Verdicts at a glance
Channel strategy
InvestMeet guests inside OTA chat
48% picked OTA messaging — almost 2× any other channel. Native app sits at 11%.
Apple/Google Wallet
TestLikely win, but validate
44% “Yes,” 25% “Maybe.” 12% don’t know what Wallet is — needs awareness, not just shipping.
Personalization
Narrow“One place” beats AI recs
46% want consolidation; only 13% want recommendations. 28% reject the idea outright.
Language
InvestShip EN + DE; defer the rest
42% EN, 38% DE. Single-language coverage misses ~40% of guests. EN+DE covers 96%.
90%
Found check-in info successfully
48%
Prefer OTA chat as primary channel
44%
Want Wallet access to reservation
38%
Willing to share preferences
01 / Channel Strategy
Guests want stay info where their booking already lives.
OTA messaging dominates. Native app interest is the lowest of any channel — building one would compete with where guests already are.
Preferred channel for stay information
Multi-select · % of all respondents (n=103)
The pattern. Guests strongly prefer channels they already use for the booking itself — OTA chat (48%) and email (36%). Only 11% want a native Arbio app, and several explicitly said they wouldn’t install one.
What guests said about channel choice
I prefer everything on one app really because the first time you stay it’s difficult to get to your website bc Booking and other platforms block the website you provide.
It’s easiest to use the booking.com app since I already have it on my phone… if you have an additional Arbio app I would not download it.
All information in one app/platform, only one/few emails with a link to that page.
Is more practical. Don’t want to install numerous apps that I might use once a year.
02 / Wallet Integration
Wallet has appetite, but a third of users don’t recognize it.
Net interest is strong — but 12% don’t know what Apple/Google Wallet is, and another 25% are conditional. This is a “ship and educate,” not a “ship and forget.”
Excluding “Not sure what that is”
n=91 · users familiar with Wallet
Among guests who know what Wallet is, 50% say yes and 29% maybe — meaning ~79% positive signal. Among the full population, that drops to 69% because of the awareness gap.
03 / Personalization
Guests want consolidation, not recommendations.
When asked what would make a personalized stay valuable, “all my stay info in one place” wins decisively. AI-style recommendations are the least wanted feature — and 28% reject personalization entirely.
What would make personalization valuable?
Multi-select · n=103
Willingness to share preferences
n=103
Personalization rejecters
n=29 · the 28% who said “I wouldn’t want one”
The tension. 38% will share data; 33% explicitly want minimal data collection. Among personalization rejecters, almost half still say “no” to sharing preferences — a hard-no segment, not just unconvinced.
04 / Information Architecture
Check-in dominates traffic — and it mostly works.
Check-in is the most-used section by a wide margin and has a 90% success rate. The cracks are in Invoice, FAQ, and Browsing Info, where “partially found” rates climb sharply.
Section usage and success rate
Stacked: Yes / Partially / No found · n varies by section
Per-section success — read the small samples with caution
| Section | Users | Yes | Partially | No | Success rate |
|---|
| Check-in | 91 | 82 | 6 | 3 | 90% |
| Contacting Us | 26 | 24 | 1 | 1 | 92% |
| Wi-Fi | 23 | 19 | 0 | 4 | 83% |
| FAQ | 19 | 13 | 5 | 1 | 68% |
| Payment | 18 | 16 | 1 | 1 | 89% |
| Invoice | 12 | 7 | 3 | 2 | 58% |
| Browsing Info | 11 | 7 | 4 | 0 | 64% |
Missing topics — what guests went looking for and didn’t find
Topics guests said were missing
Multi-select · % of all respondents
Parking is the #1 information gap. 12% flagged it explicitly, plus repeated free-text mentions of garage access, paid parking, and timing.
05 / Arrival/Departure Time Input
One in three guests doesn’t understand why we ask.
63% breeze through it. But ~17% don’t understand the purpose, and ~15% feel it’s extra work. A purpose statement could likely lift this without changing the flow.
How did filling in arrival and departure times feel?
n=103
06 / Language & Translation
EN and DE are near-equal demand. Translation is not optional.
Splitting roughly 42/38 between English and German with another 17% comfortable in either, the reservation page needs to ship in both languages — supporting only one would alienate ~40% of guests. Demand for non-EN/DE languages exists but is currently small (4%).
Preferred language for stay information
n=103 · single-select + free-text "Other"
Effective reach if we ship only one language
| Scenario | Guests served natively | Guests on non-preferred language |
|---|
| English only | 60 / 103 (58%) | 39 / 103 (38%) |
| German only | 56 / 103 (54%) | 43 / 103 (42%) |
| EN + DE | 99 / 103 (96%) | 4 / 103 (4%) |
| EN + DE + ES + FR | 103 / 103 (100%) | 0 |
"Both fine" guests counted as served in either single-language scenario.
The verdict. Shipping in English only leaves ~38% of guests on a non-preferred language; German only, 42%. EN + DE together cover 96% — this is the minimum viable footprint. Spanish + French would close the remaining 4% but the absolute number is too small to prioritize without booking-origin data confirming a growing segment.
