Original research, cross-engagement comparison
Deal origination case studies: what 7 engagements show.
Most claims about outsourced origination rest on one story, told once, with the weak quarters left out. Deal origination case studies are more useful lined up side by side than read one at a time, because a single engagement cannot tell you what is typical and what is luck. Across seven named, ongoing or recently closed engagements we run, the fastest produced a meeting one day after the first email and the slowest took sixty days to a signed mandate, and both are normal outcomes for the kind of buyer each one was.
This is not a roundup of claims. Every figure below is published on its own case study page, with a named client and a date range, so you can check it rather than take it on trust. The point is not any single number. It is what the seven together show about what makes an origination engagement start fast, and what makes one keep compounding after the first month.
What do seven real deal origination engagements actually show?
Lined up, these deal origination case studies show a wide range of starting speeds and a narrow set of causes behind the fast ones. Three are sell-side mandates (an advisory finding owners ready to sell), three are buy-side acquisition sourcing, and one is add-on sourcing for an existing platform, and the method was not identical across any of them.
| Engagement | Buyer type | Side | Time to first meeting or signal | Headline result |
|---|---|---|---|---|
| TobinLeff | M&A advisory, marketing and communications agencies | Sell-side | 1 day to first meeting | 34 meetings in 6 weeks, roughly 2.5x our platform average reply rate |
| BigTable | Acquisition sourcing | Buy-side | 2 days to first meeting | 37 positive replies in 3 weeks, roughly 4.5x our platform average |
| Paras Capital | Private equity, healthcare services | Buy-side | 1 week to first owner already considering a sale | 29 positive conversations, zero brokers or auctions involved |
| Hard Fork | Acquisition sourcing | Buy-side | Inside the first month | 7 meetings from 28 positive conversations in about a month |
| WestStar Physical Therapy | Buy-and-build, physical therapy add-ons | Buy-side | Not reported | 15 positive conversations with clinic owners, zero brokered |
| Agency Futures | Boutique M&A advisory, sell side | Sell-side | 60 days to signed mandate | Roughly 8 founder conversations a week, sustained 4+ months, across 5 segments |
| Merritt Healthcare Advisors | Healthcare investment bank | Sell-side | 3 weeks to 14 conversations | 133 conversations in 90 days, roughly 13 a week at the current run rate |
Our own deal origination benchmarks describe the aggregate, platform-wide shape of this across 1.7 million emails. These seven engagements are the other side of that same data: what the aggregate looks like when you pull out one named mandate and watch it alone.
How fast does a deal origination engagement produce a first meeting?
It depends on what counts as the first useful signal, and that differs by mandate type. TobinLeff and BigTable both produced a meeting inside two days of the first email, because both ran against universes narrow enough that nearly everyone on the list was a plausible fit. Paras Capital's fastest signal was not a meeting but a reply, in the first week, from an owner who said they had already been considering a sale and had told nobody. Agency Futures took sixty days to its first signed mandate, which sounds slower until you know what a sell-side mandate is worth: a retainer plus six-figure success-fee potential, where one closed deal pays for the engagement. Speed to first meeting and speed to the number that actually matters are not the same thing, and the mandate type decides which one to watch. Deal sourcing timeline covers the stage-by-stage version of this for programmes generally.
Why did some engagements run at several times the platform average reply rate?
In the two fastest cases, the cause was the target definition, not the writing. BigTable ran at roughly 4.5 times our platform average, the highest of any mandate we currently run, because the universe was cut down before launch to companies that genuinely fit the thesis and owners who were reachable directly rather than behind an intermediary. TobinLeff ran at roughly 2.5 times the platform average, but the more useful number on that page is a sixfold spread in reply rate between agency sub-verticals inside the same campaign: a public affairs agency owner and a production studio owner do not respond to the same message, even inside one category. Acquisition outreach targeting sets out why a narrower list outperforms a wider one on reply rate even though it looks riskier on paper.
Do buy-side and sell-side engagements produce different results?
