Core Concepts

Understanding the key concepts in Aim will help you make the most of the platform.

Systems & Integrations

What is a System?

A system is any external platform or tool that Aim can connect to. Examples include:

Analytics platforms (Google Analytics, Amplitude)
CRM systems (Salesforce, HubSpot)
Data warehouses (Snowflake, BigQuery)
Payment processors (Stripe, PayPal)

What is an Integration?

An integration is the configured connection between Aim and a system. When you set up an integration:

You provide authentication credentials
Aim establishes a secure connection
Data automatically syncs based on your chosen cadence
Metrics become available from that system

Integration Types

OAuth Integrations

User grants permission through OAuth flow
Automatically refreshed tokens
Example: Slack, GitHub

API Key Integrations

User provides API key or secret
Keys stored encrypted
Example: Stripe, Mailchimp

Service Account Integrations

Uses service account credentials (JSON key files)
Requires admin setup
Example: Google Analytics, BigQuery

Database Connections

Direct connection to databases
Requires connection string and credentials
Example: PostgreSQL, MySQL, Snowflake

Metrics

What is a Metric?

A metric is a measurable value that tracks performance over time. Metrics are the foundation of Aim.

Metric Types

Direct Metrics

Pull a single value from a data source
Example: “Total Revenue from Stripe”
Updated based on sync cadence

Calculated Metrics

Combine multiple metrics with formulas
Example: “Conversion Rate = (Conversions / Visitors) × 100”
Recalculated when source metrics update

Custom Query Metrics

Execute custom SQL or API queries
Advanced use cases requiring specific logic
Example: Complex aggregations across multiple tables

Metric Properties

Every metric has:

Name - Clear, descriptive identifier
Description - What it measures and why
Unit - Type of measurement (%, $, count, etc.)
Owner - Person responsible for the metric
Source - Which integration provides the data
Refresh Cadence - How often it updates
Historical Data - Past values for trending

Data Flow

How Data Moves Through Aim

External System → Integration → Aim Data Store → Metrics → Dashboards

Sync: Aim connects to your system via integration
Extract: Data is pulled based on refresh cadence
Transform: Data is normalized and stored
Calculate: Metrics are computed from raw data
Display: Metrics appear in dashboards and reports

Refresh Cadences

Real-time

Data updates within seconds
Available for: Webhooks, streaming APIs
Use case: Trading dashboards, live monitoring

Hourly

Data updates every hour
Available for: Most APIs
Use case: Marketing campaigns, sales activity

Daily

Data updates once per day (usually at midnight UTC)
Available for: Most integrations
Use case: Business metrics, weekly reports

Weekly

Data updates once per week
Available for: All integrations
Use case: High-level trends, executive dashboards

Monthly

Data updates once per month
Available for: All integrations
Use case: Financial reporting, board metrics

OKRs (Objectives and Key Results)

What are OKRs?

Objectives are qualitative goals you want to achieve:

“Become the market leader in our category”
“Improve customer satisfaction”
“Scale engineering productivity”

Key Results are measurable outcomes that indicate progress:

“Increase market share to 25%”
“Achieve NPS score of 50+”
“Deploy 20 features per quarter”

OKRs in Aim

Create an Objective - Define what you want to achieve
Add Key Results - Link metrics as key results
Set Targets - Define success thresholds
Track Progress - Monitor in real-time
Align Teams - Cascade OKRs across organization

OKR Cadences

Annual OKRs - Company-wide strategic goals
Quarterly OKRs - Department and team goals
Monthly OKRs - Individual and project goals

Dashboards

What is a Dashboard?

A dashboard is a customizable view that displays metrics, charts, and insights in one place.

Metric Card

Display single metric value
Show change vs. previous period
Color-coded status (on track, at risk, off track)

Line Chart

Show trends over time
Compare multiple metrics
Identify patterns and seasonality

Bar Chart

Compare metrics across categories
Show rankings and distributions
Highlight top/bottom performers

Table

Display detailed data
Sort and filter values
Export to CSV

Text Widget

Add notes and context
Embed links and documentation
Explain metric definitions

Dashboard Best Practices

Focus on what matters - Limit to 6-8 key metrics per dashboard
Tell a story - Arrange widgets in logical flow
Add context - Use text widgets to explain insights
Set time ranges - Choose appropriate windows (last 7 days, 90 days, etc.)
Share widely - Make dashboards accessible to stakeholders

Teams & Permissions

Organization Structure

Organization
├── Teams (Sales, Marketing, Engineering)
│   ├── Members
│   └── Metrics
└── Projects (Q1 2024, Product Launch)
    ├── OKRs
    └── Dashboards

Roles

Admin

Full access to all features
Manage integrations and billing
Add/remove users
Configure organization settings

Member

Create metrics and dashboards
View all team data
Edit assigned metrics
Cannot manage integrations or billing

Viewer

Read-only access
View dashboards and metrics
Cannot create or edit content
Cannot access raw data

Data Governance

Data Lineage

Lineage shows where data comes from:

Source system
Integration configuration
Transformation steps
Metrics using the data

View lineage by clicking any metric’s info icon.

Trust Scores

Aim automatically calculates trust scores for metrics based on:

Data freshness (when was it last updated?)
Data completeness (are there gaps?)
Data consistency (does it match expected patterns?)
Source reliability (is the integration healthy?)

Trust scores range from 0-100:

90-100: Highly reliable
70-89: Generally reliable
50-69: Use with caution
0-49: Needs investigation

AI Intelligence Hub

Natural Language Queries

Ask questions about your data in plain English:

“What’s our revenue growth this quarter?”
“Which marketing channels have the best ROI?”
“Show me sales pipeline by region”

The AI translates your question into a query, executes it, and returns results with visualizations.

Insights & Recommendations

The AI proactively identifies:

Anomalies - Unexpected changes in metrics
Trends - Emerging patterns
Correlations - Related metric movements
Opportunities - Areas for improvement

How It Works

AI analyzes all your metrics continuously
Compares current values to historical patterns
Identifies significant changes
Generates explanations and recommendations
Notifies you via dashboard, email, or Slack

Next Steps

Now that you understand the core concepts:

Questions?

Check the FAQ
View troubleshooting guides
Contact support

Quick Start Overview