Audience: Investors and JV partners. Status: Strategy artifact. Date: May 2026.
Reading rules: Every number here is either (a) sourced to /00-intelligence/ and the Strategy Canon, with a confidence grade (H/M/L), or (b) explicitly flagged as a USER INPUT — a negotiated or to-be-confirmed figure we do not assume. Nothing is fabricated. Where we show a worked example, it is labelled ILLUSTRATIVE and built only from sourced ranges.
1. The model in plain terms
Nest.IQ does not buy land or fund buildings. It manufactures the one thing real estate cannot manufacture on its own: guaranteed enterprise occupancy, wrapped in a premium operating standard and an intelligence layer that compounds with scale.
The structure is a joint venture with a developer. The developer contributes the hard assets and regulatory clearance; Nest.IQ contributes the brand, the enterprise demand, the operating system, and the technology. The developer keeps the property economics and asset upside it is built to capture; Nest.IQ earns fees (and, where negotiated, an economic share and/or equity participation) for filling and running the asset to a standard global enterprises will pay for.
This is the empty quadrant in the Indian market (Competitive-Analysis-Report §2, §8): hospitality-led operators own inventory but rent it opportunistically; mobility-led aggregators own captive demand but no inventory. No one fuses owned/operated keys with captive mobility demand and intelligence. That fusion is the business.
The wedge, in the canon's words: "Everyone can build the building. Only Nest.IQ arrives with the tenants — and the intelligence to keep them."
Who brings what / who earns what
| Dimension | Developer (e.g. Embassy / Prestige) | Nest.IQ (powered by IKAN) |
|---|---|---|
| Land | Contributes land (12–22% of total project cost; excluded from Nest.IQ's capital base in a JV) [D §1, H] | — |
| Building & construction capex | Funds the building and fit-out (Upscale ~₹1.12cr/key ex-land 2023; escalate ~₹1.3–1.4cr 2025–26) [D §1, H] | — |
| Local regulatory / approvals | Holds and clears | — |
| Brand & standard | — | Owns brand, design language, one operating standard across every key |
| Enterprise sales & demand | — | Captive occupancy — the moat: IKAN's 1,000+ corporate clients, 50,000+ assignments, 200+ cities; pre-let contracts before doors open |
| Operations / hospitality mgmt | — | Runs the property to enterprise/expat standard |
| Technology | — | The .IQ intelligence layer (demand-matching, yield, smart ops, resident app, data network effects) |
| Mobility-services wrap | — | Immigration, relocation, destination services, concierge (IKAN ecosystem) |
| What they earn | Property EBITDA + asset/REIT upside; downside floor if a minimum guarantee is negotiated | Base fee on revenue + incentive on GOP; optional rev-share and/or JV equity participation; cross-sell margin (split = USER INPUT) |
| What they risk | Capital intensity; asset and demand risk (mitigated by pre-let occupancy) | Performance risk on occupancy and operating standard; receivables financing |
The risk/return logic (Competitive-Analysis-Report §8.2): Ascott deliberately offloads real estate to a REIT; Ahuja leases on thin margins. Nest.IQ's JV captures operating margin plus asset-upside participation without funding capex — a better risk/return than either incumbent structure, and consistent with the management-agreement and branded-residence terms developers like Embassy already sign.
2. How Nest.IQ relates to IKAN's aggregator — and to the global aggregators
Nest.IQ is an independent, owned/JV brand. This document does not pitch the aggregation business.
IKAN today runs a B2B aggregation business (mobility demand routed to third-party supply for a markup). Nest.IQ is the opposite end of the value chain: it owns and operates the keys. Two relationships matter:
IKAN Residences (the existing aggregator) feeds occupancy. IKAN's enterprise and RMC demand — the same pipeline that powers the aggregator — becomes captive occupancy for Nest.IQ's owned inventory. The aggregator is a demand source, not a competitor; Nest.IQ is a separate brand with its own balance-sheet logic.
The global aggregators become channels once Nest.IQ owns inventory. SilverDoor/Synergy, AltoVita, Dwellworks, and National Corporate Housing are demand-rich, inventory-poor (Competitive-Analysis-Report §5). Today they are rivals of the aggregation business. The moment Nest.IQ owns vetted keys, these players resell that inventory — converting Nest.IQ from a markup reseller into their preferred India supplier, improving margin and defensibility at once.
Watch-item (Competitive-Analysis-Report §9): Ascott co-owns SilverDoor/Synergy and is the one incumbent holding both halves of the thesis (scale operator + aggregator). Defensibility is a function of speed and lock-in — secure developer JVs and enterprise contracts before Ascott fuses its halves into a deliberate India play.
