SERVICES / DATA & ANALYTICS

Every dollar, accounted for.

Tracking, identity, attribution, activation, and reporting, engineered as one system. One version of the truth your whole company can act on.

$295M
REVENUE RECONCILED TO SPEND
81
CLIENT STACKS SERVED
TRUSTED BY 80+ COMPANIES
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OUR POINT OF VIEW

We go far beyond standard analytics by discovering deeper customer signals and behavioral patterns that unlock significantly higher business returns. Our advanced targeting frameworks feed platforms enriched, high-intent signals most competitors never surface - driving more precise acquisition, stronger retention, and greater overall profitability.

THE GAP

The data trust gap

Most growth teams are rich in dashboards and poor in numbers anyone trusts. We engineer the data layer so marketing, finance, and the platforms finally agree.

80%
Silos block AI ambitions

80% of organizations say data silos are the biggest barrier to achieving their automation and AI goals.

MuleSoft, Connectivity Benchmark Report 2025
26%
A quarter of data goes untrusted

Data and analytics leaders estimate 26% of their organization's data is untrustworthy.

Salesforce, State of Data and Analytics 2025
$12.9M
Bad data has a price

Poor data quality costs organizations an average of $12.9 million every year.

Gartner, Data Quality research
PROOF

Case Studies

Get one version of the truth your whole team can act on.

Book a strategy call →
CAPABILITIES

What's included.

01

Tracking & Identity Resolution

Trustworthy tracking feeding one customer profile your whole stack agrees on.

GA4, GTM, and server-side tracking that survives ITP and ad blockers, validated event by event with consent wired in. A CDP stitches accounts, people, and devices into one profile every tool reads.

02

Attribution & Marketing Mix

A spend-to-revenue picture that holds up in a finance review.

Multi-touch attribution where the data supports it, media mix modeling where it does not, and incrementality tests to settle the argument when the two disagree. You stop debating credit and start reallocating budget.

03

Audience Enrichment & Activation

Enriched profiles synced to the channels that can act on them.

Firmographic, technographic, intent, and behavioral signals layered onto every profile, powered by MadSight, our data activation platform. Enriched segments flow to Meta, Google, LinkedIn, and your CRM on a continuous schedule.

04

Warehouse, Modeling & Forecasting

Modeled data you own, forward-looking models, and dashboards that tie spend to revenue.

Modeled, tested, version-controlled tables in your own warehouse, with reverse ETL back to the tools your teams work in. On top run LTV, churn, and demand forecasts, and executive dashboards that reconcile spend to revenue automatically.

HOW WE WORK

The method.

01
Audit the Stack

We follow every tag, event, and table from first click to closed revenue. You get a line-by-line account of what is broken, ranked by dollars at stake.

02
Draft the Blueprint

A tracking plan, event taxonomy, and identity spec designed around your funnel. Everyone signs off on one spec before a single tag ships.

03
Instrument Clean

GA4, GTM, server-side collection, the CDP, and warehouse pipelines built to the blueprint. Every event checked in staging, confirmed in production, documented on launch.

04
Activate & Own

Enriched audiences flow into every activation channel, dashboards refresh in real time, and the whole system is documented inside your own stack.

WHY EGGKNITE

Core Differences

EGGKNITEIn-house buildPoint-tool vendors
Speed to liveA senior data team that has built 81 stacks, working from a proven blueprint.A hiring plan first: analytics engineer, tracking specialist, BI lead.Fast to sign, then months of implementation consultants.
ScopeTracking, identity, attribution, warehouse, activation, and dashboards as one connected system.Whatever the roadmap has capacity for this quarter.One slice each: a CDP here, an attribution tool there, glue undone.
Marketing fluencyBuilt by people who run paid media and lifecycle, so the data serves real decisions.Data engineers translate marketing needs secondhand.Generic schemas that fit every customer and none well.
Cost shapeA scoped engagement, then a system your team runs on open tooling.Multiple full-time salaries before the first dashboard ships.Per-seat and per-event pricing that grows faster than your data.
OwnershipPipelines in your cloud, models in your warehouse, credentials in your accounts.Owned in-house by definition.Your customer data lives inside the vendor's platform.

Make your data your unfair advantage.

Book a strategy call →
WHAT YOU GET

Deliverables that ship.

A documented tracking plan and event taxonomy, with every event named, owned, and checked in staging before it ships
Server-side collection that holds up against ad blockers, ITP, and consent mode, with PII filtered before it reaches any third party
One identity-resolved customer profile, deterministic-first, synced to your ad platforms, CRM, and lifecycle tools
An attribution and media mix stack reconciled to booked revenue and validated against holdouts
Modeled, version-controlled marketing data in your own warehouse, with reverse ETL pipelines you control
Revenue and demand forecasts with scenario planning, so budgets are set on modeled evidence instead of last year plus a guess
Self-updating executive and operator dashboards where every number is defined, sourced, and safe to act on
A FIT WHEN
  • You are scaling paid media beyond the reliability of last-click attribution and need clarity on what’s truly driving revenue.
  • Your marketing, finance, and platform-reported numbers consistently disagree, turning budget conversations into debates over data accuracy.
  • Privacy changes, consent requirements, and signal degradation have weakened your tracking and caused retargeting audiences to shrink.
  • You are preparing to invest in AI, automation, or advanced modeling and need trustworthy, unified data as the foundation before any system can deliver reliable results.
FAQ

Questions, answered.

The audit comes first and tells you exactly what is broken today, which is itself a number you can act on. Clean tracking and the event taxonomy ship next, so core reporting becomes trustworthy early in the engagement, and attribution, enrichment, and forecasting build on that foundation. Each layer is validated in staging before it goes live, so trust arrives in verified increments rather than as a promise at the end.

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