Offr Financial Model
PropTech Startup Financials (Free Excel Download)
B2B SaaS platform that embeds a white-label "Offr Button" on estate agents' own websites, digitising the end-to-end property transaction (offers, viewings, legal docs, deposits, contracts).
professionals from Deloitte
Used by professionals from
About this model
Offr embeds a white-label button on estate-agent websites to digitise offers, viewings, legal documents, deposits, and contracts. It gives agents an end-to-end property-transaction workflow while preserving the agent's own customer relationship and brand.
The company sells B2B software to estate agents rather than buyers and sellers. Ireland is the primary market and the UK is active, while multi-currency and multi-language functionality supports wider expansion; it participated in the Barclays Accelerator powered by Techstars.
The model forecasts agency clients, transactions, SaaS fees, per-transaction revenue, implementation, expansion, and churn. Support delivery, compliance, sales capacity, gross margin, and customer retention determine how transaction adoption converts into recurring revenue and runway.
A turnkey financial model
Live formulas, no hardcoded values
Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.
All assumptions in one tab
Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.
Statements always balancing
For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.
Distinct schedules for clarity
Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.
No hidden macros or external links
There are no unexplained external workbook links or macros to undermine auditability or portability.
Changes flow through the model
Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.
About Offr
offr.io
How to build a detailed financial model for Offr
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Offr model - distilled from its pitch deck and publicly available information.
Product & value proposition
- White-label "Offr Button" embedded on the estate agent's own website and branding.
- Buyers can: submit qualified offers, upload proof of funds, book viewings, download legal packs, sign contracts (DocuSign integration), pay deposits (Stripe integration) - all from mobile.
- Supports multiple sale types: private treaty, auction, tender, new homes, lettings.
- Agent-side dashboard: real-time offer tracking, pipeline analytics, buyer vetting (AML/KYC), WhatsApp notifications.
- Legal data-room for solicitors to manage packs, queries, and replies.
- Core moat: patent-pending Offer Processing Engine (EP19194457.8) + trademark.
- Key claim: reduces transaction timeline from 6–9 months (analogue) to 2–3 months (Offr).
Market
- £500bn value of properties sold every year (UK market implied).
- 10 million individual offers made to buy property every year.
- 2.5 million people involved in property transactions per year.
- 1 million+ buyers per year.
- Fall-through rate of 25–33% cited as a core pain point (lost economic value).
- No SAM/SOM breakdown, no market growth rate, no Ireland-specific market size stated.
Revenue model
- Not explicitly stated in deck. No pricing slide, no fee schedule shown.
- Business model inferred: B2B SaaS subscription per agent/branch, with possible per-transaction or per-listing fees - typical for PropTech platforms of this type. The product is embedded on the agent's website, so agents are the paying customer.
- Channel: direct sales to estate agents; named customers suggest enterprise/mid-market relationships (Sherry FitzGerald = largest estate agent group in Ireland).
- No revenue figures, no ARPU, no pricing tiers disclosed.
Traction & metrics
- Named estate agent customers (5 logos shown): Sherry FitzGerald, REA Dempsey & Sothern Auctions, Harvey, artis real estate, Herbert & Lansdowne Estate Agents.
- Case study A (24 Mar 2020, Sherry FitzGerald auction): 13 registered bidders, 29 bids, guide price €360,000, sale price €580,000, 61% over guide, 60-minute session.
- Case study B (auction): 6 buyers, 36 offers, guide price €200,000, sold €267,000 (33.5% over reserve); reserve exceeded at €211,000, opening offer €195,000, winning offer €267,000.
- 800 people watching the COVID-19 auction live stream (24 Mar 2020).
- Dashboard sample data (illustrative, not confirmed as live production totals): property summary showing 7,946 / 698 / 252 / 690 / 36 / 10,922 across pipeline stages; €31.8m total portfolio value shown in demo data. - treat as UI demonstration, not verified KPI.
- No ARR, MRR, transaction volume, or churn figures disclosed.
Competition / moat
- Competitor landscape not explicitly shown; deck focuses on replacing the analogue process (email, phone, verbal offers) rather than named tech competitors.
- Moats cited: patent-pending Offer Processing Engine, trademark, first-mover claim (Ireland's first fully digital remote property transaction), deep multi-stakeholder integration (buyer, seller, both solicitors, banks, insurers, surveyors).
- Network effect potential: once agent uses Offr, all their buyers/solicitors are drawn into the platform.
- White-label approach reduces disintermediation risk - agents keep their brand identity.
Team & funding ask / use of funds
- Robert Hoban (CEO): former Director at Bidx1 (online property auction tech), former Senior Auctioneer at Allsop Ireland, 2,000 properties sold by online auction, 4,000 by physical auction, €1bn+ in property sales, 18 years' experience.
- Philip Farrell (CCO): former CEO of Real Estate Alliance (REA), largest nationwide group of chartered surveyors in Ireland, 30 years' experience, media commentator and industry advisor.
- Niall Dawson (CTO): former Head of Technology and co-founder at Xsellco (1st in Deloitte Technology Fast 50 Ireland), 20+ years building scalable tech across pharma, defence, ecommerce, recruitment, sport.
