of ecommerce carts get abandoned before checkout finishes
19%
of those shoppers cite a forced account as the reason
$260B
estimated recoverable yearly across US and EU ecommerce
Source: Baymard Institute, cart abandonment research, 2026
peelingretail.com
Launch CalendarNew ArrivalsMenWomenSneakersSale
0
Day 1Browses, adds to bag
Day 1Saves size and favorite
Day 3Returns, cart intact
Day 3Joins Rewards
One continuous thread. Auth0 held the identity the entire time, Peeling Retail never had to ask her to start over.
Why this matters
Business value
No signup wall between a visitor and the product, even on a high-traffic release day when the wall hurts most
A full cart that survives a walked-away visit is a recovered sale, not just a UX nicety
Merging a guest cart into an existing Peeling Rewards account removes the last reason a returning shopper bounces
Favorites carry over too, giving the ecommerce team a read on real intent before she's even a customer
A consistent anon@ identity gives the ecommerce team a real funnel to measure, pre-signup
Technical detail
POST /anonymous/token issues a session token (persisted client-side) and an access token for your APIs
Session data surfaces in pre-user-registration and post-login Actions as event.anonymous_session
Merge logic is yours to write. Auth0 exposes the data, your Action decides how it's reconciled
Recommended: 30+ day session lifetime, JWE encryption on the session, least privilege scopes for anon@ subjects, and an explicit /anonymous/logout call, so nothing lingers by default
Size the opportunity for Peeling Retail
Uses your own numbers, not ours
$
28,000abandoned checkouts a month 70% average, Baymard Institute
5,320cite a forced account as the reason 19% of abandoners, Baymard Institute
$505,400AOV-weighted opportunity a month
This is the size of the opportunity, not a guaranteed recovery number. Actual results depend on execution.
What's next: an AI shopping agent
Concept, not built
The same anonymous identity that carries a cart across a visit is what an AI shopping agent would need to act on a shopper's behalf, before she's ever signed in. That's the natural next step once this foundation is in place, and there's a whole second tab walking through five different moments like that, including exactly where Auth0 fits underneath each one.
Peeling RetailAI Shopping Agent, Exploratory
Concept, no committed scope yet
There's no exact use case locked in yet, and that's the point of walking through this together. Here's what a customer-facing AI agent could plausibly do for a retailer like Peeling Retail, built on the same identity work from the walkthrough on the other tab, and specifically where Auth0 needs to sit underneath it.
$1T
projected US retail revenue moving through agentic commerce by 2030
30%
average customer service cost reduction across enterprises using AI for tier-one support
10 to 30%
revenue and retention lift from personalization, once fully implemented
Sources: McKinsey & Company, agentic commerce research, 2025. IBM, Cost of a Customer Service Interaction report, 2025 (412 enterprises). McKinsey, personalization research. Industry benchmarks, not Peeling Retail-specific figures.
Five plausible moments, not a locked roadmap
The other tab opened on a simple number: 70% of carts get abandoned, and most people never come back on their own. The first one below picks up right there. The rest build on things already established earlier, her favorites, her Rewards status, her cart, rather than inventing a new story. Click into any of them to see exactly which Auth0 capability makes it possible.
01
The cart that doesn't wait for her to come back
Illustrative only
Hey, you left the Highlight Runner in your bag yesterday. Still in stock in your size, want me to finish checkout, or hold it a bit longer?
Hold it, I'm still deciding
No problem. I'll check back in a couple days if you haven't been back.
User AuthenticationToken Vault
This is the same cart Anonymous Sessions already protects. It would still be waiting for her on day three even if nobody reached out, and that's the entire point of the walkthrough on the other tab. What an agent adds is initiative: instead of waiting for her to come back on her own, it reaches out first. Same identity, same session, just used proactively instead of passively.
02
The proactive nudge
Illustrative only
Still thinking about the Team Fleece Hoodie you saved? It's back in stock in your size.
