Discovery Question Generator

Replace the same six discovery staples with 10 questions tied to your prospect's real stack.

Enterprise B2B marketing · Discovery readiness signal

Active CDP evaluation + dual-warehouse chaos = a wide-open data platform door

100
CDP intent score
Trend +4 and rising · Researching stage · Snowflake + Teradata running simultaneously · Tableau displacing 4 incumbent BI tools
SignalWhat it meansUrgency driver
CDP score 100, trend +4Active buying cycle forming nowChampion identity unknown — get in first
Snowflake (2018) + Teradata (2005) both liveDual-warehouse sync gap for marketingNo single segment source — campaigns stall
Digital Industries profit −28% FY2024Prove pipeline ROI fast budget pressureCFO + CMO need attribution in Q1
Open with this
“Your CDP intent spiked to 100 while Snowflake and Teradata are both live. Who owns the marketing-data use case on that evaluation?”

Overview

Your AEs walk into discovery calls with the same six SaaS-Q&A staples every prospect has heard. This workflow generates 10 specific, open-ended questions grounded in HG firmographic, technographic, FAI, and intent data — each anchored to a specific data point (a named tool, a recent SEC signal, a peer-cohort delta). Reps walk in sounding like they did the homework, not like they read a discovery template.

Use cases

  • First discovery calls that earn the next meeting

    When your AEs walk into a first discovery, the buyer has heard the same six 'tell me about your business' staples ten times this quarter. This workflow generates questions anchored to specific HG signals: a named tool the prospect added in the last 6 months, a peer that recently moved off it, a category where the prospect is under-spending vs cohort. Buyer hears credibility instead of template.

  • BDR-to-AE handoffs that don't restart from zero

    When a BDR books a meeting and hands it to an AE, the AE often re-asks every question the BDR already covered. This workflow takes the prospect's HG technographic + intent + FAI signals, generates 10 fresh questions that build on what's already known, and tags each with the data point it springs from. The AE arrives knowing what's been said and what hasn't.

View workflow prompt
# Discovery Question Generator

## Parameters

- `{{domain}}` *(required)* — Target company domain HG Insights uses for lookup. Example: `siemens.com`
- `{{product_context}}` *(optional)* — What you're selling — calibrates the questions and their path-to-pitch notes. Example: `data platform for B2B marketing`

## Purpose
You are an AE preparing for a discovery call with {{domain}}. The output is 10 specific, open-ended questions — each anchored to a real data point about the target — organized into Operating Context / Technical Reality / Buying Process. No generic "what keeps you up at night" filler. Every question opens a credible path to {{product_context}} (or to discovery if that's empty).

## Process
1. **Operating context** — call `company_firmographic` for {{domain}}. Capture industry, scale, recent restructuring or M&A. The first 3 questions probe operating challenges specific to that company's shape (industry-specific compliance, post-M&A integration, scale-driven complexity).
2. **Technical reality** — call `company_technographic` and `company_cloud_spend`. The next 4 questions reference specific stack items: integration friction between two named tools, capability gaps where the target has the legacy tool but not the modern equivalent, vendor consolidation pressure where 3+ point-solutions overlap.
3. **Buying process** — call `company_intent` and `sec_filing_section`. The last 3 questions probe why they're researching {{product_context}} (or adjacent categories), recent strategic disclosures relevant to the buying environment, and decision-maker tenure.
4. **Path-to-pitch notes** — for each question, append a 1-line note explaining the question opens a path to {{product_context}}. If {{product_context}} is empty, append a generic discovery note (what the question reveals about budget, urgency, or technical fit).

## Output Format
Markdown with these sections in order:
- `# 🎯 {{domain}} — Discovery Questions` (header + product context line)
- `## Operating Context (Q1-Q3)` (each question + path-to-pitch note)
- `## Technical Reality (Q4-Q7)` (each question + path-to-pitch note)
- `## Buying Process (Q8-Q10)` (each question + path-to-pitch note)
- `## Source signals used` (bullet list of the data points each question is anchored to)

Every question references at least one specific tech-stack item, industry challenge, or recent signal — never generic.

## Quality Checklist
- All 10 questions are open-ended (start with "How", "What", "Why", "Where", "Who", "When")
- Each question explicitly names a tech-stack vendor, a recent event, or an industry-specific challenge
- No two questions probe the same signal — each opens a different path
- Path-to-pitch notes are concrete (cite the {{product_context}} feature/value-prop), not generic
- Source-signals appendix lists every HG / SEC / web data point referenced