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Onboarding Plan for Multi-Site Enterprise Client

Piano di onboarding cliente enterprise multi-sede · Customer Success · Advanced · 250 XP

A new enterprise client with 12 locations and 800 users is starting implementation. The user must build an onboarding plan that accounts for the complexity of multi-site rollout, trains regional champions, manages executive sponsor engagement, and tracks adoption across locations.

Write the prompt you would give any AI (ChatGPT, Claude, Gemini, Copilot) to solve this real workplace scenario. Grace evaluates it in seconds across 7 dimensions: Role, Context, Objective, Constraints, Format, Audience, Efficiency: with a 0-100 score and coaching feedback. Your first 5 evaluations each day are free.

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Frequently asked questions

What is the "Onboarding Plan for Multi-Site Enterprise Client" scenario on Grace?

A new enterprise client with 12 locations and 800 users is starting implementation. It is an advanced-level Customer Success training scenario: you write the prompt you would give an AI to handle this situation, and Grace scores it from 0 to 100 with coaching feedback.

How many XP is "Onboarding Plan for Multi-Site Enterprise Client" worth?

Completing this advanced scenario earns up to 250 XP. XP accumulates toward your level on Grace and unlocks badges and the certification exam.

Who is "Onboarding Plan for Multi-Site Enterprise Client" for?

It is designed for Customer Success professionals and anyone who wants to handle this kind of situation with AI. The advanced difficulty makes it a solid test for experienced prompt writers.

Can I retry "Onboarding Plan for Multi-Site Enterprise Client" to improve my score?

Yes. Read the coaching feedback, strengthen the weak dimensions and submit again: your best score is what counts. When you clear it, 8 related Customer Success scenarios are waiting.

Do I need to pay to try this scenario?

You get 5 free evaluations every day, zero credit card required. That is enough to attempt "Onboarding Plan for Multi-Site Enterprise Client", read the feedback and retry with a stronger prompt.

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