── ── Mental model
Objection Handling — Surface, Understand, Resolve
Objections are information, not rejection. Most lost deals die not from the stated objection but from an unsurfaced real one (budget authority, risk, status quo). The discipline: draw objections out early, understand the true concern behind the script, and resolve it with evidence — rather than arguing or discounting reflexively.
Run Objection Handling — Surface, Understand, Resolve on a real problem
Bring something you're actually deciding — free, in the browser.
How it works
1. Invite objections early — "what would stop this from being a fit?" Better surfaced in discovery than at close. 2. Acknowledge, don't argue — lower defenses first; "makes sense" beats a rebuttal. 3. Find the real objection — the stated one is often a proxy. "Too expensive" may mean unclear ROI, wrong authority, or fear of switching. Gate: resolving the surface objection without the real one = the deal still stalls. 4. Isolate & confirm — "if we solved that, is there anything else?" so you're not fighting a moving target. 5. Resolve with evidence — proof, references, a trial, risk-reversal — matched to the real concern (money, risk, timing, authority). 6. Ask for the advance again. Gate: no re-ask = the handled objection is wasted.
When to use it
- deals stall on 'too expensive', 'not now', 'need to think about it', 'send me info'
- a founder gets flustered by pushback
- improving close rate
When not to use it
the prospect is genuinely unqualified (then disqualify, don't 'handle').
Worked example
Objection Handling — Surface, Understand, Resolve
Objections are information, not rejection. Most lost deals die not from the stated objection but from an unsurfaced real one (budget authority, risk, status quo). The discipline: draw objections out early, understand the true concern behind the script, and resolve it with evidence — rather than arguing or discounting reflexively.
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skillsUseful? Star the repo — stars help other builders find it.
Related mental models
OKRs separate ambition from measurement: an Objective is qualitative and aspirational; Key Results (3-5) are quantitative outcomes proving the objective was reached.
Colonel John Boyd (1927-1997) derived the OODA Loop from Korean War air-combat data: the F-86 Sabre achieved a ~10:1 kill ratio over the technically superior MiG-15…
People remember experiences not by averaging all moments but by sampling two: the peak (highest emotional intensity) and the end.
A power-law distribution is a statistical distribution where probability of size x is proportional to x^(−α): large events are rare but far more probable than a…