You are in Digital Analytics - Marketing Attribution
Identify Campaigns That Create Net-New Revenue
Isolate what drives new revenue and cut what only claims credit for existing demand.
Are Your Campaign Metrics Showing Activity Not Incremental Growth?
Every campaign reports performance clicks, conversions, revenue. Dashboards attribute success across channels. There is no structured method isolating incremental lift from organic demand.
Attribution Misses True Lift
What Happens: Standard models assign revenue credit but do not isolate whether the campaign generated new demand.
Real Scenario: A paid search campaign shows strong conversions. No test is run to determine whether those customers would have converted organically.
Organic-Paid Overlap Ignored
What Happens: Campaigns target audiences already in-market. There is no structured holdout or lift measurement to detect overlap.
Real Scenario: Display campaigns increase attributed conversions. Organic traffic declines proportionally. The budget shifts credit rather than generating net-new revenue.
Lift-Blind Budget Calls
What Happens: Spend decisions are based on attributed performance, not incremental contribution.
Real Scenario: High-performing retargeting campaigns receive increased budgets. Net revenue growth remains flat. CFO questions the marketing ROI narrative.
How We Fix It
We isolate incremental revenue impact before budget decisions are made.
What We Build
An incrementality measurement framework layered on top of your attribution model.
How We Build It
- Establish holdout and control groups to measure true campaign impact and incrementality
- Implement geo and audience-based lift testing to evaluate performance across segments
- Isolate baseline organic conversion rates to separate paid impact from natural demand
What We Build
A cross-channel impact model that identifies overlap between paid and organic traffic.
How We Build It
- Analyze conversion overlap across traffic sources to uncover hidden attribution conflicts
- Identify branded search cannibalization to reduce inefficient and redundant ad spend
- Measure paid versus organic substitution effects to understand true incremental impact
What We Build
A budget optimization model tied to proven incremental performance.
How We Build It
- Rank campaigns by net incremental revenue to prioritize high-impact marketing investments
- Adjust spend based on lift rather than attribution credit to improve budget efficiency
- Remove low-impact retargeting expansion to reduce waste and improve campaign ROI
What You Get
Verified growth. Disciplined spending. Defensible ROI.
Actual Revenue Contribution
True revenue contribution separated from attribution credit inflation.
Incrementality tests prove paid search generates new customers instead of attribution credit for organic.
Channel Impact Made Visible
Cannibalization and substitution effects visible across channel mix.
Display lift measured against organic baseline instead of attributed conversions hiding organic decline.
Spend Shifts to Net Revenue
Low-lift campaigns deprioritized based on incremental contribution.
Retargeting budgets rightsized on incremental lift instead of increased based on high attribution.
Digital Analytics Products for Real-Time Decisions
Enterprise-ready analytics products that standardize measurement, reduce noise, and keep decisions aligned in real time.
Continuously analyze data and surface insights automatically
Get early alerts when performance drops, translate data into clear summaries for non-analysts, and uncover patterns and anomalies manual reporting often misses.
Book a Demo →From Reporting to Control. In Four Moves.
Most analytics stop at visibility. We build the system that drives action.
Start with a Bootcamp
Bootcamp
(5 Days)Fix one decision blocker fast
We start with one live problem: attribution disputes, delayed performance signals, fragmented journeys, or profit blind spots.
In 5 days, we rebuild that loop end-to-end across the systems involved, so the number becomes usable, not debatable.
You see the fix working on your data, with clear before/after impact.
Launchpad
(60 Days)Make the fix production-grade and run it daily
Once it works, we take it live with real traffic, real refresh schedules, and real ownership.
Monitoring and guardrails are added so performance doesn’t drift silently and definitions don’t get reinterpreted team by team.
By day 60, your teams can operate the system without depending on manual reconciliation cycles.
Rollout
Expand the same control loop across more decisions
With the foundation in place, we scale the pattern to the next bottleneck. Budget optimization, cohort retention, channel ROI, margin leakage, or journey drop-offs.
Each rollout moves faster because you’re not rebuilding identity, metrics, and signal flows from scratch.
Over time, analytics stops being a project and starts behaving like an operating capability.
Digital OS
Run analytics as an always-on decision layer
At this stage, analytics becomes the control layer that keeps the business aligned in real time.
Signals stay current. Attribution stays consistent. Journeys stay connected. Profit stays visible.
Teams don’t wait for monthly reporting to act. They adjust execution continuously, with confidence.
Case Studies From Real Enterprise Environments.
What broke, how we fixed it, and what the numbers showed.
View Case Study
Customer journeys optimized using unified digital analytics
Web, mobile, and portal touchpoints were unified under a single analytics framework. Adobe Analytics was re-implemented to capture meaningful events and ensure accurate journey measurement.
Decision-Ready Analytics Starts Here
Attribution disputes. Stale performance. Split journeys. Pick one. We make it reliable enough to run daily.
Built with Enterprise-Grade Partners
20 years building on Adobe, Salesforce, IBM, HCL, SAS, and Microsoft. We know how to make them work as one system.
Customer Endorsements
"Congrats and thanks to entire Xerago team. The policy persistency model is live now, and development was done with clinical precision. It has an accuracy of 95%."
— Senior Vice-President, A Large Private Insurance Company, India
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