- Additional team (slide 35): Vicky Carroll (Head of Product), Aideen Warfield (Legal Administrator), Hayley Marjoram (UX/UI), Aidan Quigley (Marketing & Customer Success).
- Investors: Frontline Ventures, Enterprise Ireland, European Investment Fund, Delta Partners, Bank of Ireland, AIB.
Recommended financial model
- Archetype + why: B2B SaaS with per-seat / per-branch subscription + optional per-transaction revenue layer. Offr sells to estate agents (the "seat"), not to end buyers/sellers. Core drivers are agent sign-ups, branches per agent, listings per branch, and transaction volume. A 3-statement model underlies the SaaS ARR build, but the primary output should be an ARR waterfall (new ARR, expansion, churn, net revenue retention).
- Forecast horizon & granularity: 5 years (Y1–Y5), monthly for Y1–Y2, quarterly for Y3–Y5. Monthly granularity needed because the deck implies early-stage sales motion and Techstars cohort timing.
- Key drivers & assumptions:
- Agent customers (starting count): minimum 5 named logos; model from ~5–10 paying agents at deck date (2020), given early stage
- Branches per agent: ~5–15 branches for mid-market agents; Sherry FitzGerald has 100+ (use tiered segmentation: SME agent 1–5 branches, mid-market 5–20, enterprise 20+)
- Monthly subscription per branch/seat: £200–£500/month per branch, typical for UK/IE PropTech SaaS (no deck data)
- Per-transaction fee (optional layer): 0–£50 per completed transaction; deck does not confirm this model
- Listings per branch per month: ~10–30 based on estate agent industry norms
- Sales cycle: 1–3 months for SME, 3–6 months for enterprise; deck implies Sherry FitzGerald was an early adopter
- Gross margin: 70–80%; SaaS software with Stripe/DocuSign pass-through costs
- Churn rate: 10–15% annual; agent stickiness should be high once embedded (workflow dependency), but early-stage risk is real
- CAC: founder-led sales in Y1; estimate £2,000–£5,000 per agent for SME, £10,000–£30,000 enterprise
- LTV: derived from ARPU × gross margin ÷ churn
- Headcount: 7 people visible at deck date; sales and engineering hires as primary cost driver
- Geography expansion: product is multi-currency, multi-language (GBP, EUR, USD shown); UK primary launch market post-Ireland
- Scenarios (Base / Bull / Bear - which variables flex):
- Base: Steady agent acquisition (~5–10 new agents/month by Y2), mid-market pricing, 12% annual churn
- Bull: Enterprise contract with large agent networks (REA-type groups with 50+ branches each), lower churn (7%), add-on transaction fees unlock
- Bear: Slow adoption post-COVID tailwind, high churn (20%), no transaction fee monetisation, UK expansion delayed
- Required sheets / outputs:
- Assumptions dashboard (all drivers in one place)
- ARR build (cohort waterfall: new ARR, expansion, contraction, churned ARR, net new ARR)
- Revenue schedule (subscription MRR × branch count × pricing tier; optional transaction revenue)
- P&L (gross margin, OpEx by category: R&D, sales & marketing, G&A)
- Headcount plan (by department, with salary assumptions)
- Cash flow & runway (key output for fundraising context)
- Unit economics summary (CAC, LTV, LTV/CAC, payback period)
- Scenario toggle (Base / Bull / Bear)
Frequently asked
Is the Offr financial model free?+
Yes. The Offr model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.
What's included in the model?+
A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.
How was this model built?+
It was built from Offr's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.
Can I change the assumptions?+
Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.
Have more financial modelling questions? Contact us
Created by ex-finance professionals
Hey, I’m Alex and I created Finamodel.
Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.
Every model here is one I’d actually use for a client, and I personally vet each one before it goes up.
I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.
Having a template library on hand cuts a first build from hours to minutes.
Need help finding your model? You’ll find me in the Finamodel app!
Other PropTech Startup Financial Models
Browse another startup in the same category.
Agora
Agora automates operations for real estate investment firms - investment accounting, fundraising, CRM, investor reporting, portal, and data room in one platform.
Briq
SaaS platform that automates money workflow management (budgeting, forecasting, cash flow, WIP) for construction companies.
Canary Technologies
B2B SaaS platform providing guest management and digital operations software to hotels
Geodesic.Life
Sustainable prefabricated geodesic dome houses for rural development, sold as a design + prefab kit + consultancy bundle to real estate partners.
Huboo
Full-stack, software-driven e-commerce fulfilment network built on a micro-warehousing model, targeting SME merchants across UK and Europe.
Immo
Tech-enabled iBuyer that acquires single-unit/single-family residential properties directly from homeowners, renovates and rents them under the IMMO Homes brand, and aggregates the portfolios into institutional investment products.
Kasa Living
Tech-enabled hospitality operator that manages furnished apartments and hotel units on behalf of property owners, capturing a share of room revenue without owning real estate.
Latch (Door.com)
Latch is an enterprise proptech company selling LatchOS, a full-building smart-access and SaaS operating system for multifamily residential buildings, going public via SPAC merger with TS Innovation Acquisitions Corp. (TSIA).
