Anana
Anana turns hotel calls, chats, and emails into commercial demand intelligence upstream of your PMS.
Trial Anana if your reservation and operations calls, chats, and emails generate signal nobody reads. It goes past dashboarding: investigations arrive with full source chains, and outputs land as published rate updates, drafted guest replies, and routed Slack alerts. The 15-minute weave and the three-source agreement rule keep findings auditable rather than noisy. Its published frameworks for measuring lost demand and AI visibility make it a useful counterpart to an RMS (which answers who booked) or a visibility tracker (which answers who mentions you). Single-site independents with thin conversation volume have little to feed it, and if you want a booking engine or system of record, look
Verified 2d ago · liveness 64/100 · cite: rightaichoice.com/tools/anana
- Hotel groups and management companies with 2+ properties
- Revenue managers hunting pickup, parity, and lost-demand signals beyond the RMS
- Operations leads tracking recurring guest complaint patterns across weekends
- Cluster leads monitoring group pipeline across properties without losing local context
- Single-site independent hotels with low conversation volume
- Teams shopping for a guest-facing chatbot or booking automation
- Buyers expecting a standalone PMS or RMS replacement
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Skip Anana if you run a single property with low call, chat, and email volume, or if you need a guest-facing booking chatbot or replacement system of record rather than an intelligence layer.
Anana sells to hotel groups and management companies rather than single properties, which puts it in the portfolio-tooling budget line next to your RMS and CRM rather than the per-property SaaS spend. Compared with a standalone RMS, you are paying for an intelligence layer on top of systems you already run, so the value case rests on recovered direct bookings and avoided OTA commission.
In short
Anana — Anana turns hotel calls, chats, and emails into commercial demand intelligence upstream of your PMS. Best for Hotel groups and management companies with 2+ properties, Revenue managers hunting pickup, parity, and lost-demand signals beyond the RMS, Operations leads tracking recurring guest complaint patterns across weekends. Contact Sales pricing.
What's new in Anana
Checked 7 days agoAcross the latest 10 updates: 9 community discussions and 1 news mention.
How Hotels Should Measure Lost Demand
Anana publishes a framework for measuring qualified hotel inquiries across phone, email, chat, forms and RFPs, including non-conversion reasons.
Google UCP for Lodging: From AI Recommendation to AI Reservation
Anana breaks down how Google's UCP for Lodging puts hotel booking into AI Mode, how it differs from Hotel Center, and what hotels should prep.
How to Measure Hotel Visibility in ChatGPT, Google AI Overviews, and Perplexity
Anana outlines a framework for measuring hotel visibility across ChatGPT, Google AI Overviews and Perplexity using repeated prompts and citations.
Your Guests Already Told You What AI Needs to Know
Anana says hotel calls, emails, chats and lost inquiries reveal what guests value and what commercial teams should fix or publish.
AI Can Read Your Hotel. Can Your Hotel Read Its Demand?
Anana argues AI legibility drives discovery but not demand capture; teams still need guest question, hesitation and booking data.
AI Visibility Shows Who Mentions Your Hotel. It Cannot Show Who Booked.
Anana distinguishes public AI visibility from the commercial question of which real guests asked and booked.
Your Hotel Can Win Its Comp Set and Still Be Invisible to AI Travelers
Anana notes a hotel can lead its comp set yet be absent from regional AI discovery, and proposes comparing three denominators.
Why One AI Search Cannot Measure Your Hotel's Visibility
Anana says a single AI response is not a hotel visibility benchmark; reliable measurement needs repeated prompts and uncertainty ranges.
RMS vs PMS vs Commercial Intelligence: What Each Hotel System Actually Does
Anana compares RMS, PMS and commercial intelligence systems, covering who booked, who's staying and who asked.
Reduce OTA Commission by Capturing the Direct Bookings You're Already Losing
Anana details how commercial teams can shift booking mix toward direct to avoid 15-25% OTA commissions per booking.
What people actually say about Anana — is it worth it?