Embassy is the lead JV partner, not a competitor. Nest.IQ sits above Olive's volume co-living tier as the premium expat/managed-corporate layer, fed by inbound mobility demand (Competitive-Analysis-Report §6.2; Canon §9). It completes Embassy's office-park ecosystem (274 occupiers across ~51.2 msf) rather than duplicating any part of it.
3. The demand moat — captive enterprise occupancy
The moat is not the building; it is who fills it, and how cheaply.
- Extended-stay runs ~78% occupancy vs ~66% for traditional hotels — a +10–12pt structural premium driven by stable relocation, project, and assignment demand (Canon §3; Competitive-Analysis-Report §2, M confidence).
- Pre-let enterprise contracts fill homes before they open. Phase-1 strategy is explicit: pre-secure enterprise occupancy contracts before launch (Canon §8).
- Counter-cyclical demand: extended-stay demand rose +2.2% in 2025 while overall hotel demand fell −0.8%, and has declined only once in 27 years (Competitive-Analysis-Report §2).
- A captive channel eliminates most of the cost drag of hospitality-led peers: ~15–20% CAC and 15–30% OTA-commission per booking, plus ~50% OTA cancellation rates (Competitive-Analysis-Report §2). This is margin Nest.IQ keeps that hotels leak.
In underwriting terms: a hotel buys its occupancy every night; Nest.IQ contracts it in advance across a diversified 1,000+ client base — the diversification that the single-partner concentration killing Sonder did not have (Competitive-Analysis-Report §8.5).
4. The .IQ intelligence layer — concretely
The ".IQ" is not decoration. It is the system that turns a portfolio of serviced homes into a learning network, and it is the basis for any valuation premium above a pure hospitality multiple.
- Demand-matching — the right home to the right assignee. IKAN's assignment data (assignee profile, family size, stay length, employer, location need) is matched to the right unit, sub-market, and price. This is the data the aggregators route blind; Nest.IQ owns both the demand signal and the supply.
- Occupancy & yield optimization. Dynamic allocation and pricing across owned inventory and pre-let contracts to lift occupancy toward the 78–82% stabilized upside (Canon §6) and protect ADR by city.
- Smart operations & resident app. A single operating standard ("one standard, every key") instrumented through software — check-in, service requests, the arrival experience, and the concierge/relocation wrap delivered in-app.
- Data network effects. Every assignment, stay, and renewal improves matching, pricing, and demand forecasting. More keys and more assignments make the next match better — a compounding advantage neither a pure operator nor a pure aggregator can replicate.
- Cross-sell engine. The app and data layer surface the IKAN ecosystem services (immigration, relocation, destination, concierge) at the moment of need, expanding LTV per assignee.
Why it supports a proptech premium (with discipline): Hospitality assets trade ~7% EBITDA yield (~14×) to OYO's ~25–30× EBITDA / proptech ~8.8× revenue (D §7). A genuine, recurring intelligence/SaaS revenue line is what could justify a multiple above the hospitality base. The canon is explicit: US$150–300M is the defensible base (hospitality multiple on 1,500–2,000 keys); US$500M is a narrative ceiling requiring a proptech/SaaS multiple or real-estate equity participation — present it as a ceiling, not a promise (Canon §7; D §7, M confidence). The tech-premium thesis is itself a USER INPUT (share of revenue that qualifies as SaaS).
5. Revenue streams
| # | Stream | What it is | Benchmark basis | Confidence |
|---|---|---|---|---|
| 1 | Residence revenue (core) | Nightly/monthly room revenue from serviced homes | ADR ~₹8,500 blended (between all-India ₹7,951 and Top-10 ₹8,792); model city-specific | H (within market) [D §2] |
| 2 | Ancillary | Laundry, F&B, transfers, parking | Standard serviced-living add-ons; included in property economics | M |
| 3 | Cross-sell (IKAN ecosystem) | Relocation, immigration, destination services, concierge | High-margin, LTV-expanding; attach-rate is a flagged data gap — model as a USER INPUT | Flagged gap [Canon §6; D] |
Stream 1 is the underwrite. Stream 2 lifts property economics modestly. Stream 3 is the LTV story and the clearest differentiator from any hospitality operator — but its attach-rate has no public benchmark and must be supplied, not assumed.
A licensing path also exists where relevant: branded-residence royalty 2–5% of sales, with a branded premium of ~33% (up to ~75% in Pune) (Canon §6) — applicable if the JV includes for-sale branded units.
