SaaS and AI appointment scheduling software
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Background
| BizEx ID: | BizEx1369-SL |
|---|---|
| General Location: | San Jose, CA |
| Category: |
Software & Technology Healthcare |
| Years in Business: | 2 |
| Under Present Owner: | all |
| Hours of Operation: | flexible |
| Owner Hours: | part-time |
| Training: | 10 weeks @ 4 hours |
| Organization Type: | C-Corp |
| Lease Expiration: | n/a |
| Lease Options: | n/a |
| Building Size: | n/a |
| Employees: | 3 |
| Reason for Sale: | Part of strategy to scale |
Financials
| Asking Price: | $500,000 |
|---|---|
| Down Payment: | Negotiable |
| Gross Sales: | $20,000 |
| Discretionary Cash Flow: | Call |
| FF&E: | n/a |
| Inventory Included? | No |
| Inventory: | n/a |
| Min. Operating Capital: | $6,000 |
| Real Estate Available? | No |
| Rent: | $0 |
| 2019 | 2020 | 2021 YTD | |
|---|---|---|---|
| Gross Sales | $ 19,000 | $ 20,000 | $ 0 |
| Gross Profit | $ | $ | $ |
| Disc. Earnings | $ 4,000 | $ | $ |
Description
Problem this solution solves: Scheduling/appointment issues are a constant problem that medical practices and clinics encounter every week. Each week practices and clinics review their schedule for the week and see that it is generally fully booked. However, as the week progresses, they see open appointment slots in their schedule because of patient cancellations, rescheduling, and no-shows. By the end of the week, approximately 20% of their appointments would be no-shows and another 10% late cancellations. The seller's interviewed over 150 physicians, administrators, front office staff, and patients across medical practices, healthcare systems, and US Veterans Healthcare Administration (VHA), and this issue came up repeatedly. In summary, the problem of no-shows and late cancellations impacts patients, office staff, and healthcare providers in the US healthcare system in the following ways: 1) Poor patient experience due to longer wait times to get appointments; 2) Lost productivity for the office staff and physicians; 3) Increased patient follow-up costs for the medical practice or health system, and 4) Loss of revenue for the medical practice or health system.
Size of the problem: A Harvard Business Review article estimated that every year over $150B is lost in healthcare in the US because of no-shows/missed appointments, and patients waited 18.5 days on average to get an appointment.
Solution: A SaaS based product available today that can predict cancellations with over 90% accuracy and backfill those appointments in the future with 'waiting list' patients.
Traction: Live with their first client since 2019. Lifetime revenue from this client/practice is $39K
Opportunity:
The sellers believe that their solution can be tightly integrated with a telehealth solution and would allow filling predicted no-shows or last-minute cancellations over video. Lastly, this solution can address needs in other verticals (hospitality, restaurants) that face the problem of no-shows.
Ask Price:
500k plus an earnout component
Disclaimer: The information herein is furnished by the seller; BizEx has not verified this information and makes no representation or warranty as to its accuracy, completeness, or authenticity. Future earnings may differ from past earnings. Discretionary Earnings is defined as earnings before deducting interest, taxes, depreciation, and amortization, and adding Owners salary, benefits and non recurring expenses.
