Define Success Before CRM Launch

Project Background

HubSpot is preparing to launch an AI-assisted lead scoring feature for its mid-market CRM product. The feature is intended to improve sales team prioritization before the start of Q4, when customer acquisition volume peaks. You are the program manager assigned to align the team on what success looks like before engineering begins implementation.

The project team includes 10 people: 4 engineers, 1 data scientist, 1 designer, 1 product manager, 1 QA lead, and 2 go-to-market partners. Leadership wants a launch-ready plan in 8 weeks because a competitor released a similar feature last month.

Key Stakeholders

The VP of Product wants a visible Q3 launch and a clear business case. Sales Leadership wants measurable lift in rep productivity within one quarter. The Data Science lead wants enough time to validate model quality and avoid shipping a weak experience. Customer Success is concerned about false positives that could reduce trust with existing customers.

Constraints

• Total budget remaining: $180,000
• Timeline: 8 weeks to beta launch, 12 weeks to general availability
• Engineering capacity: 4 engineers, with 1 shared 30% on another roadmap item
• Data dependency: model training data from 18 months of CRM activity, with known gaps in 12% of records
• No additional headcount approved this quarter

Complications

1. Sales has already told three strategic customers the feature will be available in beta within 6 weeks.
2. Legal requires review if customer-level explanations are shown in the UI, which could add 10 business days.
3. The PM wants broad feature scope, including score explanations and workflow automation, while engineering recommends a narrower MVP.

Your Task

1. Define the project success criteria the team should agree on before build starts.
2. Propose how you would align stakeholders on scope, launch readiness, and trade-offs.
3. Create an execution plan from definition through beta launch.
4. Identify the top risks to meeting the agreed success criteria.
5. Recommend how success should be measured during beta and before GA.