wayland-icp-build

name	wayland-icp-build
description	Build an Ideal Customer Profile from existing customer data and market signals: infer segments, pick the best-fit segment, write the full profile, and define the disqualifiers. Use when the user wants to define who their best customers are and produce a reusable ICP document with explicit disqualifiers. Do NOT use for prepping a single discovery call (use wayland-discovery-prep) or building a cold outreach sequence (use wayland-outreach-build).
license	Apache-2.0
type	workflow
skills	sales-coach sales-icp sales-qualify
metadata	{"author":"wayland","version":"1.0.0","tags":"sales icp customer-profile segmentation qualification step-by-step","category":"sales","depends":"sales-coach sales-icp sales-qualify"}

ICP Build

Estimated time: 30-45 minutes

This workflow builds an Ideal Customer Profile, the profile of the customers worth pursuing. It works best with real customer data, but can build from hypothesis if none exists (the result is weaker). The output is an ICP document: data source, segments considered, best-fit segment, full profile, and disqualifiers.

Run the sales-coach agent throughout. Each step feeds the next.

Steps

Step 1: Gather the Offer and Customer Data (uses: sales-coach)

Ask the user for the offer and whatever data they have about existing customers: a pasted list, a path to a CSV, or a description of their top five best customers. Tell them that without real data you can still build from hypothesis, but it will be weaker. This is an interactive step: ask, then wait for the inputs before continuing.

• Input: user-provided offer and customer data (or hypothesis)
• Output: data_inputs (offer plus customer data or stated hypothesis)
• Key focus: get as much real customer data as the user can provide

Step 2: Infer Customer Segments (uses: sales-icp)

From the data (or hypothesis), infer the distinct customer segments. State the inferred segments and your reasoning. Present them as an inference the user can confirm or adjust.

• Input: data_inputs from Step 1
• Output: segments (the candidate customer segments, plus reasoning)
• Key focus: distinct, defensible segments grounded in the data

Step 3: Identify the Best-Fit Segment (uses: sales-icp)

From the inferred segments and the data, identify the best-fit segment using willingness-to-pay, lifetime value, acquisition cost, and strategic fit. Show the best-fit segment and the criteria behind it.

• Input: segments from Step 2, data_inputs from Step 1
• Output: best_segment (the chosen segment plus the fit criteria)
• Key focus: pick the segment with the best economics and strategic fit

Step 4: Review and Refine the Best-Fit Segment (uses: sales-icp)

Show the best-fit segment and ask the user to refine the criteria or proceed to the full profile. If they want changes, fold their feedback back into the selection (up to three passes) and re-present. Once approved, advance.

• Input: best_segment from Step 3, segments from Step 2, user feedback
• Output: approved best_segment
• Key focus: let the user adjust the criteria before profiling

Step 5: Build the Full ICP Profile (uses: sales-icp)

Build the full ICP profile of the best-fit segment: firmographics, demographics, psychographics, pain points, success criteria, and current alternatives. Show the profile to the user.

• Input: best_segment from Step 3
• Output: profile (the full ICP profile)
• Key focus: a complete, specific profile the team can target against

Step 6: Review and Refine the Profile (uses: sales-icp)

Show the full profile and ask the user to refine it or proceed to disqualifiers. If they want changes, fold their feedback in (up to three passes) and re-present. Once approved, advance.

• Input: profile from Step 5, best_segment from Step 3, user feedback
• Output: approved profile
• Key focus: a profile the user signs off on before defining who to avoid

Step 7: Build the Disqualifiers (uses: sales-qualify)

From the profile, build the disqualifiers: the prospects the user does NOT want, even if those prospects ask to buy. Show the disqualifiers to the user.

• Input: profile from Step 5
• Output: disqualifiers (explicit anti-ICP criteria)
• Key focus: protect the pipeline from bad-fit deals up front

Step 8: Final Review and Ship the ICP (uses: sales-qualify)

Show the disqualifiers and ask the user to ship the ICP document or refine the disqualifiers. If they want changes, fold their feedback in (up to two passes) and re-present. When they ship, assemble the ICP document: data source, segments considered, best-fit segment, full profile, and disqualifiers.

• Input: disqualifiers from Step 7, data_inputs, segments, best_segment, profile, user feedback
• Output: icp_document (the assembled Ideal Customer Profile)
• Key focus: deliver a reusable ICP the whole team can target against

Expected Outcome

An Ideal Customer Profile document containing the data source, the segments considered, the best-fit segment, the full ICP profile, and the disqualifiers.