We scanned public community sources for Anana on Jul 3, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Our own analysis of that scan says the posts were off-subject. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is Anana? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Ask: natural-language questions across bookings, calls, market intel, and SOPs in one thread
- Multi-turn threads with memory of past sessions and team decisions
- Sense: proactive pattern detection that surfaces when three or more sources agree
- Cross-references PMS, CRM, comp set, telephony, events, and weather data
- Pattern weave refreshes every 15 minutes across the portfolio
- Investigations: structured finding, recommendation, and full auditable source chain
- Investigations triggered by calls, CRM events, or schedule
- Filter investigations by status, category, and property
- Act: automated rate updates synced to the channel manager
- AI-drafted guest replies routed to Mail for human review
- Alert routing into Slack channels such as #ops-miami
- Portfolio-wide view with per-property visibility controls for cluster leads
- Granular role permissions for CCOs, DOSMs, CROs, and GMs
- Team-specific knowledge bases with shared history across the group
- SOC 2 Type II and GDPR compliant
About Anana
Anana is an AI workspace for hospitality commercial teams at hotel groups and management companies running two or more properties. It sits alongside your PMS, CRM, and telephony stack and converts the traveler intent already flowing through calls, chats, and emails into commercial intelligence — what guests asked, what they hesitated on, and where demand leaked before it became a booking. The workspace runs on three verbs. Ask puts natural-language questions across bookings, calls, market intelligence, and your own SOPs into one multi-turn thread that remembers what you looked at yesterday and what the team decided last week. Sense detects patterns across six sources — PMS, CRM, comp set, telephony, events, and weather — surfacing a finding when three or more sources agree, re-weaving every 15 minutes. Act closes the loop: rate updates publish to the channel manager, guest replies draft into Mail for human review, and alerts route into Slack channels such as #ops-miami. Investigations are the differentiator: when pickup softens, an RFP arrives, or the same complaint shows up three times, Anana investigates rather than pinging you — producing a structured finding, a recommendation, and the full auditable chain of tools and sources behind it. Per-property visibility controls let cluster leads flip between portfolio and single-property views while GMs stay scoped to their own hotel. Anana publishes research and frameworks on lost demand, AI visibility, and the difference between RMS, PMS, and commercial intelligence, and markets SOC 2 Type II and GDPR compliance. Several modules, including HCP (Hospitality Context Protocol), are marked coming soon.
Behind the Verdict
Anana is best understood as a commercial intelligence layer that sits upstream of the PMS. The pitch is simple: you already paid for the demand, and most of what it tells you disappears into calls, chats, emails and unconverted inquiries that no system of record keeps. Anana's answer is to keep those signals and turn them into findings. The product surface is three verbs. Ask is a multi-turn thread across bookings, calls, market intelligence and your own SOPs, with shared history across the group. Sense watches six sources — PMS, CRM, comp set, telephony, events and weather — and surfaces a pattern only when three or more sources agree, re-weaving every 15 minutes. Act is where it earns its keep: rate updates publish to the channel manager, guest replies draft into Mail for human review, and alerts route into Slack channels like #ops-miami. Investigations are the strongest differentiator. Rather than pinging you that pickup softened, Anana produces a structured finding, a recommendation, and the full auditable chain of tools and sources behind it, triggered by calls, CRM events or schedule, and filterable by status, category and property. The portfolio model is well thought through: cluster leads can flip between group and single-property views while GMs stay scoped to their own hotel, with granular role permissions for CCOs, DOSMs, CROs and GMs. Anana's recent writing is unusually specific for this category — frameworks for measuring lost and qualified demand across phone, email, chat, forms and RFPs, a method for measuring hotel visibility across ChatGPT, Google AI Overviews and Perplexity using repeated prompts and citations, and a breakdown of Google's UCP for Lodging. It also makes the case for direct-booking capture against 15-25% OTA commissions. Where it does not fit: single-site independents with low conversation volume, teams wanting a guest-facing chatbot or booking automation, and buyers expecting a standalone PMS or RMS replacement. Without logged calls, emails or CRM events flowing in, there is nothing to synthesize. HCP and other modules are marked coming soon, so evaluate on what ships today.
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Real-world workflow fit
Concrete scenarios for the personas Anana actually fits — and what changes day-one when you adopt it.
Monday morning, you open Ask and query weekend pace at Park Lane NY. Anana pulls live occupancy, the Fri–Sun group block, the event calendar, spa and F&B staffing, and last year's comparable, then tells you Sat has a soft pocket while Fri is tight.
Outcome: You publish a rate update for Apr 25–27 Deluxe King from $389 to $429 straight to the channel manager, synced to 4 channels, without leaving the workspace.
