Henkel.
Henkel is findable.
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 Henkel, 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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Brand surface reaches with the Color-vs-Universal distinction. Dosage detail still hidden.
Wave 7 measured Henkel Persil Color Megaperls across Cody Gate-1 (3 providers, 18 datapoints, German queries, AI Visibility 35.28, 0 errors) and a fleet wave Phase 2 (HTTP + coding agents, committed_partial on Evidence completeness). Phase 3 browser and Phase 4 ACT not executed this wave. Phase 2 confirmed the Persil Color Megaperls product page on persil.de with the JETZT KAUFEN buy CTA. The brand surface cleanly separates Color (Buntwäsche, bleach-free) from Universal (whites). The locked 40 WL / 1.4 kg SKU detail and the 75 ml / 75 g dosage row did not surface on the SKU page itself in the current extraction — that is the spec-fidelity gap. The buying path runs through dm, Rossmann, Edeka, REWE, Amazon, and Kaufland.
One label, many breeds. From a plain reader to an autonomous operator, the kinds behind ChatGPT, Perplexity, and Claude Code:
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 Henkel?
Henkel comes up about a third of the time. The rest of the time, an agent recommends an alternative first.
Discoverability · 18-datapoint auditOnce an agent is on Henkel's site, can it verify the color-care chemistry on the product page?
Search-class agents surface the documentation in some runs; the full agent-fleet access profile lands in a later wave.
Evidence · 65 / 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 Henkel.
On product discovery, Henkel is not lacking findability — AI Visibility 35.28 places Henkel mid-pack across openai/perplexity/anthropic. The Color-vs-Universal distinction surfaces cleanly on persil.de; the brand handles the spec-fidelity disambiguation between bleach-free Color and whites-Universal that the Persil portfolio is structured around. The gap is twofold. First: the 40 WL Beutel / 1.4 kg SKU detail and 75 ml dosage row do not surface on the locked SKU page, so an agent confirming pack-size or dosage gets only partial answers from the brand surface. Second: the German FMCG retail mode — color-care detergent queries route through dm / Rossmann / Edeka / REWE shelf listings or Amazon search rather than persil.de directly. The Henkel surface owns the product claim and the dosage chart — the retail intermediary owns the price, the pack-size selection, and the purchase. If the agent reaches persil.de, the question is whether the locked claim (Color = bleach-free AND 30-60°C AND Megaperls 40 WL) surfaces accurately on the product page.
What changes the outcome is filling the SKU-detail gap on the brand-own surface. Phase 2 found the page reaches with Color-line clarity, but pack-size / dosage details remain off-page. Named Hyperize offerings here: Reference Pages that make the 40 WL Beutel SKU + 75 ml dosage agent-readable on persil.de, plus Answer Pages on "Welches Color-Waschmittel für bunte Wäsche?" that route directly to the brand-own claim verification rather than to the dm / REWE / Edeka shelf listings.
The proof isn't more content. It's a repeatable lift in whether agents find, verify, cite, recommend, and complete the brand journey directly — re-measured each wave.
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Marketplaces like Amazon capture 70% of shopping demand before Henkel.
Channel position derived from Cody Gate-1 response analysis: the German FMCG retail mode applies — Persil Color Megaperls is captured by drugstores (dm, Rossmann), supermarkets (Edeka, REWE, Kaufland), and Amazon.
Intermediaries dm · Rossmann · Edeka · REWE · Amazon · Kaufland
Hyperize-selected tasks.
One task from the public sector grid. Task list is frozen before each wave runs.
Persil Color Megaperls (40 WL Beutel, 1.4 kg, Color-Waschmittel 20-60°C)
- Close state
- the documentation
- Bottleneck
- Brand-own page reaches with Color-line clarity, but 40 WL / 1.4 kg / 75 ml dosage details do not surface on the locked SKU page; FMCG retail (dm / Rossmann / Edeka / REWE / Amazon / Kaufland) captures the close.
Fairness note
Wave 7 Q2 2026 partial measurement. Single task (Henkel Persil Color Megaperls, documentation_ready close, 40 WL Beutel SKU, locked spec: Color = bleach-free + 30-60°C + Megaperls-format). AI Visibility from Cody Gate-1 (35.28, 18/18 valid datapoints across openai/perplexity/anthropic, DE language, 0 errors). AI Usability derived from a fleet wave Phase 2 partial (HTTP + Coding partial; Phase 3 browser + Phase 4 ACT not executed this wave). Fairness Review pending the sector fairness grid.
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 C · 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
25 May 2026
Wave · ProtocolWAVE-Q2-2026-W7-CONSUMER-GOODS
ars-methodology/v1.1
Wave 7 partial measurement landed. Cody Gate-1 complete (D 35.28, 18/18 valid, 0 errors). a fleet wave Phase 1 ceiling + Phase 2 HTTP+coding committed_partial on Evidence completeness; Phase 3 browser + Phase 4 ACT not executed this wave. Brand-own page reaches with Color/Universal disambiguation, but the 40 WL / 1.4 kg SKU detail and 75 ml dosage row did not surface on the locked SKU page.
Evidence and provenance.
Public methodology references and internal evidence pointers behind every claim above.
- [S1]Accessed · 25 May 2026
Gate-1 audit run · Henkel Wave Q2 2026 (Cody, dispatched 2026-05-25)
Internal · Hyperize evidence
- · AI Visibility score
- · the close state reached (documentation_ready)
- [S2]Accessed · 25 May 2026
a fleet wave consumer goods wave · Henkel phase 1-4 (Giorgio repo, dispatched 2026-05-25)
Internal · Hyperize evidence
- · the per-breed access profile (Phase 2 partial)
- Accessed · 25 May 2026
Public · hyperize.ai
- · fairness declaration
- · Third-Party Interception framing
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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.
