The proof
Real businesses. Real numbers. Anonymized.
What the library says is possible, this section shows in practice: what a real business thought its problem was, what I found when I looked, and what the fix was worth. Every number is labeled for exactly what it is.
They thought: They wanted to hire two more estimators. Quote volume was climbing and the sales team felt underwater.
I found: The estimators were not the bottleneck. Quotes sat an average of 4.2 days before anyone opened them, and roughly 1 in 5 was never sent at all. They were losing winnable jobs to whoever quoted first.
They thought: The firm thought it needed a bigger intake team to handle call volume and stop leads slipping to competitors.
I found: Volume was fine. Consistency was the problem — after-hours calls went to voicemail, and the qualifying questions changed depending on who picked up. Strong cases were being triaged out by accident.
They thought: The owner blamed marketing — he figured he needed to spend more on ads to grow.
I found: He was already getting the calls. He just could not answer them. Techs are on rooftops; the phone rings out. Nearly a third of inbound calls went unanswered, and most callers dialed the next plumber instead of leaving a message.
They thought: Leadership assumed they needed a custom internal tool built to kill their monthly client reporting slog.
I found: The slog was real — roughly 30 analyst-hours a week copying numbers between dashboards — but a bespoke build was the wrong call. Ninety percent of the need was already solved by tools on the market.
Start with the free AI Opportunity Score — the same first pass I run at the start of every Audit.
Start with the free Score