Sales Pipeline Diagnosis Chain

validated business chain v1.0.0 cc-by-sa

Block ID: 65d9246f-9bae-4c6b-98b5-e29d46ca19c9

Community-contributed block. PromptDNA makes no guarantee of output quality or fitness for purpose. User assumes all responsibility for use.

Template

Diagnose the sales pipeline problem in {pipeline_context} by locating where deals actually stall or die. (1) Reconstruct the pipeline by stage with conversion rates and time-in-stage, because "sales are down" is not actionable until you see whether the problem is too few deals entering, deals stalling at a specific stage, or deals dying late — each is a different problem with a different fix. (2) Distinguish a top-of-funnel volume problem (not enough qualified opportunities) from a conversion problem (opportunities not advancing) from a velocity problem (deals taking too long), since pouring more leads into a pipeline that converts poorly just widens the leak. (3) Find the stage with the worst conversion or the longest stall and reason about why deals die there specifically — a consistent drop at one stage points to a fixable cause (a pricing objection, a missing proof point, a decision-maker not engaged), while blaming the aggregate close rate hides it. (4) Check lead quality versus execution: are the wrong deals entering (a targeting or qualification problem, so reps waste effort on deals that were never going to close), or are good deals being mishandled? These have opposite remedies. (5) Separate a real performance problem from normal variance or a timing shift. (6) State where the pipeline breaks, the likely cause, the highest-leverage fix, and what data would confirm it before changing the sales motion.

Diagnose the sales pipeline problem in {pipeline_context} by locating where deals actually stall or die. (1) Reconstruct the pipeline by stage with conversion rates and time-in-stage, because "sales are down" is not actionable until you see whether the problem is too few deals entering, deals stalling at a specific stage, or deals dying late — each is a different problem with a different fix. (2) Distinguish a top-of-funnel volume problem (not enough qualified opportunities) from a conversion problem (opportunities not advancing) from a velocity problem (deals taking too long), since pouring more leads into a pipeline that converts poorly just widens the leak. (3) Find the stage with the worst conversion or the longest stall and reason about why deals die there specifically — a consistent drop at one stage points to a fixable cause (a pricing objection, a missing proof point, a decision-maker not engaged), while blaming the aggregate close rate hides it. (4) Check lead quality versus execution: are the wrong deals entering (a targeting or qualification problem, so reps waste effort on deals that were never going to close), or are good deals being mishandled? These have opposite remedies. (5) Separate a real performance problem from normal variance or a timing shift. (6) State where the pipeline breaks, the likely cause, the highest-leverage fix, and what data would confirm it before changing the sales motion.

Variables

Name	Type	Required	Trust level
pipeline_context		yes

salespipeline-analysisconversionchain-of-thought

Ratings

0.0

Overall (0)

0.0

Accuracy

0.0

Consistency

0.0

Clarity

0.0

Efficiency

Benchmarks

Not yet self-validated against any benchmark. Automated, evaluative only - not a factor in whether this block was published.

Submitted by James P FounderMod via mcp · 2026-07-18