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ShedBox Agent for Product Managers

Make data-driven product decisions without waiting for data teams.

The Product Manager Challenge​

Product managers need data to:

  • Understand user behavior
  • Track feature adoption
  • Measure experiment results
  • Report on product metrics

But they often wait days for data team support.

ShedBox Agent gives you instant access to product data.

How Product Managers Use ShedBox Agent​

Instant User Analysis​

"Show me feature adoption rates for users who signed up last month"

✓ Connects to your analytics/database
✓ Segments by signup cohort
✓ Calculates adoption metrics
✓ Highlights trends

Natural Language Queries​

Ask product questions directly:

"What's the retention curve for users who completed onboarding?"
"Which features do power users engage with most?"
"How does mobile usage compare to desktop?"

Quick Experiment Analysis​

"Compare conversion rates between control and variant A
for experiment 'new-pricing-page'"

Key Benefits for Product Managers​

1. Real-Time Product Insights​

No more waiting for scheduled reports:

"What's happening with signups today compared to yesterday?"
"Show me the latest NPS scores by user segment"
"Are there any anomalies in error rates this week?"

2. Multi-Source Product View​

Combine data from your entire product stack:

data_sources:
  analytics:
    type: rest_api
    url: https://api.amplitude.com/2/events
    auth:
      type: api_key

  database:
    type: postgresql
    connection_env: PRODUCT_DB_URL

  support:
    type: rest_api
    url: https://api.zendesk.com/v2/tickets
    auth:
      type: bearer
      token_env: ZENDESK_TOKEN

3. Shareable Analyses​

Create reports for stakeholders:

"Create a weekly product metrics summary for the leadership team"

4. Feature Launch Monitoring​

Track launches in real-time:

# Feature launch monitoring
data_sources:
  events:
    type: postgresql
    query: |
      SELECT
        DATE(timestamp) as date,
        COUNT(DISTINCT user_id) as users,
        COUNT(*) as events
      FROM product_events
      WHERE event_name = 'new_feature_used'
      AND timestamp > '2024-01-15'
      GROUP BY 1

schedule:
  cron: "0 9 * * *"

output:
  type: slack
  channel: "#product-launches"

Common PM Workflows​

User Journey Analysis​

"Map the user journey from signup to first purchase"

Feature Usage​

"Rank features by weekly active users and show trends"

Cohort Retention​

"Show 30-day retention by signup month for the past 6 months"

Experiment Results​

"Calculate the lift and statistical significance for experiment XYZ"

Customer Feedback​

"Categorize support tickets by feature area and sentiment"

Example: Feature Prioritization​

You: "Help me prioritize features based on user feedback and usage data"

ShedBox Agent:
✓ Pulls feature usage from analytics
✓ Pulls feature requests from support tickets
✓ Joins on feature name
✓ Calculates impact score

Feature Priority Analysis:
1. Search improvements - High usage (10k/week), High requests (45 tickets)
2. Export to PDF - Low usage (500/week), Very high requests (120 tickets)
3. Dark mode - Medium usage (3k/week), Medium requests (30 tickets)

Recommendation: "Export to PDF" has high latent demand despite low current usage

Get Started​

Make faster product decisions with data.

Try ShedBox Agent →