5.1 Cross-sell / LTV skeleton
Stream 3 is where Nest.IQ's economics separate from any pure operator: a resident is not a room-night, but an assignee with a relocation lifecycle the IKAN ecosystem already serves. The framework is attach-rate × per-service contribution, summed across services, expanded by stays per assignment and renewals. Every rate and margin below is an explicit ⟨INPUT⟩ — the attach-rate is a canon-flagged data gap (Canon §6) and is not assumed. The skeleton shows the chain; the pilot populates it.
| IKAN ecosystem service | Attach rate (of assignees) ⟨INPUT⟩ |
Revenue / attached assignee ⟨INPUT⟩ |
Contribution margin % ⟨INPUT⟩ |
Margin / assignee = cols × |
|---|---|---|---|---|
| Relocation (move management, settling-in) | ⟨INPUT a₁⟩ | ⟨INPUT r₁⟩ | ⟨INPUT m₁⟩ | a₁·r₁·m₁ |
| Immigration (visa, work-permit, compliance) | ⟨INPUT a₂⟩ | ⟨INPUT r₂⟩ | ⟨INPUT m₂⟩ | a₂·r₂·m₂ |
| Destination services (schooling, area orientation, spousal) | ⟨INPUT a₃⟩ | ⟨INPUT r₃⟩ | ⟨INPUT m₃⟩ | a₃·r₃·m₃ |
| Concierge (in-stay lifestyle, transport, extensions) | ⟨INPUT a₄⟩ | ⟨INPUT r₄⟩ | ⟨INPUT m₄⟩ | a₄·r₄·m₄ |
| Σ Cross-sell margin / assignee | sum of the per-service products (blank until inputs set) | Σ (aᵢ·rᵢ·mᵢ) | ||
LTV formula skeleton (margin-based; per assignee relationship):
Housing contribution / assignee = stay nights × ADR × property-margin share to NIQ ⟨INPUT⟩
Cross-sell contribution / assignee = Σ (attach rateᵢ × revenueᵢ × marginᵢ) ⟨INPUT⟩ (table above)
LTV = ( Housing contribution + Cross-sell contribution )
× stays per assignment ⟨INPUT⟩
× (1 + renewal / repeat rate) ⟨INPUT⟩
÷ discount factor ⟨INPUT, if NPV-based⟩
LTV : CAC → CAC is structurally low — demand is captive via IKAN, not bought via OTA/ad spend
(the ~15–20% CAC + 15–30% OTA drag hospitality peers carry is avoided — §3)
The strategic point needs no numbers to land: because acquisition is captive (the assignee arrives through IKAN's enterprise relationship, not a paid channel), CAC is structurally compressed while the cross-sell layer extends contribution per relationship — so the LTV:CAC ratio is favourable by construction. Quantifying it is gated on the pilot's measured attach rates, which is exactly why those cells stay ⟨INPUT⟩ rather than being invented.
6. Deal structures & economics
The norms below are sourced; the actual split is a negotiated USER INPUT per deal (no public India benchmark for the rev/profit-share exists — D §6, §"Inputs").
| Structure | How Nest.IQ earns | Sourced norm | Developer gets |
|---|---|---|---|
| Management contract | Base fee on revenue + incentive on GOP | Base 2–4% of revenue (3% common); incentive 5–15% of GOP (8–10% common), often tiered (e.g. 6–7% at 40% GOP margin → 9–10% at 50%); +1–3% tech/marketing and ~3–5% FF&E reserve | Keeps full property EBITDA and risk |
| Revenue-share | Single-digit % of total revenue + performance kicker | Reasoned from above (no single public benchmark) | Keeps majority; bears asset risk |
| Rev-share with minimum guarantee (MCMGI) | Share of revenue/GOP with a floor paid to developer | Ascott FY24 mix: 12% master-lease, 27% mgmt-contract-with-min-guarantee, 61% mgmt-contract [D §4] | Downside protection (floor) |
India validation that fee streams are real: IHCL management-fee income grew ₹470cr → ₹562cr (+20%), with >95% of new signings capital-light (D §6). Operators in India earn meaningful fee income and are aggressively pivoting asset-light — the structural tailwind under Nest.IQ's model.
Recommended posture (Canon §9): propose familiar structures — ≈20-year operating agreement; base fee on revenue + incentive on GOP weighted to profit; optional revenue-share + minimum guarantee to give the developer a downside floor. The minimum-guarantee option is the alignment tool that makes a captive-demand operator credible to a capital partner.
