👋What’s New
Quick one this week. Been head’s down ironing out last minute bugs and UI fixes for RaffleLink 2.0 (which is why I’ve been MIA on Tik Tok this week) - we sent it out to family and friends for some simple testing before we release it to our early beta users next week.
It’s not 100% there and feels a bit rushed but it’s good enough for people to use and get real feedback. Kind of funny how excited I get seeing people just…use the app? Lol
Anyways - three interesting deals this week, all SBA pre-qualified. Let’s get into it.
💼 3 Businesses For Sale
1. Hardscape & Masonry Business (Tennessee)
$250K asking | $216K cash flow | ~1.2x multiple
East Tennessee contractor specializing in stone veneer, brick, and decorative hardscaping. Active builder relationships. All referral-driven.
Why it's interesting:
Pays itself back in ~14 months
Skilled trade = barrier to entry
Builder relationships are sticky
Only question is would you need to be there in person or does it run on it’s own?
The question: Why so cheap? Health issue? Partnership breakup? At this price, worth a call to find out. Could be a steal.
Link: BizBuySell
2. Digital Marketing Agency for Interior Designers
SBA Pre-Qualified | 8 years | 80% retention | 2-3 hrs/week owner time
Niche agency serving design-driven brands. Has a podcast and YouTube presence. 99.9% of clients come inbound. Contracts start at 6-12 months, then go month-to-month.
Why it's interesting:
Hyper-niche = you know exactly who to target
Seems like owner’s found a repeatable proven system of business
Owner works 2-3 hours/week
Only question is how much of the business like the podcast and Youtube channel are tied to her personal brand?
Link: WebsiteClosers
3. Collectible Toy eCommerce (Funko POPs)
SBA Pre-Qualified | 22 years | 66% YOY profit growth | ZERO ad spend
Pop-culture collectibles, mainly Funko. 95% Amazon, 4,300+ SKUs, 36% net margin. $500K inventory included. Gets 1M Amazon page views monthly with no paid ads. One exclusive release made $27K profit in under 5 minutes.
Why it's interesting:
22 years = proven staying power
Dominant position in a niche business
Zero ad spend = organic demand is real
Exclusive supplier relationships = moat
The catch: It's a bigger operation. Might be overwhelming for a first-time buyer. But the systems are there.
Link: WebsiteClosers
💡 2 Insights This Week
1. Use Earnouts Strategically (Not as a Crutch)
Earnouts get a bad rap because they're often used to paper over valuation gaps. But they're actually great for specific risks you can't fully diligence.
Use earnouts for things like:
Customer concentration — Tie a portion to retention of the top 3 clients
Equipment condition — Holdback if major repairs are needed in year 1
Key employee retention — Payment contingent on the ops manager staying 12 months
Recurring revenue verification — If they claim 80% recurring, prove it over 6 months
Don't use earnouts as a generic "we'll figure out the price later." That creates misaligned incentives and resentment.
Rule of thumb: Earnouts should address a specific, measurable risk — not just bridge a negotiation gap.
2. SaaS Acquisition Data (Acquire.com Jan 2026 Report)
Some interesting numbers from Acquire.com's latest multiples report:
Median profit multiple: 3.9x (unchanged from 2024)
Average time to sell: 81 days
Average profit margin of listed businesses: 71%
Public SaaS multiples: Crashed from 17x (2022) → 5.5x (2025)
Private SaaS (<$10M): Held steady around 4x profit
What to takeaway from this data? It’s good to know what to expect and what is market so when you look at a deal ask if it is market and if not why?
📖 1 Story
AI Agents: You Can't Force the Use Cases
I've been playing with AI agents — automated assistants that can run tasks, pull data, write code, etc.
When I first set up my system, I sat down and tried to brainstorm: "What should I have this thing do?" Came up blank. Everything felt forced or over-engineered.
But then something shifted. Instead of trying to invent use cases, I just kept going about my work — and kept a mental note of moments where an agent could help.
Slowly, the ideas came:
Sentry throws an error → agent pulls the logs, references my codebase, and explains what broke
Stripe webhook fails → agent checks the event, cross-references Posthog, tells me why
GCP logs fill with noise → agent surfaces only what matters
None of this was obvious on day one. It came incrementally. The more I worked, the more I saw the gaps. The more comfortable I got, the more I trusted it with.
The lesson: Don't force AI agents into your workflow. Just stay aware. The use cases reveal themselves when you're actually doing the work — not when you're trying to manufacture them.
See y’all next week,
@eddieacquires