Zalando.
Discovery is there, completion is not: HTTP hits an Akamai shell, the browser cannot reach an exact-variant bag publicly, and /checkout is session-gated.
Found & recommended by AI agents
Search-class agents touched the close in some runs; the full agent-fleet access profile lands in a later wave.
This page measures the commerce lane: can an agent find Zalando, and once it arrives, transact. Talent, after-sales, procurement, investor and press lanes run on different surfaces and are not yet measured.
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Discoverable, not completable. Sub-pilot finding, the session gate is the wall.
We asked five kinds of AI agent to add a Nike Air Max 90 in size 43 to a bag on Zalando. The reference lane reached the live cart URL with the variant at €134.95, but that state depended on a pre-existing session. A plain HTTP fetch returned an Akamai-gated 403 shell with no usable product-detail HTML for Phase 2. The coding agent did not have a stable, unauthenticated product-data surface from the approved entry URL. All three standard browser runs failed to achieve a validated size-43 add-to-bag state. The autonomous agent attempted public /checkout continuation and observed a session-dependent dead-end at /checkout returning the 'This page has gone out of style' page. One of five agent classes reached the close state; per G6 this is sub-pilot.
One label, many breeds. From a plain reader to an autonomous operator, the kinds behind ChatGPT, Perplexity, and Claude Code:
Blocked somewhere on the path: Plain reader, Coding agent, Computer-use agent, Autonomous operator. A customer whose assistant runs on one of those breeds never finishes the task.
Found, and able to transact?
Two questions, measured separately. A brand can be recommended and still un-buyable, or perfectly buyable and never found.
When someone asks an agent to buy a product, does it route to Zalando?
Zalando comes up about four times in ten. The rest of the time, an agent recommends an alternative first.
Discoverability · 18-datapoint auditOnce an agent is on Zalando's site, can it check out?
Search-class agents surface a working cart in some runs; the full agent-fleet access profile lands in a later wave.
Evidence · 70 / 100 A measure of how provable and consistent the result is, grounded in cross-method ground-truth agreement (the methods that ran returned the same price), not a separate measured run. A confidence layer on the two scores above, not a third sales axis.
What this means for Zalando.
Zalando is discoverable, not completable, for the agent classes we measured. The session gate is the wall: only the reference lane reached the cart, and only because the session was pre-warmed. For an agent arriving fresh, the size-43 add-to-bag path is brittle in the browser and unreachable via HTTP or coding paths. The exact-variant completion is the deal-breaker, not discovery.
Session-free completion mechanics, not catalog repair. An agent-callable variant-selection contract that holds without a pre-warmed bag, a /checkout endpoint that accepts a freshly-built cart from an authenticated agent, and citeable evidence that the buy path is reproducible from a cold start. Until that holds, discoverability without completion is the published story.
The proof is not more listings. It is the same Air Max 90 size-43 add-to-bag completing from at least three of five agent classes from a cold session start, re-measured.
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Marketplaces like Amazon capture 61% of shopping demand before Zalando.
Across the 18 Gate-1 responses, 61% routed the Air Max 90 question through a competing multi-brand surface (Amazon in 9, About You in 8, Nike.de in 6, Nike.com in 5, Foot Locker in 3, Snipes in 3); Zalando appeared in 6 of 18 (33%). Zalando is itself a marketplace-retailer hybrid, so the displacing peers are OTHER multi-brand surfaces, not Nike-as-a-brand. The Air Max 90 buy intent is fragmented across half a dozen surfaces, with Zalando one option among several.
Intermediaries Amazon · About You · Nike.de · Foot Locker · Snipes
Hyperize-selected tasks.
One task from the public sector grid. Task list is frozen before each wave runs.
Zalando — Nike Air Max 90 size 43 (bag) — sub-pilot probe
- Close state
- a working cart
- Bottleneck
- Ceiling-only access depends on a pre-warmed session; HTTP returns Akamai-gated shell; coding has no stable product-data surface; browser 0/3 on the size-43 variant; /checkout returns a 'gone out of style' dead-end without a live bag. Sub-pilot per G6 (1/5).
