More Materials / Case Studies
Illustrative scenarios showing what changes when the system actually gets used. No real names, because none of the book's stories use them either, but the mechanics are exactly as described. These are not verified real cases, they're worked examples built to show the frameworks in motion.
Chapter 1 · ICP & Disqualifiers
Before
One qualified call in six weeks, from a client list of "anyone who needs words."
After
Three qualified calls in the first two weeks after narrowing.
A freelance copywriter was pitching website copy, email sequences, ad copy, and blog posts to anyone who'd take a call, roughly 30 outreach messages a week across founders, marketers, and agency owners. Six weeks in, she'd landed one qualified call and no clients. Her positioning line was "I write copy that converts," which described nothing anyone could check.
Instead of writing a better pitch, she wrote disqualifiers first: no pre-seed companies without a live product, no one asking for "just a few blog posts to start," no one who couldn't name a specific page that was underperforming. That last line cut her addressable list by more than half. She rewrote her positioning around the survivors: seed-stage SaaS companies with a live pricing page and a documented drop-off point.
The next two weeks, she sent 22 messages instead of 30, all to accounts that passed the disqualifiers. Three qualified calls came back, and two turned into paid diagnostic audits within the month. The message itself barely changed; who received it did.
What changed: The disqualifiers, not the pitch, did the filtering.
Chapter 2 · Fit × Timing, Research Ladder
Before
A purchased list of 1,000 contacts, a 4% open rate, zero replies in three weeks.
After
A researched list of 40 accounts, 6 replies and 2 meetings in the first week.
A solo founder selling scheduling software bought a list of 1,000 contacts from a data vendor and set up a sequence. Three weeks and roughly 1,000 sends later: a 4% open rate, no replies, and a growing sense that outbound "didn't work" for his product.
Rather than buying a second list, he ran the fit-times-timing grid on the accounts he already had. Strong fit meant a service business with more than three staff sharing one calendar; a timing signal meant a recent job posting for a front-desk or ops role. Cross-referencing both criteria took an evening and left 40 accounts out of the original 1,000.
For each of the 40, he spent about six minutes on the research ladder: company basics, who their customers were, the specific role of the person he'd contact, and one plausible relationship path in. He sent 40 messages referencing the actual hiring signal he'd found. Six people replied in the first week, two booked meetings, and one became a paying customer three weeks later. The purchased list of 1,000 never produced a single conversation.
What changed: A smaller, researched list outperforms a larger, unresearched one, because it isn't really a smaller version of the same list, it's a different list.
Chapter 6 · BATNA & Trading, Not Conceding
Before
A client asking for 30% off a $12,000 engagement, with a verbal "take it or we walk" implied.
After
Full price held, with a scope trade that both sides could defend.
An independent consultant had a proposal out for a $12,000 process-audit engagement. Two days before signature, the client's ops lead asked for 30% off, citing an internal budget cap, and mentioned they had "another option lined up" if it didn't work out. In the moment, with a slow month behind her, the discount felt easy to just say yes to.
Before the call, she'd written her reservation point on paper: the lowest she'd go was $10,200, and below that she'd rather take a smaller engagement with a different client she was already talking to. That number, written down before any pressure existed, was what she referred back to instead of guessing live on the call.
Instead of countering with a lower number, she offered a trade: full scope at $12,000, or a reduced scope, cutting the two lowest-value deliverables, the competitor benchmarking section and the quarterly follow-up review, at $10,500. The client picked the reduced scope. She kept her rate per deliverable intact, and the client got a number closer to their number without her simply cutting her price to keep the deal.
What changed: A reservation point written down before the pressure exists is what survives contact with the pressure.
Chapter 7 · Health Signals as Prompts, Genuine Check-Ins
Before
A 35% drop in weekly logins for a mid-tier account, three weeks before renewal.
After
A resolved integration bug and a signed renewal, caught in time to fix it.
An account manager tracking a portfolio of 40 accounts noticed one customer's weekly active logins had dropped from roughly 60 to 39 over two weeks, a health-score dip flagged by the dashboard. Renewal was five weeks out. The easy move would have been to file it as "probably fine, they're busy" or send the standard automated check-in that goes out to every flagged account.
She sent a specific, genuine message instead: "Noticed your team's logins dropped a fair bit over the last two weeks, anything change on your end, or is it just a slower stretch? No agenda, just want to catch it early if something's off." No mention of renewal, no pivot to upsell.
The reply came within a day: a recent update to their CRM had broken a sync integration, so half the team had quietly switched to checking data manually and stopped logging in altogether. It wasn't a satisfaction problem, it was a plumbing problem nobody had reported. Her team's engineer fixed the sync within a week, logins recovered, and the account renewed on schedule a month later. A generic "just checking in!" message, or silence, would have left the real cause undiscovered until the renewal conversation itself, by which point the account would likely have already decided to leave.
What changed: The dip was a prompt to ask a specific question, not a verdict to act on alone.
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