Open questions for the team
- Is the page currently single-language? If yes, this is a clear ship-translation decision; if both already exist, the question becomes language-detection logic.
- How are guests routed today? Booking.com profile language, browser default, or manual switch? The 17% "both fine" suggests detection errors are tolerable, but EN-only or DE-only guests will notice.
- Booking-origin data needed. Survey n=4 for Spanish/French is too small to act on alone. Pair with reservation data: if 10%+ of bookings come from those markets, the case for additional languages strengthens.
07 / Voice of Guest — Operational Signals
Recurring pain points outside the survey’s structured questions.
Free-text answers surface operational issues that are not product-driven but materially shape guest perception. Flagging here for cross-functional visibility.
Themes from “Anything else?” (n=39 responses)
- Wi-Fi code discoverability — 4+ guests mentioned not finding it; one suggested printing it in the flat
- Key/code reliability — wrong codes, off-by-one digits, white card vs. code confusion, lockouts
- Invoice delivery — guests still chasing invoices days/weeks after stay; ask for automatic delivery
- Parking — booking process, paying the garage, late prompts; reinforces structured-data finding
- Damage/issue reporting — explicit ask for a fast in-stay reporting channel
- Mobile check-in form — small fields, mandatory selfie at booking is friction for group travel
- Severe case — at least one guest reported toilet blockage with no support response, still awaiting refund. Flag for ops follow-up.
08 / Recommendations
Where to invest next.
Ranked by signal strength and effort. All recommendations tied to specific findings — see evidence line on each.
01
Invest
High signal
Channel
Lean into OTA chat as the primary delivery channel; deprioritize the native app.
Make the reservation-page link the first thing guests see in OTA chat. Optimize for OTAs that block external links (Booking, Airbnb) — guests said this is a known friction. Native app investment looks low-ROI: only 11% want one, and several said they wouldn’t install one.
Evidence: 48% OTA · 36% email · 11% native app · multiple free-text confirmations
02
Test
Medium signal
Wallet
Ship Wallet integration as a Phase 1, gated by an awareness experiment.
69% of all guests said Yes/Maybe. But 12% didn’t know what Wallet is — so the rollout copy matters as much as the feature. Suggest A/B testing two intro messages and measuring adoption among first-time vs. returning guests before scaling.
Evidence: 44% Yes · 25% Maybe · 12% “not sure what that is”
03
Invest
High signal
Language
Ship the reservation page in both English and German. Defer other languages.
Single-language coverage leaves 38–42% of guests on a non-preferred language. EN + DE covers 96% — the clear minimum viable footprint. Spanish, Portuguese, and French surfaced in free text (n=4) but the volume is too low to act on without booking-origin data; recommend tracking those markets quarterly and revisiting when any single non-EN/DE segment exceeds ~10% of bookings.
Evidence: EN 42% · DE 38% · Both fine 17% · Other 4% (ES/PT/FR)
04
Invest
High signal
Personalization
Define "personalization" as consolidation first. Defer AI recommendations.
"All my stay info in one place" is the #1 chosen value (46%) and it aligns with the channel finding. AI recommendations got only 13% interest — and 28% reject personalization entirely. A consolidated reservation page is the real product unlock; recommendation features are a second-order bet.
Evidence: 46% want one place · 26% faster check-in · 13% recommendations · 28% rejecters
05
Quick win
UX copy
Add a one-line purpose statement on the arrival/departure time input.
~17% of guests don't understand why we ask. A single sentence explaining the operational reason (cleaning prep, key handover, etc.) should reduce friction without changing the flow. Cheap to test.
Evidence: 17% "wasn't sure why" · 15% "felt like extra work"
06
Quick win
Info architecture
Add a Parking module to the reservation page.
The single most-flagged missing topic in structured data (12%) and a recurring theme in free text. Should include: garage location, payment, timing, and a "book in advance" prompt where applicable.
Evidence: 12% flagged parking missing · multiple free-text mentions
07
Investigate
Cross-functional
Audit Invoice and FAQ flows — both under 70% success.
Small samples (n=12 and n=19) so directional, but Invoice success is 58% and FAQ is 68%. Free-text confirms invoice-delivery delays. Worth deeper qualitative diagnosis before product changes.
Evidence: Invoice 58% Yes (n=12) · FAQ 68% Yes (n=19) · free-text on delayed invoices
Methodology & caveats
Sample. 103 completed responses, May 7–19 2026. Channel skew likely toward guests already engaged enough to respond — channel-preference findings should be read as directional, not population-level. Per-section success rates below n=20 are sensitive and flagged in the table.
Self-selection. Incentivized survey (coupon code). Guests with severe negative experiences may be over- or under-represented.
What this report does not answer. Booking-channel mix (Booking.com vs. direct vs. others), repeat-stay segmentation, property-type effects, or correlation with NPS — none were captured in this survey. Recommend pairing with reservation + reviews data for a full picture.
Analyst confidence: 80 / 100