Diligence pricing is usually a black box: an hourly engagement, a scope letter full of qualifiers, and a final bill you learn at the end. I price Digital Deal Diligence at a flat $5,900 with a 5-to-7-day turnaround, so the least I can do is publish exactly what that buys. This is the full scope, and just as importantly, what it is not.
For context on why I built it this way: I evaluated roughly 50 software companies as an M&A advisor at Carbon6, about one a month, and I have been the seller in two exits of my own. The diligence below is the work I found actually changes buy decisions on sub-$2M digital deals, with the ceremony stripped out.
1. Financial verification against source systems
The seller's P&L is the claim. The source systems are the evidence. This phase reconciles the two: Stripe or the payment processor for SaaS, Seller Central settlement reports for Amazon businesses, the ad accounts and order systems for DTC. I am looking for revenue that exists on the P&L but not in the processor, refunds netted out of view, intercompany or personal transactions mixed in, and the gap between cash collected and revenue claimed.
This is the step that most often kills deals, and it is the step a buyer cannot do from a broker's data room, because data rooms contain exports the seller prepared. The work is in getting read access to the systems themselves and reconciling from the raw transaction level up.
2. MRR and churn reconstruction
For SaaS and subscription businesses, I do not take the seller's MRR chart. I rebuild it from the subscription ledger: every customer, every plan change, every cancellation, from raw billing events. That reconstruction surfaces the things a summary chart hides: annual prepays smeared across months to flatten a decline, paused accounts counted as active, discounted cohorts about to renew at full price and churn, founder-friends accounts that never paid.
Churn gets the same treatment, cohort by cohort. A blended churn number is close to meaningless; what you are buying is the retention curve of recent cohorts, because that is the revenue that will still exist in a year.
3. Traffic authenticity analysis
Revenue quality depends on traffic quality. This phase separates what the listing calls "organic" into what it actually is: durable non-branded search, branded search that may not transfer, paid traffic, referral spikes, and traffic exposed to AI answer engines absorbing informational queries. I check ranking history, link-velocity patterns that suggest bought links, and the dependence of revenue on a small number of keywords or a single acquisition channel.
4. Platform and transfer risk
Digital businesses live on rented land. This phase documents which platforms the business depends on, the account health and suspension history on each, whether the accounts and contracts legally transfer, and how exposed the model is to policy changes already in motion, like marketplace API restrictions or advertising policy shifts. The output is a transfer map: what moves cleanly, what needs consent, and what cannot move at all.
5. Codebase and infrastructure review
For software assets, I review the codebase and infrastructure the way an operator would: how it is hosted and what it costs, what breaks if the one contractor leaves, how much of the stack is deprecated or unmaintained, where the security exposures are, and what the real monthly run cost looks like compared to what the seller reports. The question is not "is the code beautiful." It is "what does it cost to operate and change this thing without its author."
6. The AI Ops Underwrite
This is the part of the report nobody else does, and it comes from running my own software company on 130+ AI systems. Every report ends with a quantified model of the business with a modern AI operations layer installed: which manual loops disappear, what the owner-hours requirement drops to, and what that does to the P&L you are underwriting. You are not just buying what the business is. You are buying what it becomes under competent ownership, and that number belongs in your model before you set a price.
Digital Deal Diligence is $5,900 flat, 5 to 7 days, built for sub-$2M digital deals. If you are earlier than that, start with the $950 Red-Flag Scan instead.
Start an EngagementThe honest QoE comparison
A Quality of Earnings report is an accounting work product, usually CPA-prepared, focused on normalizing earnings and validating add-backs. On small deals it typically runs $20-40K, which is exactly why buyers skip diligence on sub-$2M deals: the insurance costs more than the risk seems to justify. That is backwards. Sub-$2M sellers are the least audited sellers in the market.
| CPA-prepared QoE | Digital Deal Diligence | |
|---|---|---|
| Price | $20-40K typical | $5,900 flat |
| Core question | Are the normalized earnings right? | Is the asset real, and what does it become? |
| Revenue check | Accounting records and bank statements | Source systems: Stripe, Seller Central, billing events |
| MRR / churn | Usually out of scope | Rebuilt from raw subscription data |
| Traffic, platform, code | Not covered | Core scope |
| Lender acceptance | Required for most SBA deals | Not a QoE substitute |
When you need a CPA instead
Straight talk, because it is also on the diligence page: I am not a CPA firm and this is not an audit. You need a CPA-prepared QoE when your lender requires one, which is the norm for SBA-financed acquisitions. You want one when the deal is large enough that tax structuring, working-capital pegs, and GAAP-level normalization move real money, generally above the $2M range. On those deals, my scope runs alongside the CPA's, covering the digital-asset questions their engagement letter does not touch. On a $400K content site or an $800K SaaS, a $30K QoE does not pencil, and this is the diligence that does.
Questions buyers ask
Is digital deal diligence the same as a Quality of Earnings report?
No. A QoE is an accounting work product, usually CPA-prepared, focused on normalizing earnings, and typically costs $20-40K. Digital deal diligence verifies the things a QoE never touches: whether revenue matches source systems like Stripe and Seller Central, whether MRR and churn are what the seller claims, whether traffic is authentic, and whether the code and platform accounts survive a transfer.
When do I need a CPA instead of, or in addition to, this?
If your deal is SBA-financed, your lender will likely require a CPA-prepared QoE; this service works alongside that, not instead of it. You also want a CPA when the deal is large enough that tax structuring, working-capital pegs, and GAAP-level earnings normalization drive real money, generally above the $2M range. This is not an audit and is not a substitute for one.
Why is the price flat at $5,900?
Because hourly diligence creates an incentive to expand scope and a bill the buyer cannot predict. The scope of a sub-$2M digital deal is knowable in advance, so the price can be too. Flat pricing also makes the math easy: on a $500K acquisition, $5,900 is about 1.2% of the purchase price to find out whether the asset is real.
What is the AI Ops Underwrite?
Every report ends with a quantified model of what the business looks like with a modern AI operations layer installed: which manual loops disappear, what the owner-hours requirement drops to, and what that does to the P&L you are underwriting. It is the part of the report that treats the business as what it can become, not just what it is.