Analytics spend forecaster for growing teams

The moment this becomes real is when a team's analytics bill arrives 40% higher than last month and nobody can explain why — not the finance lead, not the data analyst, not the tool admin. They dig through usage logs manually, argue about which dashboard triggered the overage, and still can't predict next month with confidence.

This gap persists because analytics vendors have every structural incentive to keep pricing opaque. Metered billing tied to data volume, active users, and feature tiers creates a ceiling the vendor benefits from you hitting. The vendor's dashboard shows you what you consumed — never what you're on track to consume.

What's missing isn't a general cloud cost tool (those cover compute and storage but treat analytics seats and SPICE-style query capacity as line items they can't interpret). What's missing is something that understands the specific billing mechanics of analytics tools — per-session charges, capacity reservation blocks, reader vs. author seat distinctions — and translates actual usage patterns into a forecast a finance lead can act on before the invoice arrives.

Users complain that 'determining pricing for SPICE is tricky to plan ahead for' and that costs have 'doubled in the last year' without clear explanation. Without a way to model growth scenarios — what happens to the bill if we add 20 users, or if query volume doubles during a campaign — teams either overbuy capacity and waste money or underbuy and get surprised.

This is a recurring business problem because the underlying billing models don't simplify over time — analytics vendors add tiers and features, making forecasting harder every year. The need recurs every budget cycle. Finance teams that have been burned once will pay a fixed monthly fee to avoid being burned again — especially when the alternative is hiring someone to build and maintain a spreadsheet model that breaks every time the vendor changes pricing.

What to build

Connect to an analytics account's usage API (starting with QuickSight), parse the actual billing dimensions — SPICE capacity, reader sessions, author seats — and output a 90-day cost forecast with scenario sliders for user growth and data volume, delivered as a weekly email digest and a simple web dashboard.

Where to start

Target QuickSight specifically first, because SPICE capacity confusion is the most-cited specific pricing complaint and has no dedicated forecasting tool — every QuickSight admin currently guesses, making the value proposition immediate and obvious without needing to explain the broader problem.

The hard part

Analytics vendors expose usage data through APIs at varying levels of granularity, and some billing dimensions — like SPICE capacity consumption per workload — are not exposed programmatically at all, forcing you to rely on scraping billing exports or asking users to upload CSV reports manually, which creates friction that kills activation.

How it makes money

Flat monthly subscription priced per analytics account connected — around $49–$149/month depending on account size — with a 14-day free trial that requires no credit card but asks users to upload a billing CSV to generate their first forecast.