Enroll hostel Business Model

Enroll hostel Business Model

• 1.
  Find Good Hostelin Any Cities
• 2.
  Problem Statement 1. SEARCHno easy way + no/stale data + occupancy 2. PRICE, LOYALITY 3. CONVIENCE: Transfers /admissions 4. safe PAYMENT 5. SHARING ECONOMY: facility , procurements. 6. No assured QUALITY, stats, history, facilities 7. No integrated software to manage hostel. 8. Non-AUDITED Facility Discovery, history 9. Lack of Hostel DATA (95%) and analytics.
• 3.
  Business Model :Part 1 0.22 crore 500 110 crore We charge 10% of student transaction first time. Or Rs 500 17% Prospects = 0.22 crore PROSPECTS CHARGE REVENUE
• 4.
  Business Model: Part2 Earn On 1 • Brokerage/Bid/Facility 2 • Consultancy/Analytics 3 • Hostel Software/Devices
• 5.
  USP Hostel Occupants 1.SAVE Money on Searches . (T/M/C) 2. SAVE Money on Brokerage 3. CONVIENCE Online Payment and EH Card. 4. Recommendation system for hostel suggestions 5. (T/M/C) Real time seat occupancy . 6. (T/M/C): Virtual Hostel on EH Card. 7. SHARE Hostel Ancillary Facilities EHCard. 8. QUALITY audit for rankings, quality of service. 9. Hostel analytics :CAT exam ,CA, company office etc.
• 6.
  USP Hostel Owners 1.MANAGE Money HM Software /App. on Cloud. 2. SAVE Online Payment and EH Card. 3. EARN: Bid seats high rent for high rank 4. MANAGE :Audit, Rank (own+Student) reviews 5. SHARE: Co-sourcing Grocery online grocers . 6. SHARE: Co sourcing hostel automation products 7. EARN: par with international dorms. 8. SHARE Facilities for deficient hostels on EH Card. 9. Hostel DATA analytics (where to build next hostel)
• 7.
  Market Size: 150crore 1. Calculations: Rent brokerage market 1500 crore. 2. 850 universities, 40,000 colleges. 3. 10% college seats = 4/40 lakh hostel seats. 4. School hostel 3/30 lakh. 5. School + College prospects = 7/70 lakh. 6. Working population hostel prospects = 15/40 lakh. 7. Total prospects = 22 lakh. 8. Market size @ Rs. 500 per student = 110 crore.
• 8.
  Projection Revenue in1 year  5 hostel/day X 4 = 20 per day = 20X250=5000 per year. (1,00,000 hostel in India) Largest site in country  5 colleges/dayX4= 20 per day= 5000 colleges covered. Largest in country presence in Hostel industry.  Very conservative 1% student conversation: Each college 12/1200 student booked = 60,000 booking. 0.6 Lakh X 500= 3 crore earning.  Break Even in under 6 months
• 9.
  Revenue Forecasting: inCrore 2017 • 3 (5000) 2018 • 15 (25000) 2019 • 50 (50000) 2020 2021 • 100 ( 1 Lakh) • 200 Crore Nepal, Mynamar, Thialand, Increase Avg Rev Per Hostel Increase Avg Rev Per Occupant Increase Hostel Funding #2(15 cr) 3L customer, 25000 hos/ Market Research Funding #1(0.7 cr) Hostel Marketing Team/BPO addition 1 mill cust./Sensor Devices/Consultancy/Dorms Increase deficient Facility Occupant/AR/Card World Largest Hostel Site, add ASEAN/Euro
• 10.
  Competition Competitors Repo sitory Occu pany Au dit facili ty No stale listing Onlin e payme nt % coverage HostelDunia YESNO NO Y/N NO NO 1% hostelnpg YES NO NO Y/N NO YES 1.5% nobroker Y/N NO NO NO NO NO 0.5% EnrollHostel YES YES YES YES YES YES No.1 in India JustDial YES NO NO Y/N NO NO 0.5% olx Y/N NO NO Y/N NO NO 0.1%
• 11.
  Investment: Cost/monthly Nos Salary Lakh Total Lakh Hostels/ Offices Expected Revenue Hostel Marketing 4 0.66 2.64 400 Student Marketing 4 0.66 2.64 400 x 10 4000X 500 =20 Lakh Salary Dev 4 0.75 3.00 Digital Marketing 1 0.35 1 Rent 1 0.50 0.50 Posters/BPO 2 0.50 0.50 Total 10.28 2-20Lakh
• 12.
  Seed Funding Requirement NosSalary Lakh Total Lakh monthly Hostels / Offices Expected Revenue Hostel Marketing 4 0.15 0.60 400 hostel per month Office Marketing 4 0.15 0.60 400 = 4000 Offices/colleges 2800X 500 =14 Lakh Salary Dev 2 0.50 1.0 Digital Marketing 1 0.25 0.50 Rent 1 0.25 0.20 Posters/BPO 2 0.10 0.10 Total 3.00 12-14 Lakh
• 13.
  Expense/Income Expenses Income 75 Lakh(6 months) 1.5 crore (6 months) First Six months 2,500 hostels+ 2500Colleges Double Marketing Team 6-12 month Re-invest in Business 1.5 crore Next Six months 5,000 hostel + 5,000 colleges Largest Site for hostel in 1 year 7,500 Hostel + 7,500 colleges 1 year = 0.75+ 1.5 = 2.25 crore 1 year = 1.5 crore + 3 crore= 4.5 crore
• 14.
  Expense/Income (Pune) Expenses Income firstmonth = 3.00 Lakh 400X500=2 Lakh Total in 2 months = 9 Lakh 800X500= 4 Lakh+2 Lakh Total in 3 months = 14 Lakh 1600X500=8 Lakh+6=14 Lakh 3 Months 1600 hostels 1600 hostel + 1600 colleges One of Top Indian Hostel site Top Search in pune/mumbai 30-50,000 followers
• 15.
  Current State: As-is Website/App is complete Ready with web software.  20 Lakh rupees of effort gone into it.  Integrated CRM, HR, Expense management Exists.  Tied up with Many hostels nearby with own marketing  Analysis data, blogs, social marketing Etc all setup.  Facebook, linkedin, google map integrated.
• 16.
  Future State:  LargestSite in world in 3 years for Hostel.  EH Hostel Data Analytics ( where to plan next hostel)  EH Card Services/ facility Services  AI based searches for required hostels.  Machine learning Recommendations for Users.  Virtual Hostel views to book seat. (Virtual Reality)  Hostel Security devices,Light kitchen devices. IoT  EH Hostel combined grocery sourcing.
• 17.
  Risk/Mitigation(Porter Forces):  95%hostel not covered by sites competitor Risk is very less.  Differentiated (7P) to cover commoditizing risks.  Differentiated offering for owners cover Growth risks.  Technology Risk: IT diff with AI/MR/VR/Analytic.  Focus ARPH/ARPO cover Revenue Risks.  Differentiated products offering: Risk of substitute or Risk of buyers  Customer Relationship/Quality risk: Hostel attended Trained on EH software,Techniques recruited for hostels (Full Time/Part Time/ Consultation basis
• 18.
  Summary 1. BIG OPPURTUNITY:95% market untapped. 2. Differentiated Product on all offering 7P, 7C. 3. Future VR can enter Reality market. 4. Sharing Economy and Co own opportunity. 5. World biggest Hostel Market. 6. Most South Asian Hostel deficient in automated swiping machine(s/w)/Solar heating/HM s/w, motion sensor lighting, Hostel ratings expanding young population colleges and company sparsely located