AI Super Simplified

The Data Analysis Test

Same messy CSV. Two models asked to find the insight hidden in the numbers — no chart libraries, just logic and output. One found it. One got close.

1

The exact prompt we used

prompt.txt — fed identically to both models
Here is monthly revenue data for a fictional SaaS company. Analyze it, find the most important business insight a CEO should act on, and explain your reasoning in plain English. Show calculations inline. Month/MRR/New Customers/Churned/Support Tickets: Jan $42K/18/3/24, Feb $44.1K/21/4/31, Mar $47.2K/19/2/28, Apr $49.8K/15/7/67, May $48.1K/12/9/89, Jun $45.2K/10/11/112, Jul $43.8K/8/12/134

Don’t take our word for it. Paste this into any AI model and compare your result against the outputs below.

2

What each model wrote — the exact answers, side by side

Claude Opus 4.8Model answer

The most important signal in this data is hidden in the support-ticket column, not the revenue line — and the CEO should act on it now.

Revenue looks healthy until you line it up by month. MRR climbed from $42K in January to a peak of $49.8K in April, then fell three months straight: $48.1K (May), $45.2K (June), $43.8K (July) — a 12% slide from the peak in a single quarter ($49.8K → $43.8K).

But that decline is a lagging symptom. The earliest warning sign is support tickets, which exploded a full month before MRR peaked:

  • Jan–Mar held steady: 24, 31, 28 tickets.
  • April jumped to 67 — up 139% over March (28 → 67).
  • Then 89 (May), 112 (June), 134 (July) — about 4.8× the Q1 level.

Churn follows the same curve, one step behind: 3, 4, 2, then 7 (April), 9, 11, 12 (July) — a 6× rise from March. New customers move the opposite way: 18, 21, 19, then 15, 12, 10, 8.

Put acquisition and churn together and the real story appears — net customer change per month:

  • Feb / Mar: +17 each
  • April: +8
  • May: +3
  • June: −1  ← the company starts shrinking
  • July: −4

The business crossed from growth into contraction in June, and the trigger traces back to whatever broke around April, when tickets more than doubled.

The insight to act on: a product or service-quality problem emerged in April. It surfaces first as a support-ticket surge, then as rising churn, then as falling MRR. More acquisition spend won’t fix it — that’s pouring new customers into a leaking bucket (new adds are already down ~56% from the February high while churn is up 6×).

What I’d do first: pull every April ticket and find the single change — a release, a price change, an outage, a policy — that set this off, and fix that before funding any new growth. The support queue is both the smoke and the fire.

Model answer — exact text returned
GPT-4oModel answer

To analyze the data, let's summarize the Monthly Recurring Revenue (MRR), number of new customers acquired, number of churned customers, and support tickets over this seven-month period. By doing this, we can understand the trends and identify key insights that could be beneficial for the CEO.

Key Metrics Analysis:

  1. Monthly Recurring Revenue (MRR) Growth:
    • Jan: $42K
    • Feb: $44.1K
    • Mar: $47.2K
    • Apr: $49.8K
    • May: $48.1K
    • Jun: $45.2K
    • Jul: $43.8K

    Trend: The MRR increased from January to April ($42K to $49.8K), but then started to decrease from May onwards, reaching $43.8K in July. This pattern indicates an initial growth followed by a decline.

  2. New Customers:
    • Jan: 18
    • Feb: 21
    • Mar: 19
    • Apr: 15
    • May: 12
    • Jun: 10
    • Jul: 8

    Trend: There is a clear downward trend in acquiring new customers. The number of new customers decreased each month from a high of 21 in February to just 8 in July.

  3. Churned Customers:
    • Jan: 3
    • Feb: 4
    • Mar: 2
    • Apr: 7
    • May: 9
    • Jun: 11
    • Jul: 12

    Trend: The churn rate is increasing, with more customers leaving the service each month. It increased from 3 churned customers in January to 12 in July.

  4. Support Tickets:
    • Jan: 24
    • Feb: 31
    • Mar: 28
    • Apr: 67
    • May: 89
    • Jun: 112
    • Jul: 134

    Trend: There is a significant rise in support tickets, which increased from 24 in January to 134 in July. This suggests growing customer support issues.

Insight and Recommendation:

Insight: The most critical insight is that the company is facing increasing customer dissatisfaction, as evidenced by the rise in churn rate and support tickets. The rise in support tickets could imply that customers are facing issues with the service that are not being resolved effectively, leading to increased churn and a decline in MRR.

Recommendation: The CEO should prioritize improving customer satisfaction and service quality. This could involve:

  • Enhancing Support: Invest in enhancing customer support to handle the growing number of issues more efficiently. This could involve expanding the support team or implementing more sophisticated customer support tools.
  • Identifying Pain Points: Conduct thorough investigations into the issues customers are facing to understand the root causes and find solutions or improvements in the product or service.
  • Retention Strategies: Implement strategies to retain customers, such as loyalty programs, better onboarding experiences, and more effective engagement strategies.

By focusing on improving customer experience and satisfaction, the company could reduce churn, lower support tickets, and stabilize or even increase its MRR.

Model answer — exact text returned
3

What to look for

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