6.1 The economics waterfall — how Nest.IQ earns
The structures above describe terms; the waterfall describes the mechanism — the exact chain from a room-night to Nest.IQ's retained take. Sourced ranges anchor the property lines; every step that depends on a negotiated or to-be-measured figure is a ⟨INPUT⟩ gate (shown in clay). Amounts are deliberately blank — this is the chain, not a forecast.
| Step | Line | How it is set | Amount |
|---|---|---|---|
| 1 | Room revenue | keys × occupancy × ADR × 365 — sourced ranges [S3] | ₹ ⟨—⟩ |
| 2 | + Ancillary | room rev × ancillary % — ⟨INPUT⟩ |
₹ ⟨—⟩ |
| 3 | + Cross-sell | Σ (attach × revenue × margin) — ⟨INPUT⟩, §5.1 skeleton |
₹ ⟨—⟩ |
| 4 | = Total property revenue | sum of 1–3 | ₹ ⟨—⟩ |
| 5 | − Operating cost | property cost stack — ⟨INPUT⟩ |
₹ ⟨—⟩ |
| 6 | = GOP / property EBITDA | sourced 28–40% net [S3][S5][S9][S10] | ₹ ⟨—⟩ |
| 7 | × Fee % + incentive % | base 2–4% rev + 5–15% GOP norm [S11][S12]; actual split ⟨INPUT⟩ |
₹ ⟨—⟩ |
| 8 | = Nest.IQ take | the retained line — product of 6 × 7 (plus any rev-share / equity participation) | ₹ ⟨—⟩ |
Two honesty notes on the chain. First, in the management-contract case Nest.IQ's take is computed off revenue and GOP (steps 1, 6) via the fee schedule (step 7); the developer retains property EBITDA net of that take, plus asset/REIT upside — so steps 6–8 are where the JV split actually bites (the highest-leverage input, per Financial Framework §6.2). Second, where Nest.IQ negotiates a revenue-share or JV-equity participation instead of (or alongside) a fee, the take is drawn higher up the chain or from asset economics directly — the diagram's step 7 is the placeholder for whichever structure §6 settles on. The sourced lines (1, 6) and norm ranges (7) are real; the amounts stay blank until the Input Register is populated.
7. Unit economics of a representative pilot — ILLUSTRATIVE
This is a framework populated with sourced ranges, not a forecast. Every cell is either a sourced range or a flagged USER INPUT. FX placeholder USD 1 ≈ INR 85 (USER INPUT). Pilot = Bengaluru, 50–80 keys (Canon §8). Bengaluru is modelled conservatively (city ran 64.8% occupancy, heavy supply).
Driver inputs (sourced ranges):
| Driver | Range used | Source / flag |
|---|---|---|
| Keys (Phase 1) | 50–80 | Canon §8 |
| Capex/key, ex-land | ~₹1.3–1.4cr (Upscale, escalated to 2025–26) | D §1, H — borne by developer in JV |
| Land | 12–22% of total project cost | D §1 — excluded from Nest.IQ capital base |
| ADR (blended; city-specific preferred) | ~₹8,500 | D §2, H within market |
| Occupancy (base → stabilized) | 72% base; 78–82% upside; Bengaluru ~65% | D §3 / Canon §6 |
| Property-level EBITDA (pre-corporate G&A) | 28–40% net-property (corporate housing) | D §4, "Reasonable" |
| Stabilization | 18–24 mo base; 24–36 mo downside (supply-heavy BLR) | D §5, M |
Illustrative gross residence revenue (arithmetic per Canon §7: keys × occupancy × ADR × 365; label ILLUSTRATIVE; before ancillary + cross-sell):
| Phase | Keys | Illustrative gross room revenue |
|---|---|---|
| Phase 1 | 50–80 | ~US$1.3–2.1M |
| Phase 2 | ~300–500 | ~US$7.9–14.6M |
| Phase 3 | 1,500+ | ~US$39–58M |
Reading the pilot economics:
- Capex is the developer's, not Nest.IQ's. At ~₹1.3–1.4cr/key ex-land for 50–80 keys, the building investment sits on the developer's balance sheet. Nest.IQ's capital base is operating set-up + working capital, not bricks — the core reason the model scales (Sonder failed on fixed lease obligations; Ascott endures asset-light — Canon §3).
- Nest.IQ's fee economics flow from §6: a base 2–4% of that residence revenue plus 5–15% of GOP, with the absolute rupee amount small at pilot scale and compounding with the Phase 2/3 key count. Property-level EBITDA of 28–40% accrues to the developer (or is shared per the negotiated split).
