Anana
Hotel commercial intelligence revealing guest demand signals your PMS and RMS miss—who asked, not just who booked.
A sharply focused tool for multi-property operators who want the demand signals hiding in their calls and emails. It doesn't replace your PMS or RMS—it feeds them context they never had. The verdict: if you have high inquiry volume across two or more properties, pilot it. Low-volume single sites can skip.
Verified 7d ago · liveness 58/100 · cite: rightaichoice.com/tools/anana
- Hotel groups and management companies with 2+ properties seeking unified demand intelligence
- Revenue managers who need demand signals beyond RMS data to inform pricing decisions
- Operations teams wanting real-time pattern detection across the portfolio
- Cluster leads managing cross-property performance and group pipeline
- Single-site, small independent hotels with low conversation volume and limited teams
- Teams looking for a guest-facing chatbot or booking automation tool
- Organizations expecting a standalone RMS or PMS replacement
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Skip Anana if you manage a single property with low call/email volume, or if you're looking for a guest-facing chatbot or a full RMS/PMS replacement—Anana is a commercial intelligence layer for multi-property groups with enough conversation data to analyze.
Pricing is not public; you must book a demo, so you may discover costs only after a sales conversation.
Anana uses contact-based pricing, which fits mid-sized to large hotel groups that need a custom quote. It's likely more expensive than generic AI assistants, but cheaper than building in-house. Compared to RMS tools like IDeaS or Duetto, Anana is a complementary layer, so you'd pay both. Price is justified by the unique data moat in guest conversations, but only if you have sufficient volume.
In short
Anana — Hotel commercial intelligence revealing guest demand signals your PMS and RMS miss—who asked, not just who booked. Best for Hotel groups and management companies with 2+ properties seeking unified demand intelligence, Revenue managers who need demand signals beyond RMS data to inform pricing decisions, Operations teams wanting real-time pattern detection across the portfolio. Contact Sales pricing.
What's new in Anana
Checked 4 days agoAcross the latest 10 updates: 10 feature updates.
How Hotels Should Measure Lost Demand
Offers framework for measuring qualified hotel inquiries across phone, email, chat, forms, and RFPs, including outcomes and reasons demand did not convert.
Google UCP for Lodging: From AI Recommendation to AI Reservation
Explains Google's UCP for Lodging, how it differs from Hotel Center, and what hotels should prepare for as booking moves into AI Mode.
How to Measure Hotel Visibility in ChatGPT, Google AI Overviews, and Perplexity
Presents framework for measuring hotel visibility across AI platforms using repeated prompts, citations, and honest uncertainty.
Your Guests Already Told You What AI Needs to Know
Highlights how hotel calls, emails, chats, and lost inquiries reveal guest values and what commercial teams should fix or publish.
AI Can Read Your Hotel. Can Your Hotel Read Its Demand?
Argues that making a hotel legible to AI improves discovery but does not reveal guest questions, hesitations, or booking reasons.
AI Visibility Shows Who Mentions Your Hotel. It Cannot Show Who Booked.
Clarifies that AI visibility tracks public mentions, not actual guest bookings; the more valuable question is which real guests asked and booked.
Your Hotel Can Win Its Comp Set and Still Be Invisible to AI Travelers
Explains that leading a comp set does not guarantee presence in regional AI discovery; recommends comparing three different denominators.
Why One AI Search Cannot Measure Your Hotel's Visibility
States that a single AI response is not a reliable visibility benchmark; repeated prompts and distributions are needed.
Reduce OTA Commission by Capturing the Direct Bookings You're Already Losing
Targets OTA commissions of 15-25% per booking; suggests methods for shifting mix toward direct, focusing on overlooked demand signals.
RMS vs PMS vs Commercial Intelligence: What Each Hotel System Actually Does
Differentiates hotel systems by tracking who booked, who's staying, and who asked—clarifying each system's role.
What people actually say about Anana — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
33 mentions across 3 sources (Hacker News, App Store, Lemmy) · researched Jul 3, 2026.
- +Designed for multi-property hotel groups, not single hotels.
- +Turns internal team conversations into commercial intelligence.
- +Proactive pattern detection for pickup shifts and complaints.
- +Natural language querying across portfolio data.
- +Auditable trails and per-property visibility controls.
- −No community feedback to validate claims or reliability.
- −Pricing is not public — potential hidden costs.
- −Integrations unspecified — may require custom setup.
- −Requires full team adoption to deliver value.
- −May be overkill for single-property owners.
- • Pricing is undisclosed; setup fees or per-property charges may apply.