Fairness note
Wave 3 Slow Lane (a fleet wave Consumer Retail, sub-pilot). Single measured task (Nike Air Max 90 size 43 add-to-bag, cart_ready close state). The session-warmed reference (ceiling) lane reached the cart at €134.95, but HTTP / coding / all three standard browser runs / autonomous all fail from a cold start. G6 count is 1/5 with ceiling as a reach, 0/4 if ceiling is treated as provenance evidence only — below the G6 threshold either way, sub-pilot. AI Visibility 43.26 (18/18 valid datapoints across 3 providers); AI Usability low (derived from the cold-start access profile, not the session-warmed reference). Channel split grounded via channel-derive.py (competing multi-brand surfaces in 11/18, Zalando own-domain in 6/18). The page carries the Pilot probe chip and noindex via confidence=D — measured, but below the G6 threshold for a normal scored brand.
How the score was produced.
Discoverability is audit-pipeline-derived. 3-provider sample (openai, perplexity, anthropic), 3 query variants per task, 2 runs per variant · 18 valid datapoints scored against a five-state handoff cascade. [S1]
AI Usability is derived from the access-profile above (usability-derivation/v1): how far the best agent reached (close state) modulated by how many agent classes succeeded. The per-class profile is the truth; the score is a reproducible summary of it, not a separate rating. Fleet phases (HTTP / Coding / Browser / ACT) produce the profile. [S2]
Agent Success Score = (AI Visibility × 0.20) + (AI Usability × 0.70) + (Evidence × 0.10)
On a 0–100 scale, displayed 0–10. AI Usability bundles the agent's reach + completion; AI Visibility is audit-derived discoverability. Weighting is public; the per-prompt derivation is not.
Measurement scope
Confidence D · one measured task on a 3-provider track (openai, perplexity, anthropic). Confidence promotes to B with a second task plus a fourth provider on the next wave.
Measurement timeline.
Each wave appends; nothing overwrites. Frozen Wave Rule.
- Entry · 01
23 May 2026
Wave · ProtocolWAVE-Q2-2026-W3-SLOW
ars-methodology/v1.1
First v3 measurement. Discoverable-but-not-completable finding: the session-warmed reference (ceiling) lane reached the cart at €134.95, but the four cold-start agent classes (HTTP / coding / standard browser / autonomous) all fail. Direct /checkout returns the 'This page has gone out of style' page without a live bag. G6 count is 1/5 with ceiling counted as a reach, 0/4 if it is treated as provenance evidence only — below the G6 threshold either way. AI Visibility 43.26 (18/18 valid datapoints, 3 providers, DE). Shipped with confidence D (Pilot probe chip + noindex).
Evidence and provenance.
Public methodology references and internal evidence pointers behind every claim above.
- [S1]Accessed · 23 May 2026
Gate-1 audit run · Zalando Wave Q2 2026
Internal · Hyperize evidence
- · AI Visibility score 43.26 (18/18 valid datapoints across 3 providers)
- [S2]Accessed · 23 May 2026
Hyperize fleet · a fleet wave Consumer Retail (access profile)
Internal · Hyperize evidence
- · discoverable-but-not-completable finding (ceiling session-warmed reach; all other classes fail)
- · the close state attempted (cart_ready) and the dead-end (no_public_checkout_without_live_bag_session)
- · Five-Agents-Five-Answers passing 1/5, sub_pilot true
- Accessed · 23 May 2026
Public · hyperize.ai
- · fairness declaration
- · sub-pilot doctrine (G6)
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Task Selection.
The fairness doctrine behind the slate above. Five failure modes, six criteria, public before each wave.
Read ChallengeDisagree with this score.
Send evidence under public Fairness Review. Failed reviews are documented with the named failure mode.
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Open Surface Run · additive measurement. The Hyperize-selected slate stays frozen; your task gets the same methodology.
SubmitEditorial coverage
The DAX 40 Agent Success Index is a point-in-time snapshot of the agent-success of public digital touchpoints. Results are not statements about product quality, company performance, service quality, or the legal obligations of the brands named. Brand names and logos remain the property of their respective owners and are used solely for identification and reporting purposes in the context of editorial coverage (§ 23 MarkenG, Art. 5 GG).
Brands wishing to respond, engage, or correct a factual error may contact hello@hyperize.ai. Responses received are published in full alongside the findings. Full methodology and editorial-coverage notice: coverage statement.