- Stabilization of 18–24 months means the pilot underwrites to steady-state inside two years given pre-let demand — faster than the ~3-year hotel norm precisely because demand is contracted, not bought (D §5).
What is deliberately NOT shown: a multi-year P&L, an IRR, a valuation number, or a JV split. Those depend on the USER INPUTS in §9 and would violate the no-fabrication rule.
8. Cost structure, margins, and working capital
Two margin layers — keep them separate:
- Property-level EBITDA (pre-corporate G&A): 28–40% is the reasonable band for a well-run owned serviced apartment in India (D §4). Reference points: India listed hotels ~36%; IHCL ~35%; Lemon Tree owned ~46.8%; Ascott SR gross ~45.8%; OYO asset-light ~17.5%.
- Corporate G&A is a separate deduction. The benchmarks above are mostly property-level/gross; central overhead (sales, the .IQ platform, leadership) must be subtracted to reach net. The "mobility-integrated 35–45%" claim is aspirational and unbenchmarked — flag it (D §4); the old deck's "hotels 18–25%" is understated for Indian owned upscale.
- Corporate G&A load is a USER INPUT (target EBITDA by model + overhead — Canon §7).
Working capital — a structural advantage of corporate housing (D §8):
| Item | Characteristic | Effect |
|---|---|---|
| Corporate (B2B) receivables | 45–90 days common; ~63% of B2B on credit | A drag Nest.IQ must finance (DSO) |
| Security deposits (as operator) | Commercial up to 6 months' rent (New Rent Law 2025); refund 15–30 days of vacancy | A source of float |
| Pre-opening costs | ~5–9% of dev cost (in developer's capex) | Bundled, not Nest.IQ's burden |
| Payback / ROI context | Hotel payback 7–10 yrs; ROI ~10–15% | Asset-level, accrues to the asset owner |
Net read: large refundable corporate deposits are a float source, and contracted monthly billing shortens DSO versus OTA-dependent hotels — favourable working capital, offset by enterprise net-45/60/90 terms that create a receivables line Nest.IQ finances. Actual receivables terms and deposit policy are USER INPUTS.
9. User inputs (do NOT assume)
The model is a framework: sourced ranges plus explicit input cells. These must be supplied (Canon §7; D §"Inputs"):
- USD/INR rate · 2. Land treatment in the JV · 3. Capex/key per city & tier · 4. Per-city ADR · 5. Per-city stabilized occupancy · 6. JV economic split (fee / rev-share / guarantee) · 7. Stabilization ramp · 8. Target EBITDA by model + corporate G&A load · 9. Tech-premium thesis (SaaS revenue share for valuation) · 10. Corporate receivables terms · 11. Security-deposit policy · 12. Raise size / capital sources.
10. Model-specific risks & mitigations
| Risk | Why it matters | Mitigation |
|---|---|---|
| Lease-heavy fragility | Sonder's Chapter 7 (Nov 2025) was killed by ~US$303M/yr fixed lease vs transient revenue [Competitive §8.5] | JV-led, not asset-heavy lease. No fixed rent obligation against uncertain demand |
| Single-partner concentration | One anchor client/partner failing can sink the model | Diversified 1,000+ client base; lead Embassy JV with Prestige as backup (Canon §1) |
| Ascott fuses operator + aggregator | The one incumbent able to copy the fused thesis [Competitive §9] | Speed and lock-in: developer JVs + multi-year enterprise contracts before the window closes |
| Bengaluru supply glut | 64.8% city occupancy, heavy new supply [D §3] | Model BLR occupancy conservatively (~65%); pre-let contracts; campus-adjacent density in the highest-demand sub-markets |
| Receivables drag | Enterprise net-45/90 terms strain cash [D §8] | Security-deposit float; disciplined DSO; deposit policy as a financing lever |
| Cross-sell attach uncertainty | Attach-rate is a genuine data gap [Canon §6] | Treat as a flagged input, not a baked-in number; validate in pilot before scaling LTV claims |
| Valuation over-promise | $500M needs a proptech/SaaS or RE-equity multiple [D §7] | Underwrite to the $150–300M defensible base; present $500M only as a narrative ceiling |
| Margin overstatement | "Mobility-integrated 35–45%" is unbenchmarked [D §4] | Underwrite to 28–40% property-level; deduct corporate G&A explicitly |
Sources: Strategy Canon; Brief-D Operating & Financial Benchmarks (source IDs [S1]–[S16], registry in the TAM/SAM/SOM report §8 Sources); Competitive Analysis Report. Confidence grades and source IDs carried inline. All forward figures are ILLUSTRATIVE framework outputs from sourced ranges; no forecast is asserted.