Period Comparison Investigation

Compare any two time periods to understand what changed and why.

---

The Question

"What changed this quarter compared to last quarter?"

Or variations:

• "Compare Q3 to Q2"
• "What's different about this month vs last month?"
• "How did performance change year over year?"
• "What improved and what declined?"

---

What Scoop Investigates

Scoop performs a comprehensive comparison:

Investigation Plan:
├── Probe 1: Identify all metrics
│   └── What metrics exist in the data?
├── Probe 2: Calculate changes
│   └── How did each metric change?
├── Probe 3: Find significant changes
│   └── Which changes are statistically meaningful?
├── Probe 4: Analyze by dimension
│   └── Break down changes by segment, region, etc.
├── Probe 5: Identify drivers
│   └── ML analysis: What factors drove the changes?
└── Synthesis: Executive summary

---

Example Output

Investigation Results: Q3 vs Q2 Comparison

SUMMARY:
Overall performance improved with revenue up 12%,
but customer acquisition costs increased 23%.

KEY IMPROVEMENTS:
├── Revenue: +12% ($4.2M → $4.7M)
├── Win Rate: +8 points (32% → 40%)
├── Customer Satisfaction: +0.4 points (8.1 → 8.5)
├── Deal Size (avg): +15% ($24K → $28K)
└── Time to Close: -5 days (45 → 40 days)

KEY DECLINES:
├── Customer Acquisition Cost: +23% ($850 → $1,045)
├── Lead Volume: -18% (1,200 → 984)
├── Trial Conversion: -3 points (28% → 25%)
└── Support Response Time: +2 hours (4h → 6h)

BREAKDOWN BY SEGMENT:
├── Enterprise: Revenue +24%, Win Rate +12 pts
├── Mid-Market: Revenue +8%, Win Rate +2 pts
└── SMB: Revenue -3%, Win Rate -1 pt

ROOT CAUSE ANALYSIS:
├── Revenue increase driven by 3 large enterprise deals
├── Win rate improvement correlated with new demo process
├── CAC increase due to 40% higher ad spend (CPL up 35%)
├── Lead volume decline from paused content marketing
└── Support slowdown linked to 2 team departures

RECOMMENDED FOCUS AREAS:
1. Investigate high CAC - ROI may not justify spend
2. Resume content marketing for lead volume
3. Address support capacity before it impacts CSAT
4. Document enterprise success factors to replicate

---

Sample Prompts

Basic Comparison

"What changed this quarter vs last quarter?"

Specific Metrics

"How did revenue and costs change month over month?"

With Focus Area

"What changed in our enterprise segment this quarter?"

Year Over Year

"Compare this Q3 to Q3 last year"

Root Cause Focus

"Why did performance change between Q2 and Q3?"

---

Follow-Up Questions

---

Data Requirements

Any dataset with:

The more metrics and dimensions, the richer the comparison.

---

Types of Comparisons

Sequential Periods

• This month vs last month
• This quarter vs last quarter
• This week vs last week

Year-Over-Year

• Q3 2025 vs Q3 2024
• This month vs same month last year
• Rolling 12 months vs prior 12

Custom Ranges

• Before vs after product launch
• Pre-campaign vs post-campaign
• First half vs second half

---

Understanding the Analysis

Significant vs Noise

Scoop identifies which changes are meaningful:

• Statistical significance testing
• Filters out random variation
• Highlights changes worth investigating

Dimension Breakdowns

Shows WHERE changes happened:

• By customer segment
• By product line
• By region/territory
• By team member

Root Cause Analysis

Uses ML to find WHY changes happened:

• Correlation analysis
• Factor importance
• Pattern detection

---

Tips for Better Comparisons

1. Ensure date coverage - Both periods need sufficient data
2. Include dimensions - Enables breakdown analysis
3. Add context fields - Campaign, rep, source for richer analysis
4. Consistent definitions - Same metrics calculated the same way

---

Related Patterns

• Pipeline Investigation - Pipeline-specific comparison
• Revenue Investigation - Revenue-focused analysis
• Churn Investigation - Compare churned vs retained