Merck.
A reference-grade B2B catalogue that text and code agents can't reach at all.
Found & recommended by AI agents
Can an agent use the surface to get the job done
This page measures two lanes. Commerce: can an agent find Merck, and once it arrives, transact. Talent: can a candidate's agent find an open engineering role on Merck's own career surface and prepare the application. After-sales, procurement, investor and press lanes run on different surfaces and are not yet measured.
Your brand isn't measured yet
What does an AI agent do with your website?
The same measurement as Merck, free for your domain. Five agent classes, one real task, your score in 48 hours.
A €154 reagent you can order with a browser, invisible to anything simpler.
We asked five kinds of AI agent to find an RNA-extraction kit for human whole blood at 200µl on Sigma-Aldrich. The plain reader's connection aborted before any response landed. The coding agent's curl returned HTTP 000, no file written. The browser navigated to sigmaaldrich.com/DE/de/product/sigma/t3809, identified TRI Reagent BD (catalog T3809), confirmed whole-blood compatibility, and added a 25mL, 100mL, and 200mL pack to cart, with the cart counter ticking from 0 to 1 and an alert confirming "1 Artikel wurde in den Warenkorb gelegt." No login required. The full-automation run completed the same flow.
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. A customer whose assistant runs on one of those breeds never finishes the task.
Scope. This is one reagent on one surface (Sigma-Aldrich). Merck Life Science sells hundreds of thousands of SKUs across reagents, chemicals, analytical, biopharma and lab equipment, each on parametric-search-driven product pages.
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 find and order a kit, does it route to Merck?
Merck 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 Merck's site, can it place the order?
Computer-use agent and Autonomous operator reach a working cart; the other agent classes do not.
Browser-class agents reach a working cart; text / code agents are blocked, final payment is a separate step · breakdown aboveHow far the agent actually got
Close state is cart-ready: the agent reached a working "Add to cart" with no login gate. The transaction path is real, not just order-ready. (Final payment is a separate step.)
Evidence · 68 / 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.
The talent lane.
A candidate's agent, sent to find an open software-engineering role at Merck and prepare the application. Same brand, second surface: the career portal.
Application-ready for agents.
Both non-browser agent classes read the full job posting and its structured JobPosting data directly from Merck's own career page; the application entry sits behind a SuccessFactors login wall that requires account creation before the form itself becomes visible.
Furthest close-state reached: application ready · frozen task locked 2026-07-02
The score above is provisional where a class shows untested: untested classes are excluded from the calculation, so the pending check can only confirm or raise the value, never silently lower it.
AI Visibility · in measurement — the audit run for this lane has not landed yet. No Talent-lane composite is shown until both axes are measured.
What this does not yet cover
This measurement did not test the application form itself, did not create an account, did not log in, and did not submit an application. Only the publicly reachable job-detail page (HTTP GET) and the public-facing sign-in gate of the apply entry (HTTP GET, no credentials entered) were measured. Whether the SuccessFactors form itself is agent-friendly once authenticated remains untested.
Fairness note
This measurement covers Merck KGaA, Darmstadt, and its brand-owned career site careers.merckgroup.com; it is not related to Merck & Co (MSD). Only the publicly reachable job-detail page for a real, open IT role (Req 297478, verified 2026-07-02) was read: no account was created, no form was opened, and no application was submitted. The account requirement before the application form is documented as a fact of the SuccessFactors process and does not reduce the score; browser-based agents were not tested in this run, and the usability figure reflects only the agent classes that were.
What this means for Merck.
On B2B life-sciences sourcing, Merck is not lacking a catalogue, T3809 carries the kind of structured product data the Hyperize cookbook calls reference-grade. It is losing the agent classes that don't run a browser. WAF protection at sigmaaldrich.com aborts the HTTP connection before any product content is served, the simpler agents that LLM tools call out to first see nothing. A specifier who lets ChatGPT do the lookup against a text-only fetcher gets routed to Qiagen, Thermo Fisher, or Bio-Rad by default.
The fix is not removing WAF, the security trade-off is real. It is publishing the catalogue's agent-readable shadow alongside it: Reference Pages per high-traffic SKU carrying spec + price + cart URL in plain HTML, Answer Pages for the parametric questions a buyer asks ("Welches Kit für RNA aus Vollblut?"), Concept Pages for the technique vocabulary so the brand owns the terms upstream of product selection.
The proof is not a new commerce flow. It is plain readers and coding agents extracting "T3809, TRI Reagent BD, whole blood compatible, €154/25mL, add-to-cart URL" directly, alongside the existing browser path, re-measured each wave.
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The same measurement runs free against your domain: five agent classes, one real buying task, your Agent Success Score in 48 hours, in the exact format of this page.
No intermediary stands between agents and Merck. The gap is being found, not the channel.
Channel position derivation on the Wave 5 the AI Visibility pass response texts is queued; the displayed share values are the unmeasured default. The measured task closes directly on Sigma-Aldrich (Merck's own catalogue), so the close-state is brand-owned rather than intermediated; the discovery competition with peer catalogues (Qiagen, Thermo Fisher, Bio-Rad) will be characterised in the next pass.
Hyperize-selected tasks.
One task from the public sector grid. Task list is frozen before each wave runs.
TRI Reagent BD T3809 for whole-blood RNA extraction (200µl)
- Close state
- a working cart
- Bottleneck
- WAF blocks the plain reader and coding agent at the connection layer; browser and full automation reach the cart without login.
Fairness note
Wave 5 Q2 2026 audit complete on a single task (TRI Reagent BD T3809, cart-ready close state). AI Visibility from the audit pass on an unbranded informational probe (RNA-Extraktion-Vollblut-Lab-Anbieter). AI Usability from a fleet wave (2026-04-07) full phase 1-4. 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
07 Apr 2026
Wave · Protocola fleet wave
fleet/measured
First-pass FLEET measurement: TRI Reagent BD T3809 on Sigma-Aldrich across ceiling + http + coding + browser-agent + act breeds. Found connection-layer blocking for text/code agents (HTTP 000); browser success 3/3 with Score 96.3 average; ACT cart-ready with no login gate.
- Entry · 02
24 May 2026
Wave · ProtocolWAVE-Q2-2026-W5-LIFE-SCIENCES
ars-methodology/v1.1
Wave 5 kickoff. AI Visibility audit running on unbranded informational probe (RNA-Extraktion-Vollblut). AI Usability carried from a fleet wave full phase 1-4 access profile.
Evidence and provenance.
Public methodology references and internal evidence pointers behind every claim above.
- [S1]Accessed · 24 May 2026
AI Visibility audit · Merck Wave Q2 2026 (unbranded informational)
Internal · Hyperize evidence
- · AI Visibility score (audit-derived, 18 datapoints, 3 providers)
- · AI platforms queried (openai/perplexity/anthropic)
- · close state reached (cart_ready)
- [S2]Accessed · 07 Apr 2026
Agent-fleet run · Life Sciences · Merck phases 1-4
Internal · Hyperize evidence
- · per-class access profile (text/code blocked at connection layer; browser success 3/3; ACT add-to-cart no login)
- · WAF finding (HTTP 000 timeout for both text and coding agents)
- · cart-ready ACT (Warenkorb 1 + alert 'Artikel wurde in den Warenkorb gelegt')
- [S3]Accessed · 07 Apr 2026
Ground-truth ceiling run · TRI Reagent BD T3809 specification
Internal · Hyperize evidence
- · Ground-truth catalog number (T3809)
- · Whole-blood compatibility, 25mL/100mL/200mL pack sizes, €154/€472/€863 pricing
- Accessed · 24 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.
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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.
