---
title: "Case study: how Novakid analyses call transcripts to coach sales reps"
description: "How Novakid put sales conversion diagnostics, call coaching, marketing performance and forecasting in the hands of country leads and sales ops, using Rig's context layer and MCP in Claude."
canonical: "https://rig.so/case-studies/novakid"
format: markdown
---

[All case studies](https://rig.so/case-studies)

Global · Series B · EdTechEdTech Platform

# How Novakid analyses call transcripts to coach sales reps

Novakid is a global EdTech platform delivering live, one-to-one English lessons to children in over 50 countries. Their BigQuery warehouse is the source of truth for sales, marketing and ops, but it was effectively read-only for the people closest to revenue. The CTO and CRO brought in Rig to flip that, letting sales managers and ops teams query the warehouse directly and build the data tooling they'd been asking for.

[Rig context layer](https://rig.so/context-layer)[Rig data apps](https://rig.so/connect)

5,000+

Tables in the governed context layer

10

Commercial users actively building on Rig MCP

2,500+

Rig MCP tool calls in the last 30 days

Rig MCP adoption

Active Rig MCP users by month

From onboarding

Rig MCP usage

Rig MCP tool calls by month

From onboarding

From a single technical user testing the connection to the commercial team running Rig MCP in Claude every day, in two months.

## A 5,000-table warehouse, commercial teams locked out.

Sales managers, country leads and revenue ops at Novakid were running a global, high-volume business on top of a BigQuery estate they couldn't query directly. Every operational question (which campaigns are converting best, how trial-to-purchase is trending by country, which reps to highlight as best practice) routed through a small data team.

The CRO wanted the people closest to revenue to query and build on the warehouse themselves, without compromising governance and without a queue.

## Why Rig

Rig built a managed context layer over Novakid's BigQuery warehouse, then handed sales, marketing and ops teams Rig MCP access inside Claude. Commercial users get to query, the data team gets to govern, and every call runs against the same certified context.

## How commercial teams use Rig

The shape of Rig MCP usage across the org, aggregated by team and goal. Every question runs against the same context, every answer is governed by per-user permissions.

Top intent category

Sales conversion diagnostics

Trial-to-purchase performance by country, year-on-year movement, regional conversion drivers. Asked weekly by country leads.

Used by sales leadership

Sales coaching & call analysis

Comparing rep call content to top managers worldwide, objection-handling patterns from transcripts, coaching opportunities surfaced from outcomes.

Used by growth marketing

Marketing campaign performance

Which campaigns convert to trial and to purchase by country, best send-time for offer mailings, spend re-allocated to the strongest performers.

Used by sales ops

Sales-ops daily monitoring

Workload by manager, plan vs actuals by region, retention metrics by cohort, call answer-rate by attempt number. Standing daily questions, now self-served.

Used by finance & RevOps

Forecasting & planning

Forward-looking forecasts of new-student purchases against the business plan, regional pipeline projections, secondary-sales upside.

## Want results like this?

[Book a demo](https://rig.so/book-demo)[See how Rig works](https://rig.so/walkthrough)

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