Yes, in what they measure as success, not in whether direct outreach works. BigTable, Hard Fork, Paras Capital and WestStar are all buy-side: a fund or platform looking for owners to acquire, where the unit that matters is a qualified conversation or meeting. TobinLeff, Agency Futures and Merritt Healthcare Advisors are sell-side: an advisory looking for owners who might engage them to run a sale, where the unit that matters is a signed mandate, because one mandate can be worth more than a year of buy-side meetings. Sell-side vs buy-side origination goes through why the two need different targeting and messaging even though the underlying method, direct outreach to an owner rather than through a broker, is identical.
What happens to an engagement after the first month?
The ones with more than ninety days of data show the same pattern: results compound rather than spike and fade. Merritt Healthcare Advisors went from 14 conversations in the first three weeks to 133 within 90 days, and the run rate has held at roughly 13 new conversations a week five months in, after Merritt chose to double outreach volume. Agency Futures sustained roughly eight founder conversations a week for more than four months before the engagement closed on schedule. That is the difference between a campaign, which decays after the initial push, and standing infrastructure, which a client can turn up when they want more coverage. First 90 days of deal origination covers the general ramp curve this follows.
What separated the fast starts from the slow ones?
Four things recur across all seven, in this order of weight:
- 1. A universe narrow enough that every name on it genuinely fit the thesis. BigTable's speed came from this alone; a wider list would have felt safer and produced a quieter result.
- 2. Owners reachable directly, without a broker or a switchboard in the way. Paras Capital and WestStar both depended on this, because their categories are too small or too local to run through an intermediary at all, a point we expand on in what proprietary deal flow really means.
- 3. Positioning written per segment, not one message for a whole category. Agency Futures ran five agency segments in parallel, each with its own pitch, specifically to find out which part of the category would talk before spending the budget proving it the expensive way.
- 4. Qualification before anything reaches a calendar. Hard Fork's seven meetings came from 28 conversations that were read and categorised first, which is why none of the seven case studies here report a raw reply count as the headline, a distinction we cover in deal origination vanity metrics.
None of these four is about the message itself. That is the pattern worth taking from seven engagements that nothing taken from one would show.
If you would rather have this run for you, DealSource Systems does off-market deal sourcing for lower middle market private equity: owners reached directly before they run a process, for a flat $4,000 a month.
Frequently asked questions
How fast does deal origination typically produce a first meeting?
Across these seven engagements it ranged from one day (TobinLeff) to about two days (BigTable) for the fastest starts, and up to sixty days to a signed mandate for a sell-side advisory (Agency Futures), because a mandate is a different, slower unit than a meeting.
Do buy-side and sell-side origination engagements perform differently?
They measure success differently rather than performing differently: buy-side mandates count qualified meetings and conversations, sell-side mandates count signed engagements, but all seven ran on the same direct-to-owner method.
What causes an engagement to run at several times the average reply rate?
In both cases here that ran well above average, BigTable at 4.5x and TobinLeff at 2.5x, the cause was a target universe narrowed before launch to names that genuinely fit the thesis, not a difference in the message.
Does a narrow target list really outperform a broad one?
Yes: a wider list produces a bigger first-week number but a quieter result overall, while BigTable's narrow, reachable universe produced the highest reply rate of any mandate we currently run.
How many owner conversations should a new programme produce in its first quarter?
It depends heavily on category and universe size, but Merritt Healthcare Advisors reached 14 in three weeks and 133 within 90 days, which is a useful reference point for a healthcare-focused sell-side mandate specifically, not a universal target.
Do early results hold up over months, or just spike and fade?
In the two engagements with more than ninety days of data, results compounded rather than faded: Merritt's run rate held at roughly 13 conversations a week five months in, and Agency Futures sustained its pace for more than four months.
Is one case study enough to judge whether an origination partner works?
No, which is why deal origination case studies are more useful read side by side than one at a time: a single engagement cannot show you what is typical for your situation versus what was specific to that client's category, universe size or mandate type.
What is the difference between a positive reply and a qualified meeting?
A positive reply is any engaged response, including one that never goes anywhere, while a qualified meeting is a calendar entry with an owner who has been read and categorised first, which is why Hard Fork's seven meetings from 28 conversations is the more defensible number than a raw reply count would be.