Analytics and reporting
Effective analytics work doesn’t begin with a dashboard. It begins with the decisions the business needs to make, the metrics required to support those decisions, and the instrumentation and architecture needed to make those metrics trustworthy. When that chain is sound, arguments about whose number is right disappear, and meetings get shorter.
What’s usually broken
- The same KPI, calculated differently. Marketing’s conversion rate and finance’s conversion rate meet in a board deck and disagree.
- Reporting still runs on spreadsheets. Someone exports, pastes, and emails every Monday, and the process breaks every time they take a vacation.
- Dashboards need an analyst attached. The tools exist, but every question still becomes a ticket.
- Instrumentation drifted. Events fire twice, or stopped firing in March, and nobody noticed until the trend line did something impossible.
- The last mile is missing. Insights accumulate in dashboards while the operational systems that could act on them never hear about it.
What I do
- KPI standardization: agree the 10-20 executive-visible KPIs, define each one once, and rebuild the top executive dashboards on those definitions.
- Dashboard and BI architecture: Looker, Tableau, and Power BI on a governed semantic layer, designed around audience and action rather than data availability.
- Instrumentation: end-to-end event collection and tag management, with release-gate QA so tracking survives deploys. Adobe Analytics, GA4, and the surrounding stack.
- Attribution and measurement: cross-channel attribution, campaign measurement, and acquisition-cost work of the kind marketing and finance both sign off on.
- Forecasting models: LTV by channel, churn risk by cohort, platform-mix return, built to inform decisions someone actually has to make.
- Activation: reverse ETL, so the segments and scores in the warehouse reach the ad platforms and CRM where they earn money.
How it works
Analytics engagements start from the decision inventory: what the business needs to decide, at what cadence, with what numbers. Instrumentation and dashboards get rebuilt against that inventory. It’s disciplined work with visible results early, which is why KPI standardization is a top-3 quick win in most estates I’ve reviewed.
Proof
At Goldman I rebuilt the Marcus measurement stack on Adobe Analytics, GA, and GTM, authored the solution design reference, and delivered a cross-line-of-business attribution model adopted by both marketing and finance. At Rdio my team’s measurement and forecasting work moved install-to-paid conversion up 10-20% and blended acquisition cost down 10-20%, and the subscriber analytics carried into Pandora’s acquisition diligence. At Architizer, rebuilt analytics across 3 business lines, supporting a marketplace that grew deal flow 425% year over year.
Start a conversation
If your Monday metrics meeting starts with reconciling numbers, start here.