the season window closes. Discovering either in week eight means options have narrowed.

Your team’s energy and attention are highest at launch. Capitalize on this by channeling focus toward the metrics that matter. Knowing exactly what to watch prevents scattered analysis and enables decisive action.

Pre-launch preparation

Effective launch analytics start before launch. Set up tracking, establish benchmarks, and align your team on what you’re measuring.

Define success metrics

What does a successful launch look like? Set specific targets before you have data that might bias your judgment.

Revenue targets by day and week. Based on historical launches and marketing investment, what should this collection generate? Day one target, week one target, week two target.

Sell-through targets by milestone. What percentage of inventory should sell by day 7? Day 14? Use previous collection data to set realistic expectations. First-week sell-through of 10-15% is typical for mid-market fashion. Adjust based on your historical patterns.

Traffic and conversion benchmarks. How many sessions should launch marketing drive? What conversion rate do you expect? If you’re spending more on this launch, traffic should be proportionally higher.

Set up tracking

Ensure all tracking works before launch. UTM parameters on all campaign links. Conversion tracking verified. Analytics dashboards configured to show collection-specific performance.

Create a launch dashboard or report showing: daily revenue and orders, top-selling styles, traffic by source, conversion rate, and inventory levels for key items. You’ll check this daily—make it easy to read quickly.

Test everything. Click through your own campaign links. Place a test order. Confirm data appears correctly. Technical issues during launch week waste precious attention.

Establish your review rhythm

Decide when and how you’ll review data. Daily morning check-ins work for most teams. Icebug, the outdoor shoe brand that grew e-commerce 600%, describes their approach: “The first thing we do every morning is open our emails and check yesterday’s numbers. We compare the sales and order numbers with our goals and also keep track of which models are selling best and where our traffic is coming from.”

Assign ownership. Who reviews the data? Who makes decisions based on it? Who executes changes? Clear ownership prevents important signals from getting lost.

Days 1-3: Launch momentum

The first 72 hours reveal initial response. You’re looking for signs of momentum, not final judgment.

What to measure

Traffic volume versus expectation. Did launch marketing drive the sessions you planned? If traffic falls significantly short, investigate immediately. Email deliverability issues? Ad account problems? Website downtime? Traffic shortfalls on day one compound quickly.

Conversion rate versus baseline. Compare to your typical conversion rate, not to arbitrary benchmarks. If you normally convert at 2.5% and launch day shows 1.8%, something’s off. If launch day shows 3.2%, you’ve got a winner.

Email performance. Launch emails typically drive significant early sales. Open rates, click rates, and revenue per email all matter. Underperforming email suggests list fatigue, subject line issues, or offer problems.

Top performers emerging. Which styles generate first sales? Early bestsellers often stay bestsellers. Note them for potential marketing emphasis and inventory attention.

Action triggers

Traffic more than 30% below target: Investigate marketing execution immediately. Don’t wait.

Conversion more than 25% below baseline: Check site functionality, pricing display, and product page quality. Something is creating friction.

Zero sales on any style after 48 hours with decent traffic: Flag for review. Not necessarily a problem yet, but worth watching.

Any style exceeding 5% of inventory sold in 72 hours: Potential stockout risk. Begin reorder evaluation.

Days 4-7: Pattern establishment

By the end of week one, patterns emerge. Initial spike normalizes. Sustainable run rate becomes visible. Winners and potential losers differentiate.

What to measure

Daily revenue trend. Day one is always highest due to launch marketing. What matters is the decay curve. Revenue dropping 50% day over day is normal. Dropping 80% suggests launch spike without sustained interest.

Week one sell-through by style. Calculate units sold versus units available for each style. Rank them. Your top 20% and bottom 20% are now visible.

Traffic source performance. Which channels drove sales, not just visits? Email almost always wins on conversion. But did paid social contribute meaningfully? Did organic search pick up the new collection? Channel mix informs ongoing marketing investment.

Return rate early signals. Returns take time to process, but early return requests indicate problems. If a specific style shows multiple return initiations in week one, investigate fit, quality, or photography issues.

Customer mix. What percentage of launch buyers are existing customers versus new? Heavy existing-customer concentration suggests you’re reaching your base but not expanding. High new-customer percentage indicates acquisition channels are working.

Action triggers

Week one sell-through below 8% overall: Launch underperforming. Review marketing effectiveness, pricing, and product-market fit.

Week one sell-through above 18% overall: Strong launch. Consider accelerating marketing spend while momentum exists.

Any style below 3% sell-through: Underperformer identified. Evaluate merchandising position, photography, and pricing. Candidate for early promotional attention if issues can’t be fixed.

Any style above 25% sell-through: Stockout risk is real. Initiate reorder process immediately if feasible.

Return requests exceeding 5% of orders on any style: Quality or fit issue likely. Investigate before more inventory ships.

Days 8-14: Trajectory confirmation

Week two confirms whether week one patterns hold. Sustainable demand becomes clearer. Decision time approaches for underperformers.

What to measure

Week two versus week one revenue. Typical decay is 40-60%—week two generating 40-60% of week one revenue. Steeper decay suggests launch-dependent demand without organic interest. Flatter decay indicates sustained appeal.