Actually yes, does the Fairview store have it?
It does. Want me to hold it, or add it to your bag for checkout now?
User AuthenticationToken Vault
The agent knows this is Riley, and what she favorited, because it inherited her Peeling Rewards identity. Checking live stock happens through a short-lived Token Vault credential instead of a password the agent has to hold onto.
03
Release day, stock and pickup
Illustrative only
The Highlight Runner just dropped in your size. Want me to grab one before the Launch Calendar traffic hits?
Yes, hold it for pickup today.
Done, ready after 4pm at Fairview. Since this is your first order, I applied your 15% Rewards welcome offer too.
User AuthenticationToken Vault
Same two pieces as the first scenario, identity and secure API access, just under release-day pressure instead of a quiet afternoon. The agent still isn't holding raw credentials to check inventory or apply an offer.
04
Rewards balance, and a return
Illustrative only
How many points do I have, and am I close to VIP?
180 points, MVP tier. 20 more gets you to VIP, and VIP earns 1.5x points instead of 1x.
The Highlight Runner didn't fit, can you start a return on that?
Starting that now, but a return over $50 needs your quick approval first, sending a confirmation to your phone.
User AuthenticationToken VaultCIBAFine-Grained Authorization
The moment that matters most. The agent doesn't process the return on its own. CIBA pauses for a real human approval before anything consequential happens. Fine-Grained Authorization means it only ever sees Riley's own order history, never anyone else's, even if the conversation gets manipulated.
05
The upsell that's actually earned
Illustrative only
Since you're picking up the Highlight Runner today, want some moisture-wicking socks with it? Members who buy this shoe usually add these, and it'd put you 20 points from VIP.
Sure, add them
Done, that's 205 points. Welcome to VIP, earning at 1.5x starts now.
User AuthenticationFine-Grained Authorization
This is the revenue side of the story. Cost avoidance is only part of it. The recommendation works because the agent can see Riley's own purchase pattern and real Rewards progress, rather than guessing generically. Fine-Grained Authorization is what makes it safe to hand the agent that much visibility into one specific customer's history.
Most of these moments are about removing friction and cost. The upsell is what completes the case: the same identity data that keeps an agent safe also makes its recommendations worth acting on.
What could go wrong without it, and how Auth0 prevents it
Without a proper identity layer
The bot can't reliably tell Riley from a stranger, so it either re-verifies constantly or trusts whoever's typing
A manipulated conversation could expose someone else's order history or Rewards balance
Nothing stops the bot from taking a consequential action, like a refund, entirely on its own
No clean record of who actually approved what, if something goes wrong later
With Auth0 underneath it
User Authentication: the bot always knows exactly who it's talking to, guest or Rewards member
Fine-Grained Authorization: scoped to that person's own data, nothing crosses over
CIBA: anything consequential pauses for a real human approval first
Token Vault: the bot calls Peeling Retail's systems with short-lived tokens, never a raw password or API key
What this could be worth, cost and growth
Uses your own numbers, not ours
The savings above are one part of the picture. Done well, the same identity foundation drives more revenue too.
Cost avoided
$
$600,000estimated annual savings at a 30% reduction IBM, 2025, average across 412 enterprises. Top-quartile programs report cutting costs by as much as 53%, per McKinsey.
Revenue potential
$
$4.0M to $12.0Mpotential lift at a 10 to 30% personalization uplift McKinsey, personalization research. Range covers both incremental revenue and improved retention, not one single lever.
Not a commitment, just a rough estimate. Actual results depend heavily on scope and execution.
What this is, and isn't
The identity and authorization layer underneath an agent is the same Anonymous Sessions and Auth0 foundation from the walkthrough. It works whether the first real use case ends up being a stock-check assistant, a loyalty concierge, or something else entirely, so nothing here depends on having that locked in today. Once the shape is clearer, we can scope it properly together.