Sense flags a spa staffing pattern: 9 repeat complaints at Miami clustered after 4pm, agreeing across telephony, CRM and PMS sources.
Outcome: Anana routes an alert into #ops-miami with the finding and source chain, so your team fixes Saturday staffing before the next weekend peak.
An RFP arrives and a guest email asks about holding 18 rooms for October. Anana triggers an investigation and drafts the reply into Mail with the group pipeline context.
Outcome: A human reviews and sends the drafted reply, and the group pipeline shows up 18% week over week with $1.2M in play across 3 properties.
Use Cases
- Ask about weekend pace at a specific property and get live occupancy, group blocks, and staffing in one answer
- Investigate why spa complaints clustered on weekends and receive a structured finding with recommendations
- Track group pipeline growth week over week and drill into rate blocks and event overlaps
- Cross-reference event calendars with F&B and staffing plans to find soft pockets in advance
- Surface demand shifts across the portfolio, such as pickup moving from Tue–Thu to Thu–Sat
- Turn call, chat, and email logs into structured demand intelligence instead of untracked conversation
- Publish rate updates to the channel manager from a finding rather than a separate workflow
Limitations
- Anana is designed for hotel groups managing multiple properties with a portfolio-level focus, so single-site independents get limited value.
- It depends on logged calls, emails, or CRM events to analyze; with no conversation data flowing in, there is nothing to synthesize.
- It is positioned as a commercial intelligence layer upstream of the PMS rather than a booking or system-of-record.
- Several workspace modules, including HCP (Hospitality Context Protocol), are marked 'coming soon'.
as of 2026-10-09
Verification history
We have re-verified Anana 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
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Where the pricing makes sense
The company stage and team size where Anana's pricing actually pencils out — and where peers do it cheaper.
Anana sells to hotel groups and management companies rather than single properties, which puts it in the portfolio-tooling budget line next to your RMS and CRM rather than the per-property SaaS spend. Compared with a standalone RMS, you are paying for an intelligence layer on top of systems you already run, so the value case rests on recovered direct bookings and avoided OTA commission.
Setup time & first value
How long it actually takes to get something useful out of Anana — broken out by persona, not the marketing-page minute.
For a hotel group with clean PMS, CRM and telephony feeds, expect days rather than weeks: Anana ships on your real portfolio data rather than a demo sandbox, so the first session can query live bookings and calls. Groups with fragmented call logging or no CRM events will spend longer wiring sources before Sense produces three-source findings. GMs and cluster leads need only role permissions set
Switching to or from Anana
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From an RMS-only stack: keep the RMS for who-booked reporting and layer Anana on top for lost-demand and conversation intelligence.
- →From spreadsheet call logs: consolidate call, chat, and email records into the PMS or CRM feed so Sense has three sources to agree on.
- →From a generic BI dashboard: move recurring pickup and complaint questions into Ask threads with shared team history.
- ↗To a standalone RMS: export the commercial findings you rely on and re-point rate publishing back to the channel manager workflow.
- ↗To a visibility tracker only: if you only need who-mentions-you data, Anana's conversation and booking signals become redundant.
- ↗To your PMS vendor's native reporting: expect to lose cross-source investigations and the auditable source chain.
Integrations
Resources & Guides
Tutorials & Learning
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Official links
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Featured Head-to-Head Comparisons
Anana vs Presto Voice
Choose Presto Voice if you're a QSR chain looking to automate drive-thru orders and boost revenue via upselling. Choose Anana if you're a hotel group that wants to capture demand signals from guest communications that PMS/RMS miss. They serve completely different industries, so the decision depends on your vertical.
Anana vs Nectar Energy
Nectar Energy and Anana serve completely different markets. Nectar Energy is for commercial building energy optimization, ideal for facility managers seeking automated HVAC/lighting control and ESG reporting. Anana is for hotel groups, turning guest calls/emails into demand intelligence. Buyers should choose based on their sector: energy management vs hotel commercial intelligence.
Anana vs Truleo
These tools serve entirely different verticals: Truleo is purpose-built for law enforcement agencies to connect siloed data and automate case work, while Anana targets hotel groups needing demand intelligence from guest communications. Choose based on your industry and data sources — neither is cross-industry. Truleo wins on explicit integrations and CJIS compliance; Anana wins on capturing human conversation signals that PMS and RMS miss.
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