Turning “Launch Commerce” Into a Growth Engine: Lessons from EQL's Andrew Lipp

E-commerce is generally efficient—and predictable. Launches are not.

They spike traffic, test your infrastructure, attract bots and make or break brand trust in minutes. Andrew Lipp, Co-Founder and CEO at EQL calls this world launch commerce and he’s built EQL to run it well: fair drops, clean data, fewer bad actors, more loyal customers.

Why launches need their own playbook

Traditional storefront flows break under launch pressure. Bots swarm. Inventory misallocates. Support queues explode. This isn’t edge case—it’s fairly normal.

• Bots can dominate hot drops. In one large sneaker release, automated traffic represented >99.8% of visits, dwarfing humans.

• Shoppers will trade speed for fairness. 87% prefer a reliable site with a short wait over instant access that crashes. Average willingness to queue: 53 minutes for a fair shot.

• Checkout friction is deadly. Global cart abandonment still sits around ~70%—fixes to flow and fairness move real dollars.

EQL treats launches as a distinct system: protect the experience, reward real fans, capture demand signals you can actually use.

What success really looks like (not “sold out in 90 seconds”)

Measure the stuff that predicts future revenue:

1. Experience & uptime. Smooth and fair beats “viral but broken.”

2. Demand vs supply capture. Clean curve, no oversells, no ghost orders.

3. Loyalty mix. % to members, VIPs, in-store regulars — and how many net-new.

4. Sentiment. Quiet comments and “lost but felt fair” replies are wins.

5. Operational load. Fewer people, fewer days, fewer fire drills.

6. Halo revenue. Track the lift around the drop window, not just the SKU.

Shopify brands: enterprise-grade drops without the war room

You don’t need a large enterprise launch team to run a great launch. Shopify already handles massive peaks — 40k checkout starts per minute per store and 99.99% checkout uptime during BFCM-scale events — and processed $11.5B over BFCM 2024 alone. Build on that.

What EQL adds that makes a big difference:

• Exclusive access via segments or lists

• Gated races when speed is the story

• Automated draws when fairness is the story

• Smart waitlists to score intent and trigger follow-ups

Make your launch data do something useful

The point isn’t another dashboard. It’s sequences that improve the experience for both sides.

• Nurture the 90. If 100 enter for 10 units, 90 raised their hand. Give them next access, an invite in-store, or a targeted offer.

• Predict LTV. Identify profiles that typically become high-value and accelerate their path.

• Cross-pollinate. Use overlap signals to plan collabs that actually land.

• Right-size supply. If demand outstrips inventory 10:1, plan a restock without killing desirability.

A 30-day product launch plan

Week 1 — Pick the wedge
Choose a product with real community heat. Define success beyond “sold out”: loyalty %, net-new %, halo sales, CS tickets.

Week 2 — Set the rules
Decide draw vs race. Map VIP lists. Write the “lost but felt fair” email now.

Week 3 — Instrument & rehearse
Dry-run confirmations and let-downs. Capture sentiment with a one-question survey.

Week 4 — Launch, learn, amplify
Go live. Trigger your “Nurture the 90” sequence immediately. Publish fairness stats and the next access date.

Use Lucky Orange to de-risk the drop page

Traffic is expensive. Don’t send it into a leaky funnel.

• Heatmaps to confirm the primary CTA is obvious on mobile and desktop

• Segment comparisons to see how VIPs vs non-VIPs behave

• Funnels to spot step-level falloff during the launch hour

• Discovery prompts that cut through fog fast:

  • “Compare UTM tagged VIP vs non-VIP behavior on the launch page for the last 7 days. What’s different?”

  • “Why did mobile signups dip during the drop hour?”

  • “Where are rage clicks spiking in the flow and what’s the likely fix?”

Re-run the same prompts post-launch to show improvements and quantify halo revenue.

Copy-paste assets you can ship

Fairness statement snippet
“We’re running a [draw/race]. Entries are one per person. Winners are selected with [method]. We’ll email results by [time]. Didn’t win? Here’s what’s next: [offer or next access].”

Support macro
“Thanks for entering. We use a fairness system to block automation and reward real customers. You can read how it works here: [policy link]. If you didn’t win this time, you’ll get [benefit] on the next drop.”

Post-drop stats block
“Entries: [#]. Inventory: [#]. % members served: [#]. Queue wait median: [mm:ss]. Error rate: [<X%]. Next access date: [date].”

Why this matters right now

• Launches invite outsized bot pressure — plan for it.

• Shoppers will wait for fairness — earn the trust dividend.

• Fixing friction in checkout fights the ~70% abandonment drag that follows every spike.

• Shopify’s infrastructure can take the punch. Your launch layer decides whether you turn the punch into loyalty and LTV.

Listen to the full episode with Andrew Lipp on The Lucky Orange Show and steal what works for your next drop. Then tell us what you shipped — we’ll feature the best runs on the blog.