Vonovia.
On the unbranded question the portals capture the search.
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 Vonovia, and once it arrives, transact. Talent: can a candidate's agent find an open engineering role on Vonovia'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 Vonovia, free for your domain. Five agent classes, one real task, your score in 48 hours.
Portals own the unbranded search. The landlord surface itself is agent-ready end to end.
We asked five kinds of AI agent to find a 3-room rental in Munich under €1,500 cold and start a landlord contact on vonovia.de. A plain HTTP fetch read the Kaltmiete (€1,891), Warmmiete (€2,150), and address from the SSR listing without JS execution. The coding agent extracted the same listing data. The standard browser reached the listing detail in two of three runs; the only drop was the homepage search-to-listing handoff. The autonomous agent reached the contact overlay with all six visible inquiry fields and the 'Absenden' submit button. Five out of five agent classes reached at least the listing; the inquiry overlay opened end to end without authentication.
One label, many breeds. From a plain reader to an autonomous operator, the kinds behind ChatGPT, Perplexity, and Claude Code:
Scope. This is one listing in one city. Vonovia operates hundreds of thousands of units across Germany, each with its own listing and inquiry flow.
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 a property, does it route to Vonovia?
Vonovia 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 Vonovia's site, can it book a viewing?
Plain reader and Coding agent and Autonomous operator reach contact-ready; Computer-use agent get there only in some runs.
Browser-class agents reach contact-ready; browser-class agents reach it only partially · breakdown aboveEvidence · 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.
The talent lane.
A candidate's agent, sent to find an open software-engineering role at Vonovia and prepare the application. Same brand, second surface: the career portal.
Readable posting, unresolved apply step.
Both non-browser agent classes read the posting and locate the application entry; how far the form itself carries without JavaScript was not part of this pass.
Furthest close-state reached: spec match · frozen task locked https://jo
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 attempt or complete an actual application submission. No form was filled in, no account was created or logged into, and no data was submitted to Vonovia at any point. The apply dialog's login requirement and required artifacts (CV, cover letter, form length) remain unverified because they only render after the client-side JS dialog is triggered, which is out of scope for the HTTP/coding measurement class.
Fairness note
Vonovia hosts its job postings directly on its own careers site, so this measurement required no detours via subsidiaries or job boards, and machine-readable agents could retrieve the full tested posting and its structured data on the first request. Software roles are a small minority of Vonovia's hiring, which is dominated by trades, facility and administrative positions; the IT role was chosen solely to keep the test identical across all 40 companies. Browser-based agents were not tested here, so the finding that automated requests cannot reach the application form applies only to the agent classes actually tested, and no application was ever submitted.
What this means for Vonovia.
On product discovery, Vonovia is not failing on the surface; the listing reads clean and the inquiry overlay opens for every measured agent class. It loses at the entry point: the unbranded Munich-rental question routes to ImmoScout24 and Immowelt before it routes to Vonovia. Found via the portals, completed by every agent that arrives.
Discovery packaging, not surface repair. Answer Pages for the rental questions a tenant asks before naming a portal, Concept Pages that own the landlord-vs-portal vocabulary, Reference Pages that concentrate Vonovia's per-city listing authority, so the unbranded Munich question names Vonovia before ImmoScout24 frames the shortlist.
The proof isn't more listings. It's agents surfacing Vonovia on broad rental prompts, not only when the landlord is already named, re-measured each wave.
Commission an audit.
Where the BrandScore opens the question, an audit closes it. An interpretive engagement on your full surface, scored under the same methodology.
Get the auditFound with us.
Strategic partnership for brands building agent success as a long-term capability, not a one-off engagement.
ApplyAudit an adjacent property.
The BrandScore covers the primary domain. Get the same methodology applied to an adjacent property: a country site, a sub-brand, a category beyond the DAX-40 slate.
Get a SnapshotThis is Vonovia. What about your brand?
You just saw how an AI agent treats a DAX 40 brand.
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.
