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ARRAYMATIC

ArrayMatic Technologies

B-23, B Block, Sector 63, Noida, Uttar Pradesh 201301

[email protected]

+91-9555505981

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HomeIndustriesStartupsData-Driven Growth & Analytics

Startups

Data-Driven Growth & Analytics

Instrumentation, warehouse, and dashboard stack that gives founders a single source of truth for acquisition, activation, retention, and revenue — built in two to three weeks.

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Industry overview

Data-driven growth analytics is the practice of instrumenting every product interaction, centralising event data in a queryable warehouse, and building dashboards that connect user behaviour directly to business outcomes.

At a glance

  • Structured event taxonomy design covering all product surfaces
  • Segment or custom SDK instrumentation for frontend and backend
  • Data warehouse setup in BigQuery or Redshift with raw and transformed layers

Most early-stage products have fragmented analytics: some events in Mixpanel, revenue in Stripe, support tickets in Intercom, and no way to connect them. Founders make decisions from whichever dashboard they happen to open. We build a unified analytics stack: a single event schema, a warehouse that ingests from all sources, and dashboards that answer the questions that actually drive product decisions — activation rate by acquisition channel, feature usage by cohort, revenue retention by plan.

What we instrument and build

We design a structured event taxonomy, instrument your frontend and backend using Segment or a custom event SDK, and pipe everything into BigQuery or Redshift. On top of the warehouse we build dbt transformation models and a Metabase or Superset dashboard layer with the five to eight views your team checks weekly. We also wire funnel alerts: when activation drops below threshold, a Slack message fires before anyone notices manually.

Key capabilities

What we deliver

Engagements are scoped to your business context — these are the core capabilities we bring to startups clients.

Structured event taxonomy design covering all product surfaces

Segment or custom SDK instrumentation for frontend and backend

Data warehouse setup in BigQuery or Redshift with raw and transformed layers

dbt transformation models for activation, retention, and revenue metrics

Metabase or Superset dashboards covering acquisition-to-revenue funnel

Automated threshold alerts for key metric drops delivered to Slack

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