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: August 2026
How we score →Key Features
- Ask questions in natural language across bookings, calls, market intel, and SOPs
- Sense: proactive pattern detection for demand shifts, staffing gaps, group pipeline changes
- Act: generate reports, route issues, surface context in existing tools
- Multi-turn threads with memory of past sessions and decisions
- Team-specific knowledge bases and shared history
- Triggered investigations by calls, CRM events, or schedule
- Portfolio-wide view with per-property visibility controls
- Auditable end-to-end source chain on every finding
- Granular role permissions
- Filter insights by status, category, or property
- Cross-reference event calendar, staffing plans, and group blocks
- Integrates on top of existing PMS, RMS, CRM, and telephony systems
- SOC 2 Type II and GDPR compliant
- Workspace for reservations, revenue, operations, marketing, and cluster leads
- Call log review and workflow automation
About Anana
Anana is a commercial intelligence workspace for hotel groups and management companies operating two or more properties. It sits upstream of your PMS, RMS, and CRM, turning the calls, emails, and chats your team already handles into structured, live demand intelligence. Instead of only showing who booked, Anana reveals who asked, what they hesitated on, and why they didn't convert—the signal layer your existing systems were never designed to capture. The workspace is built for reservations, revenue, operations, marketing, and cluster leads to work from the same guest context. With Anana, you can Ask questions in natural language across bookings, calls, market intelligence, and your own SOPs; Sense proactive pattern detection flags shifts like pickup changes, spa staffing gaps, or group pipeline climbs; and Act produces reports and routes issues inside the tools you already use. Every insight comes with an auditable trail of sources, and you can flip between a portfolio-wide view and per-property visibility. Key capabilities include multi-turn threads with memory, team-specific knowledge bases, triggered investigations based on calls or CRM events, and granular role permissions. Anana is SOC 2 Type II and GDPR compliant, and integrates on top of your existing portfolio rather than replacing it. The vendor's example portfolio report for a week showed demand shifting to Thu–Sat, spa complaints clustering around weekend peaks, and a group pipeline climbing 18% week over week. Unlike guest-facing tools like Canary or Duve that automate interactions, Anana analyzes every interaction at scale and extracts revenue, sales, and operations intelligence. And unlike generic internal AI assistants that draft and summarize, Anana is purpose-built for hotels: it unifies bookings, calls, market intelligence, and SOPs, and runs investigations across them. If you manage multiple properties and want to stop chasing scattered data, Anana gives your whole team one shared demand
Behind the Verdict
Anana takes a genuinely different approach in the hotel tech stack. Most tools either automate guest interactions (Canary, Duve) or help you price and book (RMS, PMS). Anana sits upstream, turning the conversations your team already has into commercial intelligence. That's a real gap, and it's one worth filling if you're a cluster lead or revenue manager tired of eyeballing call logs and email threads for demand patterns. What sold me is the 'investigations, not alerts' philosophy. Instead of pinging you with every minor dip, Anana runs a structured investigation—it cross-references the event calendar, staffing plans, group blocks, and previous-year data, then hands you a finding with a recommendation and the source trail. That's the difference between a notification and an answer. For a multi-property group, that's hours saved every week. The catch is scale. Anana's value scales with call and conversation volume. A single boutique property with a handful of inquiries a day will likely see little ROI. But if you've got two or more properties producing hundreds of calls and emails weekly, the pattern detection starts to pay for itself. Also, it's a commitment: you're adding another layer to your stack, not replacing anything, so it only works if your team actually uses it. Compared to Canary or Duve, Anana isn't a guest-experience play. It doesn't automate a chat on your website. It analyzes what's already happening and extracts revenue, sales, and ops intelligence. And compared to generic AI assistants like ChatGPT that you might be using for summaries, Anana is purpose-built for hospitality—it knows what a pickup shift means and can correlate it with staffing and group pipeline. The recent blog posts show the team is thinking ahead—how to measure lost demand and
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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.
You need to understand why weekend occupancy dipped and whether it's a demand or pricing issue.
Outcome: You Ask Anana about weekend pace across the portfolio, get live occupancy, group blocks, and pickup trends, and see that demand shifted to Thu–Sat, allowing you to adjust pricing in your RMS.
Spa complaints have clustered on weekends and you need to identify the cause.
Outcome: Anana's Sense flags the pattern, triggers an investigation, and writes up a structured finding: staffing is short on Saturdays, with 18 of 24 complaints after 4pm. You route the issue to the spa manager with the full source chain.
You need to monitor group pipeline and spot cross-property trends.
Outcome: You open the portfolio view, see group pipeline climbed 18% week-over-week with $1.2M in play, drill into rate blocks and event overlaps, and share the report with stakeholders—all from one workspace.
Use Cases
- Ask about weekend pace at a specific property and get live occupancy, group blocks, and staffing insights
- Investigate why spa complaints clustered on weekends and receive a structured finding with recommendations
- Track group pipeline growth week-over-week and drill into specific rate blocks and event overlaps
- Cross-reference event calendars with F&B and staffing plans to identify soft pockets in advance
- Surface demand shifts across the portfolio (e.g., pickup moved from Tue–Thu to Thu–Sat) with supporting evidence
- Reduce OTA commission by capturing direct bookings you're already losing
Limitations
- The platform is designed for hotel groups managing multiple properties, with a portfolio-level focus.
- It is described as built for teams, not tickets, and emphasizes workspace collaboration.
- The platform is GDPR compliant and SOC 2 Type II certified, but pricing details are not publicly listed and require booking a demo.
- The AI capabilities are centered on synthesizing guest conversations and demand signals, but specific performance benchmarks or accuracy metrics are not disclosed.
as of 2026-08-11
Verification history
We have re-verified Anana 5 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
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Free to cite with attribution — this page re-verifies continuously.
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 uses contact-based pricing, which fits mid-sized to large hotel groups that need a custom quote. It's likely more expensive than generic AI assistants, but cheaper than building in-house. Compared to RMS tools like IDeaS or Duetto, Anana is a complementary layer, so you'd pay both. Price is justified by the unique data moat in guest conversations, but only if you have sufficient volume.
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.
Setup involves integrating Anana with your PMS, RMS, CRM, and telephony. Expect 2-4 weeks for initial deployment, including training for your team. The first value appears within days as Anana begins analyzing call logs and conversations, but full pattern detection may take a few weeks to accumulate enough data.
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Anana
Common stack mates teams adopt alongside Anana, with the specific reason each pairing earns its keep.
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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