Ongoing Grader Optimization

Once you've built your grader, the name of the game is continuous improvement. The following ideas are the best of the best ways to improve, pulled from hundreds of in-depth conversations with high-performers using PipeAI to win more better deals faster.

The overarching theme of optimizing your grader and your performance is this: keep repeating the cycle of refining, testing, and learning what works and what doesn't. The more records (e.g., leads and opportunities) you grade, the better you get.

Grader Optimization Workspace

PipeAI offers a dedicated Grader Optimization workspace where you can monitor, analyze, and improve your graders' performance. To access it, simply select the grader you want to optimize from your dashboard.

At the top of your workspace, you'll find the AI-Power indicator showing how much recent usage your grader has received across your team. The more your team uses a grader, the more AI-power accumulates to surface increasingly powerful and actionable insights.

Core Optimization Features

Issues

Issues are manually logged by team members when they identify potential problems with grader results. When a team member clicks the thumbs-down button under a grade or action recommendation, they can add details about the issue for future review.

Closeouts

Closeouts are automatically captured each time a record is marked as converted or closed. When a pipeline record reaches this stage, a short questionnaire appears, collecting valuable information on whether the outcome was a win/conversion or a loss, along with user feedback on learnings while the experience is still fresh.

This process provides critical validation data that helps connect grader recommendations to final outcomes. It's also an excellent opportunity to take a short breather and reflect on what led to this outcome—considering whether:

  • The grader is capturing the right information via the right questions and responses
  • Response grades and impact multipliers (if in use) are calibrated appropriately
  • Actions and their rules are striking the right balance of investing the right amount of energy based on records' grading results

Regular review of Closeout data helps ensure your grader evolves to better predict successful outcomes.

AI-Insights

AI-Insights are automatically generated as your grader usage grows. These insights become more numerous and powerful as more grading data becomes available for analysis, helping you identify optimization opportunities without manual analysis. Requires Pro plan

AI Chat Analyst

Engage with our AI analyst assistant through a dedicated chat interface to explore your grader data in depth. This powerful feature allows you to ask specific questions about your grader's performance and receive customized analysis and recommendations. Requires Pipemaster plan

When you're ready to implement changes, simply click "Show grader setup" to make adjustments without leaving the Grader Optimization workspace.

Valuable AI Chat Prompts

The AI Chat Analyst can help you uncover powerful insights about your grader. Here are some of the most valuable questions to ask:

→ "Questions to add' ideas" Ask for suggested new questions that could strengthen your grader based on patterns in your data.

→ "Response grade adjustment' ideas" Get recommendations for fine-tuning your response grades to better align with actual outcomes.

→ "List top easy/hard questions (avg. response grade)" Understand which questions consistently receive high or low grades across your records.

→ "Response impact multiplier adjustment' ideas" Receive suggestions for recalibrating your impact multipliers to better reflect real-world importance.

→ "List strongest leading indicators of wins/losses (question-response pairs)" Identify the specific combinations of questions and answers that most reliably predict success or failure.

→ "Questions with biggest difference in response grades across users" Discover where your team members might be interpreting or answering questions differently.

→ "Identify grader blindspots based on closeout data" Find what your grader might be missing based on records that performed differently than predicted.

→ "Recommend action rule adjustments based on conversion patterns" Get suggestions for refining your action recommendations based on what's actually driving conversions.

→ "Compare grading patterns before and after recent grader changes" Evaluate the impact of your most recent grader updates to see if they're having the desired effect.

→ "Identify ideal question sequence for qualification efficiency" Discover the optimal order of questions to quickly determine record quality with the fewest questions.

→ "Show team members with highest conversion rates and their grading patterns" Learn from your top performers by understanding their unique approach to quality assessment.

Grader Optimization Tips

→ Grade Result vs. Gut-Feel Misalignment If the overall grade for some records seems off—either too low or too high:

  • Review Questions: Ensure you're capturing all relevant information.
  • Adjust Responses: Make sure each response impacts the overall grade appropriately.

→ Incorrect Action If you disagree with the recommended next best action:

  • Review Action Details: Check if you need to update the minimum grade or adjust your Action Rules.
  • Fine-Tune: Add, remove, or change Actions to align Action recommendations with your expectations and requirements.

→ Team Discussions Regular Discussions: Schedule meetings to discuss grading criteria, share results, and gather input.

  • Compare Results: Identify top performers and underperformers to develop improvement strategies.
  • Check-Ins with Other Teams: Engage with marketing, customer success, and leadership to find grader improvement opportunities.

→ Positive Surprises Stay open to unexpected insights from you and your teammates' selling efforts:

  • New Questions: Identify what information should be captured by adding new grader questions to see if they provide meaningful quality signals.
  • Update Responses: Adjust responses to better assess quality for future grader runs.

→ Balancing Your Grade Distribution Grade Analysis: If the average grade across all grader runs seems to be too low or too high:

  • Adjust Response Grades: Consider adjusting response grades to bring overall grade averages closer to a balanced "C" range.
  • Reevaluate Impact Multipliers: If using Impact Multipliers, double-check all of them to ensure you're not over- or under-weighting any responses.

→ AI Suggestions Leverage AI insights:

  • Pattern Matching: Ask PipeAI's AI which questions and responses lead to wins, losses, or stalled deals.
  • Implement AI Suggestions: Implement updates suggested by PipeAI's AI when they align with your observations and instincts.

Best Practices for the Optimization Workspace

  • Regular Team Reviews: Schedule periodic team reviews to go over Insights, Issues, and Closeouts together in the Optimization workspace.
  • Mark Items as Reviewed: As you review insights and issues, mark them as "Reviewed" or "Resolved" to keep your workspace organized.
  • Document and Communicate Changes: When making adjustments to your grader, ensure all team members understand what has changed so they can continue to monitor performance and provide feedback.

The more you use your graders, the more powerful these AI features become, creating a virtuous cycle of continuous improvement and increasingly accurate pipeline decisions.