Lab 2 · Write a discovery questionnaire

Objective

Given a fictional customer brief, draft a 20-question discovery questionnaire that covers business context, technical landscape, and success criteria.

Time: 45-60 minutes Prerequisites: Read Standard CS workflows (Phase 1: Discovery) and Templates.

The scenario

You’ve just been assigned to a new prospect: MegaFreight, a mid-size freight forwarder based in Dubai.

What you know so far (from the sales handoff):

• 200 employees, operating in 12 countries (Middle East + South Asia)
• Handle 800 RFQs per day via email (mostly unstructured)
• Current quoting process takes 4-6 hours per RFQ
• Losing deals to faster competitors
• CEO wants to “automate 80% of quotation” within 6 months
• They use SAP TM for freight management
• They’ve heard about Shipsy from the Aramex case

Your task

Draft a 20-question discovery questionnaire organized into four sections:

Section 1: Business context (5 questions)

Understand the business, the pain, and what success looks like.

Hints:

• Volume and growth trajectory
• Current cost of quoting (people × time × error rate)
• Win rate on RFQs — does speed matter?
• Seasonal patterns
• What “80% automation” means to them specifically

Section 2: Process deep-dive (5 questions)

Understand the current quoting workflow, step by step.

Hints:

• Where do RFQs arrive? (email, portal, phone)
• What formats? (structured forms, free-text email, attachments)
• What data does the analyst need to produce a quote?
• Which Incoterms do they handle? All 11 or a subset?
• What’s the approval workflow? Who signs off on quotes?

Section 3: Technical landscape (5 questions)

Map their systems and integration points.

Hints:

• SAP TM version and customizations
• Rate management — where are tariffs stored?
• Email infrastructure (Exchange, Gmail, custom)
• Data residency — any restrictions on cloud processing?
• Existing APIs or integration experience

Section 4: Success criteria & timeline (5 questions)

Define measurable outcomes and constraints.

Hints:

• KPIs they’ll measure (response time, accuracy, win rate)
• Who are the stakeholders? (CEO, ops, IT, finance)
• Timeline expectations vs reality
• Budget range (or at least: is budget approved?)
• Pilot scope — which routes/customers to start with?

Exercise

1. Write your 20 questions.
2. For each question, note why you’re asking it — what will the answer tell you about the deployment?
3. Identify which 5 questions are most critical (must-answer before you can scope the solution).

Reference solution

After completing the exercise, compare your questionnaire with:

• The discovery questionnaire template
• The RFQ + Freight AI agent page — what technical details would you need to confirm?
• The Aramex case study — what can you learn from a similar deployment?

Checklist

• 20 questions drafted across 4 sections
• Each question has a “why” annotation
• Top 5 critical questions identified
• Compared with reference material

What you learned

• How to structure a discovery conversation
• What information drives agent scoping decisions
• How to connect business pain to technical architecture

Next steps

• Lab 3: Reverse-engineer Maya
• Industries we serve for industry-specific questions

Changelog

• 26 May 2026: Full lab content with fictional scenario, structured exercise, and reference solution pointers.