Cumulative sell-through at day 14. Where does each style stand? Strong collections reach 20-30% cumulative sell-through by day 14. Weak collections struggle to hit 12-15%.

Marketing efficiency trends. Compare cost per acquisition in week two versus week one. Rising CPA suggests you’ve exhausted easy audiences. Stable CPA indicates room to continue spending. Declining CPA (rare) means momentum is building.

Organic traffic growth. Is unpaid traffic to collection pages increasing? Growing organic interest signals word-of-mouth and SEO traction. Flat organic traffic means you’re entirely dependent on paid promotion.

Size and color distribution. Are certain sizes or colors selling disproportionately? If medium sells out while small and large lag, you have size curve data for future buying. If one color dominates, note it for future collection planning.

Action triggers

Week two revenue below 35% of week one: Demand is fading fast. Reduce ongoing marketing spend. Prepare for earlier-than-planned promotional activity.

Any style still below 5% cumulative sell-through at day 14: Confirmed underperformer. Decide on action: merchandise repositioning, promotional pricing, or acceptance of eventual deep markdown.

Any style above 40% cumulative sell-through at day 14: Confirmed winner. Prioritize reorder if possible. Feature prominently in ongoing marketing.

Size stockouts occurring: Adjust remaining inventory allocation. Consider whether to reorder specific sizes or accept partial stockout.

Making decisions with launch data

Inventory decisions

Launch data enables smarter inventory action than waiting for end-of-season analysis.

Reorder decisions should happen by day 10-14 for styles showing breakout performance. Waiting longer means reorder inventory arrives too late in the season. Calculate: if current sell rate continues, when does stockout occur? Is there time for reorder to arrive and sell?

Markdown candidates identify early. Styles showing sub-5% sell-through at day 14 rarely recover without intervention. Begin planning promotional strategy rather than hoping for organic improvement.

Size rebalancing helps when certain sizes sell faster. If you can transfer inventory between channels or locations, move slow sizes to where they might perform better.

Marketing decisions

Double down on what works. If specific channels or creative approaches drove strong performance, increase investment there. Launch periods justify aggressive spending when data supports it.

Cut what doesn’t work. If a channel generated traffic but no sales, reduce spend. If certain ad creative underperformed, pause it. Launch budgets are too valuable for underperforming tactics.

Shift messaging based on bestsellers. If certain styles emerged as winners, feature them more prominently. Customer response tells you what resonates better than your pre-launch assumptions.

Product and merchandising decisions

Reposition underperformers on site. Maybe they’re buried in category pages. Maybe photography doesn’t show them well. Test different positions and presentations before assuming the product itself is wrong.

Update product descriptions based on customer signals. If questions consistently arise about sizing, fit, or materials, add that information to descriptions. Reduce friction that early customers revealed.

Document learnings for future collections. What worked? What didn’t? Why? These insights inform design, buying, and marketing for future launches.

Building your 14-day launch system

Create a repeatable process, not just one-time analysis.

Pre-launch checklist: Tracking verified, benchmarks set, dashboard ready, team aligned on review schedule and ownership.

Days 1-3 daily review: Traffic, conversion, email performance, early sellers. 15 minutes each morning.

Day 7 deeper review: Week one sell-through analysis, channel performance, customer mix, action decisions. 30-60 minutes.

Days 8-14 daily monitoring: Continue daily checks with awareness of week one patterns. Watch for confirmation or deviation.

Day 14 comprehensive review: Full performance assessment, confirmed winners and losers, documented decisions on inventory and marketing, lessons captured. 60-90 minutes.

Post-launch documentation: Record everything in consistent format. Future launches benefit from historical comparison. What benchmarks should you adjust? What worked that you should repeat?

Frequently asked questions

What if my collection launches without much marketing push?

Benchmarks shift but the framework applies. Without launch marketing, expect slower initial velocity but potentially steadier week-over-week performance. Judge against your owned-channel reach (email list, social following, organic traffic) rather than paid-inflated expectations. The patterns still emerge—just at lower volumes.

How do I handle launches across multiple markets or currencies?

Track each market separately with consistent metrics. A style might perform well in one market and poorly in another due to local preferences, pricing, or marketing differences. Market-level analysis reveals opportunities that aggregate numbers hide. Normalize currencies for overall reporting but preserve market detail for decisions.

Should I run promotions during the launch period?

Generally avoid heavy discounting in the first 14 days unless data clearly indicates problems. Launch buyers are often your most engaged customers—they’ll pay full price. Promotional activity during launch can train customers to wait for sales on future launches. Reserve promotions for styles with confirmed underperformance, not blanket launch discounts.

How does this framework adjust for different collection sizes?

Smaller collections (under 20 styles) allow style-level analysis for everything. Larger collections require tiering: watch top and bottom performers closely, sample-check middle performers. The framework scales by adjusting granularity of attention, not by changing what you measure or when.

Peasy emails your key metrics every morning—get visibility in 2 minutes instead of 15 minutes checking dashboards. Starting at $49/month. Try free for 14 days.