AI Agents Challenge

Dataset 1: Pipeline Insights

Tests ability to analyze sales pipeline metrics, identify bottlenecks, and forecast outcomes.

Dataset 2: Email Analysis

Evaluates understanding of customer communications, sentiment analysis, and key topic extraction.

Dataset 3: Sales Records

Focuses on historical sales data analysis, win/loss patterns, and deal value optimization.

Dataset 4: Rule Compliance

Tests ability to identify sales reps following or breaking specific process rules and policies.

Dataset 5: Performance Trends

Evaluates identification of top/bottom performers and understanding performance trends over time.

Dataset 1: Pipeline Insights

• How many deals are currently in the Negotiation stage, and what is the total Amount of those Negotiation deals?
• Which Lead Source has produced the most close won deals, and what was the conversion ratio?
• Identify the largest deal in the dataset (by Amount) and specify which sales Owner is responsible for it.
• Which deals have missing data?
• Which two records likely refer to the same client, and what steps should you take to resolve the duplicate to maintain data cleanliness?

Dataset 2: Email Analysis

• What is the sentiment of this email thread (e.g. positive, neutral, or negative), and what key concern is the customer expressing?
• Based on the conversation, what stage of the sales process is this opportunity likely in, and what is the prospect's main objection or hesitation?
• Summarize the key points of the exchange and suggest an appropriate next step for the sales rep to move the deal forward.
• Based on all email threads from the past, look at closed lost deals and identify which one has the highest potential to be re-engaged.

Dataset 3: Sales Records

• Update XYZ opportunity's Stage to Closed Won.
• Calculate the expected total forecasted revenue from these opportunities and identify which deals to mark as high-confidence wins for this quarter.
• Which opportunities should be flagged as at-risk, and why?
• Here are 10 upcoming leads and 100 historical leads (some sold, some not). Rank the 10 leads based on the historical data, and explain.
• Here is a transcript of a meeting. Provide notes, analysis, and specific employee notes.
• Draft a sales follow-up email to the MavTech deal (just lost in the final stage).

Dataset 4: Rule Compliance

• Rule 1 (Send follow-up emails within 3 days): List 5 sales reps who always follow this rule.
• Rule 2 (Always personalize follow-ups): Do sales reps who follow this rule deliver more revenue than those who do not? If so, how much?
• Rule 3 (Close deals that are in the pipeline for more than 30 days): How many sales reps are compliant with this rule?
• Rule 4 (Do not offer more than 10% discount): How many sales reps are compliant with this rule?
• Rule 5: How many sales reps are compliant with this rule (whatever the specific rule #5 might be)?

Dataset 5: Performance Trends

• What performance trend do you observe over the year, and what might this imply for the next quarter's focus or targets?
• Which 5 sales reps have the biggest revenue results?
• Which sales rep is performing more effectively, and what metrics support that conclusion (consider a 50% win rate, 40% quota attainment, and 10% average deal size)?
• At which stage of the funnel is the largest drop-off occurring? Offer a recommendation to improve conversion at that stage.
• Provide strategic recommendations to improve overall sales performance. (Think in terms of training, process changes, resource allocation, or pipeline adjustments.)
• List the common sales pipeline stages (e.g., Prospecting, Qualification, Proposal, etc.) and briefly describe what happens in each stage.