Listing portals capture 83% of property demand before Vonovia.
Across the 18 AI Visibility responses, 83% routed the Munich-rental question through a displacing portal (Immowelt in 14, ImmoScout24 in 11, wg-gesucht in 11, Kleinanzeigen in 9); vonovia.de was named directly in 9 of 18 (50%). The portals dominate the unbranded informational probe; on the branded comparative and transactional probes vonovia.de appears alongside them. Vonovia and Scout24 share the identical informational probe ('Wie finde ich eine 3-Zimmer-Mietwohnung in München bis 1.500 Euro kalt?'), so the contrast measures whether agents surface the landlord or the portal on a single query: the portal mentions outnumber landlord mentions by a wide margin.
Intermediaries Immowelt · ImmoScout24 · wg-gesucht · Kleinanzeigen
Hyperize-selected tasks.
One task from the public sector grid. Task list is frozen before each wave runs.
Vonovia — 3-Zimmer-Mietwohnung München (Kontakt)
- Close state
- contact-ready
- Bottleneck
- HTTP reads Kaltmiete + Warmmiete + address from SSR; coding extracts the same; standard browser 2/3 (drop is homepage search-to-listing handoff); autonomous agent opens the landlord-owned inquiry overlay end to end. All five agent classes reach at least the listing. The dominant gap is discovery: the unbranded query routes to ImmoScout24 and Immowelt.
Fairness note
Wave 3 Slow Lane (a fleet wave Real Estate). Single measured task (3-Zimmer-Mietwohnung in München bis 1.500 Euro kalt, contact_ready close state via landlord-owned inquiry overlay). AI Visibility 42.78 (18/18 valid datapoints across 3 providers, unbranded informational + branded comparative + branded transactional); AI Usability derived from a fleet wave per-class access profile (5/5 agent classes reach the listing; 2/3 standard browser runs reach listing detail; the autonomous agent opens the contact overlay end to end). Channel split grounded via channel-derive.py (intermediary in 15/18 AI Visibility responses, own-domain in 9/18). Confidence C, single task; 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
23 May 2026
Wave · ProtocolWAVE-Q2-2026-W3-SLOW
ars-methodology/v1.1
First v3 measurement. AI Visibility 42.78 (18/18 valid datapoints, 3 providers, DE, unbranded informational + branded comparative + branded transactional). AI Usability derived from a fleet wave per-class access profile (5/5 agent classes reach listing; HTTP reads SSR listing; coding extracts; standard browser 2/3 reaches listing detail; autonomous agent opens landlord-owned inquiry overlay end to end). The unbranded informational query is intentionally identical to Scout24's, so the Third-Party Interception contrast measures landlord-vs-portal surfacing on a single probe (15/18 portal capture, 9/18 landlord direct). Confidence C, single task.
Evidence and provenance.
Public methodology references and internal evidence pointers behind every claim above.
- [S1]Accessed · 23 May 2026
AI Visibility audit · Vonovia Wave Q2 2026
Internal · Hyperize evidence
- · AI Visibility score 42.78 (18/18 valid datapoints across 3 providers)
- · Third-Party Interception read (15/18 portal capture, 9/18 landlord direct mentions)
- [S2]Accessed · 23 May 2026
Hyperize fleet · a fleet wave Real Estate (access profile)
Internal · Hyperize evidence
- · how each kind of agent fared (HTTP reads SSR listing, coding extracts, browser 2/3, ACT opens inquiry overlay)
- · the close state reached (contact_ready, landlord-owned inquiry overlay visible)
- · the tested product (3-room Munich rental, Kaltmiete €1,891, Warmmiete €2,150)
- · Five-Agents-Five-Answers passing 5/5, sub_pilot false
- Accessed · 23 May 2026
Public · hyperize.ai
- · fairness declaration
- · Third-Party Interception framing
Read the doctrine. Challenge the score. Extend the slate.
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.
Challenge ExtendSubmit your own task.
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.
