Analytics

Measure business impact and performance of your AI applications with KPIs and OKRs that matter to stakeholders.

Overview

Analytics provides a framework for measuring, analyzing, and reporting on the business impact of your AI applications. It enables you to:

Track key performance indicators (KPIs) for AI-driven processes
Measure return on investment (ROI) of AI initiatives
Compare performance across A/B tests and experiments
Align technical metrics with business objectives (OKRs)

Features

Business Metrics: Track KPIs that matter to stakeholders
ROI Analysis: Calculate financial impact of AI investments
Experiment Tracking: Compare performance across A/B tests
OKR Alignment: Connect AI performance to business objectives
Custom Dashboards: Create reports for different stakeholders

Usage


import { trackMetric, defineExperiment } from 'analytics.do'
 
// Define an A/B test experiment
const productRecommendationTest = defineExperiment({
  name: 'product_recommendation_algorithm',
  description: 'Test different recommendation algorithms',
  variants: [
    { id: 'control', description: 'Current algorithm' },
    { id: 'collaborative', description: 'Collaborative filtering' },
    { id: 'content_based', description: 'Content-based filtering' },
  ],
  metrics: {
    primary: 'conversion_rate',
    secondary: ['revenue_per_user', 'click_through_rate'],
  },
})
 
// Track metrics for business KPIs
await trackMetric({
  name: 'conversion',
  value: 1,
  metadata: {
    userId,
    productId,
    revenue,
    experimentId: 'product_recommendation_algorithm',
    variant: 'collaborative',
  },
})
 
// Update KPI dashboard aligned with business OKRs
await analytics.updateKpiDashboard({
  metric: 'revenue_from_recommendations',
  value: revenue,
  dimensions: {
    experiment: 'product_recommendation_algorithm',
    variant: 'collaborative',
  },
})