Measurement that changes decisions, not just dashboards.
GA4, server-side tracking, self-attribution, warehouse (BigQuery / Snowflake / ClickHouse), and dashboards designed for the person who has to sign the ad budget.
Why this matters now.
Most Indian mid-market brands have a GA4 install, a dashboard someone made in Data Studio in 2022, and no idea if any of the numbers reconcile. Meta reports one number, Google reports another, the CRM reports a third, the finance team runs a fourth in Excel, and the CEO trusts none of them. This is the standard state, and it is the wrong state.
We fix it in three moves. First, a real tracking spine: GA4 rebuild if needed, server-side event architecture (GTM SS or a custom Cloudflare Worker), offline conversion imports, and self-attribution survey on your thank-you page. Second, a warehouse (BigQuery or Snowflake — pick one, we'll help) where every source lands and gets reconciled. Third, an executive dashboard that reads like a one-page memo, not a 40-panel Data Studio wall.
For D2C brands, this typically pays back inside quarter one — we regularly find 8–15% of revenue that platforms had been mis-attributing, which means real ad spend gets reallocated. For B2B and SaaS, the payoff is longer but larger: real closed-won attribution instead of the perennial 'sales says one thing, marketing says another' loop.
We are honest about the trade-offs. Server-side tracking costs real money and adds real complexity. If your business is under ₹1cr/month in revenue, you probably don't need it yet — you need better product-market fit. We will tell you if we think you're over-buying data infrastructure.
Deliverables, spelled out.
Server-side tracking spine
Google Tag Manager Server-Side or a Cloudflare Worker collecting events. Sent to Meta CAPI, Google Ads, GA4, and your warehouse in one place.
Self-attribution survey
Post-purchase / thank-you page survey. Reconciled against platform-reported data monthly. The one attribution signal that platforms can't game.
Data warehouse setup
BigQuery / Snowflake / ClickHouse. Fivetran or Airbyte for ingestion. dbt for transformation. Modelled tables your BI tool can query.
Executive dashboard
One-page dashboard for the founder / CFO / board. Not 40 charts. 6 numbers that matter. Refresh cadence set to weekly.
Operator dashboard
Deeper dashboard for the marketing operator. Channel-level, campaign-level, creative-level. Still designed, not a raw pivot table.
Attribution model
Multi-touch attribution — data-driven where you have volume, position-based where you don't. Reconciled against self-report survey monthly.
The whole surface area.
Every sub-capability lives on the map. Click one and we'll build a working prototype in a week — we don't handwave scope.
4 deep specialisations. Each its own page.
Click any tile to open a full engagement brief — deliverables, process, KPIs, and honest FAQs.
From input to outcome.
Foundational engagements: 6–10 weeks. Ongoing warehousing: retainer.
6-step engagement, no filler.
- 01Measurement auditTwo-week audit of your current tracking, warehouse, and attribution setup. Delivered as a written memo with prioritised fix list.
- 02Tracking spine buildWeeks 3–5: GA4 rebuild if needed, GTM Server-Side or Worker deployment, Meta CAPI, Google offline conversion imports, self-attribution survey deployed.
- 03Warehouse setupWeeks 4–8: BigQuery / Snowflake, Fivetran/Airbyte ingestion of ad platforms, CRM, order data. dbt models for staging and marts.
- 04Attribution modelWeeks 6–8: multi-touch attribution model calibrated against self-report survey. Confidence intervals published, not hidden.
- 05Dashboard layerWeeks 8–10: exec dashboard (6 numbers), operator dashboards (channel, campaign, creative), weekly ops memo template.
- 06Ongoing reconciliationMonthly: platform-reported vs. self-report vs. warehouse reconciliation. Discrepancies investigated, models re-calibrated.
The numbers we ship.
What we won't report.
- ✕We won't upsell warehouses to brands doing under ₹1cr/month.
- ✕We won't call platform-reported ROAS 'attribution'.
- ✕We won't build a 40-panel dashboard nobody reads.
- ✕We won't skip the self-attribution survey — it's the only ground-truth signal.
Questions smart clients ask.
Only if you're doing enough revenue that reconciling platform data actually pays back. For most D2C brands that's ₹1cr+/month in revenue, and for most B2B/SaaS it's ₹40L+/month ARR. Below that, a well-configured GA4 + spreadsheet is fine.
BigQuery for most cases (Google Cloud consolidation, generous free tier). Snowflake if you have a data team already fluent in it. ClickHouse for event-heavy workloads at scale. We'll advise honestly per project.
No — we build the foundation and hand over cleanly. We're not trying to be your permanent data function. If you already have a data team, we work alongside them and often accelerate their roadmap by two quarters.
GDPR-compliant consent management (Cookiebot / OneTrust integration), PII redaction at ingestion, DPA agreements with every vendor. Compliance is built in, not bolted on.
Foundation build: ₹12–35L one-off. Ongoing warehousing retainer: ₹2–6L/month depending on ingestion volume and dbt model complexity.
Kick off with a 30-minute strategy call.
We diagnose live, on the call. No decks. If we're the wrong fit we'll say so — and point you to who isn't.