ShedBoxAI for SaaS
Build product analytics pipelines with ShedBoxAI. Track user behavior, predict churn, and generate insights with AI.
SaaS Use Cases
User Behavior Analysis
Track and analyze user actions:
data_sources:
events:
type: csv
path: "user_events.csv"
processing:
contextual_filtering:
events:
- field: "event_type"
condition: "in:signup,purchase,churn"
new_name: "key_events"
advanced_operations:
user_metrics:
source: "key_events"
group_by: "user_id"
aggregate:
event_count: "COUNT(*)"
first_event: "MIN(timestamp)"
last_event: "MAX(timestamp)"
sort: "-event_count"
output:
type: file
path: "user_behavior.json"
format: json
Churn Prediction
Use AI to identify at-risk customers:
data_sources:
users:
type: csv
path: "user_activity.csv"
ai_interface:
model:
type: rest
url: "https://api.anthropic.com/v1/messages"
method: POST
headers:
x-api-key: "${ANTHROPIC_API_KEY}"
Content-Type: "application/json"
options:
model: "claude-sonnet-4-20250514"
prompts:
churn_risk:
system: "You are a customer success analyst."
user_template: |
Analyze these users and identify churn risk:
{% for user in users %}
- {{ user.name }}: Last login {{ user.last_login }}, {{ user.feature_usage }} features used, {{ user.support_tickets }} tickets
{% endfor %}
Categorize each user's churn risk (low/medium/high) and explain why.
output:
type: file
path: "churn_risk_report.md"
format: json
MRR Dashboard Data
Calculate key SaaS metrics:
data_sources:
subscriptions:
type: rest
url: "https://api.stripe.com/v1/subscriptions"
headers:
Authorization: "Bearer ${STRIPE_SECRET_KEY}"
response_path: "data"
processing:
contextual_filtering:
subscriptions:
- field: "status"
condition: "active"
new_name: "active_subs"
advanced_operations:
mrr_by_plan:
source: "active_subs"
group_by: "plan.id"
aggregate:
subscriber_count: "COUNT(*)"
mrr: "SUM(plan.amount)"
sort: "-mrr"
output:
type: file
path: "mrr_metrics.json"
format: json
Why SaaS Teams Choose ShedBoxAI
| Challenge | Solution |
|---|---|
| Scattered analytics | Unified pipelines |
| Manual reporting | Automated metrics |
| No AI insights | Built-in LLM |
| Engineering time | YAML configuration |
Get Started
pip install shedboxai
shedboxai run saas_pipeline.yaml