Frequently Asked Questions
What it costs, how fast we start, who does the work, and what we need from you. If your question isn't here, ask my AI.
Pricing and commitment
How much does Datalyze cost?
Three tiers: a one-time audit from $1,000; infra setup at $1,500 to $3,000 per project; and embedded (ongoing) at $2,000 to $5,000 per month. Most teams start with the audit and scale from there.
Do I have to commit to a retainer?
No. The audit and infra setup tiers are both one-time projects. Some clients start with an audit and scale into a retainer; others take a project and run it themselves afterwards.
Why not just hire a full-time analyst?
A full-time analyst costs $100,000 to $150,000 loaded, takes 3 to 6 months to ramp, and brings experience from one or two companies. Datalyze brings senior operators who've seen the patterns across 150+ startups, starts within a day, and costs a fraction of a full-time salary. When you're ready for that hire, they'll inherit a clean, documented foundation instead of the mess they'd normally spend their first six months untangling.
Timing and process
How fast can you actually start?
Within a day of kickoff. We don't need a month to learn your stack or a week of onboarding meetings. Share access and we're auditing your data by tomorrow.
How long until we see results?
Most teams see their first actionable insights within 2 to 3 weeks of kickoff. The audit itself takes 1 to 2 weeks.
What does a typical engagement look like?
Week one: full data audit. We identify what's broken, what's missing, and what's being tracked but never used. From there, we prioritize, fix critical tracking issues, unify data sources, build the reporting your team actually needs, and start identifying growth levers. Weekly syncs keep everything aligned.
What happens when an engagement ends?
Everything we built - tracking plans, models, dashboards, documentation - is in your tools and owned by your team.
The team
Who will I work with?
You'll work with a small, focused team based on your needs. This may include a product analyst, analytics engineer, growth strategist, and developer. No unnecessary layers - you talk directly to the people doing the work.
What do you need from our team?
We may need light developer support to implement tracking, add events, or help with data foundations for modeling.
Tools and setup
We already have analytics tools. Why do we need you?
The tool is rarely the problem. The implementation is. Whether you're running Mixpanel, Amplitude, PostHog, BigQuery, Snowflake, or some combination of all of them, most setups we audit have 20 to 40% of events, models, or pipelines that are misconfigured, missing, or quietly broken. Your tools work fine. The data flowing through them doesn't. We fix the foundation across your whole stack, then make it actually useful for decisions.
What if we already have some analytics setup?
Most companies do. The question is whether anyone trusts it. We audit what you have, fix what's broken, fill what's missing, and build on what's working. We don't rip and replace, we make your current investment reliable.
Which tools do you work with?
Whatever you're already running: Mixpanel (Certified Partner), PostHog (Implementation Specialist), Amplitude, Heap, GA4, Google Tag Manager, Google Ads, Meta Ads, HubSpot, Stripe, Chargebee, Recurly, RevenueCat, BigQuery, Snowflake, Postgres, Looker Studio, Metabase, Databricks, Segment, dbt, Fivetran, Hightouch and Airbyte.
Results
How do you measure the 14% revenue lift?
We measure the before-and-after revenue impact of the specific changes made during each engagement: conversion improvements from tracking fixes, retention gains from product changes, revenue from experiments we design and run. The 14% is a weighted average across 150+ engagements, not a cherry-picked best case.
What if the work does not move the numbers?
When an experiment doesn't move the needle, we tell you and run a better one. We measure revenue impact on every change we ship.