TG3 47 SaaS brands scaled and $84M+ in client pipeline generated. See the proof → Free: 14 SaaS calculators, no signup. CAC, LTV, churn, Rule of 40. Open the tools → We rebuild attribution at the warehouse so every channel gets honest credit. See how →
TG3 SaaS/Services/Analytics and attribution

The SaaS marketing analytics agency for warehouse-based attribution.

Service · 07 of 07 · Foundation lever
Setup timeline
4 to 6 weeks
Dashboards delivered
6 to 12
Source of truth
Single
CFO sign-off
Required
What this is

A SaaS marketing analytics agency for B2B SaaS past $3M ARR where platform attribution has started lying. We rebuild it in the warehouse. HubSpot and Salesforce keep their reporting. The warehouse becomes the source of truth. Multi-touch attribution that the CFO will defend. Dashboards your team will actually open. No vanity metrics. No platform-attributed ROAS that overcounts by 3x.

01 · Setup timeline
4 to 6 wk

From kickoff to first live dashboard. Includes warehouse model, identity resolution and KPI definitions.

02 · Dashboards delivered
6 to 12

Per engagement. Marketing scorecard, channel deep-dives, cohort retention, attribution model, sales-pipeline view, more on request.

03 · Source of truth
1

One URL. One owner. One refresh schedule. The dashboard the board sees is the one operators use.

What's inside the engagement

Six SaaS marketing analytics programs. Built for the warehouse.

The retainer isn't one thing. It's six programs under one team, sequenced by what your stage needs. The audit picks the sequence. Most engagements use four of the six in the first 90 days.

SaaS marketing analytics agency programs · time to impact · suits TG3 SaaS internal · 47 engagements
Program Time to impact What it ships Suits SaaS that
Warehouse attribution Weeks 4 to 12 Stitch every touch to deals via BigQuery or Snowflake. Multi-touch model. Pipeline-attributed metrics. SaaS past $3M ARR. Where platform attribution starts undercounting real drivers by 2x to 4x.
Dashboards & reporting Weeks 4 to 8 Looker, Metabase, Hex or Mode. Built around the eight metrics that matter. Reviewed weekly. Any SaaS where the marketing team and CFO disagree about what worked last quarter.
CRM hygiene & audit Weeks 2 to 6 HubSpot or Salesforce cleanup. Object structures, custom fields, deduplication. Foundation work. SaaS where reporting questions take days to answer. Usually because the CRM is a mess.
Event tracking Weeks 4 to 8 GA4 events, server-side tracking, Segment, Rudderstack. Cookie-resilient, CCPA-compliant. Any SaaS losing data to platform tracking changes. Iotvitable post-iOS 17.
Marketing ops automation Weeks 6 to 10 Lead scoring, routing, nurture orchestration in HubSpot or Marketo. Sales-aligned. SaaS where leads take more than 4 business hours to reach the right rep. Almost everyone.
Forecasting & planning Quarterly Pipeline forecast models, ARR projection, retention modelling. Used in board reporting. SaaS past $10M ARR. Where the board needs marketing to defend forward projections.
Most engagements start with 3 of these 6. The audit picks which three →
Fit

When SaaS marketing analytics fits. Two honest columns.

Analytics is the foundation underneath every other service. When it's broken, the rest of marketing runs blind.

Right fit

You should run SaaS analytics with us if

  • You're past $1M ARR and your numbers don't reconcile across teams.
  • You have a CRM with stage data and at least one ad platform.
  • You have a warehouse or you're ready to provision one this month.
  • Your CFO has stopped trusting marketing's attribution claims.
  • You'll commit to a single owner of the dashboard inside your team.
Wrong fit

You shouldn't, if

  • You want a Looker dashboard built in two weeks. Real attribution takes the data layer first.
  • You don't have a warehouse and won't pay for one. The math doesn't carry without it.
  • Your CRM stage data is fictional. Fix that before we build on top of it.
  • You expect one model that explains every deal. Multi-touch attribution is an approximation. We say so.
  • Your engineering team won't grant warehouse access.
Methodology

Six named steps. Data first. Dashboard last.

Most analytics engagements ship the dashboard first and discover the data is wrong. We don't.

01

Source audit

Week 1

Every source mapped. GA4, HubSpot or Salesforce, Stripe, ad platforms, product analytics, support tool, NPS. Each one rated for reliability and completeness.

02

Warehouse model

Weeks 2 to 3

dbt models in BigQuery or Snowflake. Staging, intermediate, marts. The data your dashboards read is built once and audited. Not glued together at the visual layer.

03

Identity resolution

Weeks 3 to 4

Person → company → account graph. Cross-platform stitching where possible. We name the gaps where stitching is impossible. Honest dashboards beat heroic dashboards.

04

KPI definition

Week 4

Eight numbers signed in writing. ARR, pipeline, CAC, activation, NDR, organic sessions, demos booked, burn vs plan. Definitions documented. Anyone who reads them gets the same number.

05

Dashboard build

Weeks 4 to 6

Looker or Hex. Six core dashboards: scorecard, channel deep-dive, cohort retention, attribution, sales-pipeline, burn. Refreshed every six hours from the warehouse.

06

CFO sign-off + handoff

Week 6 onward

Walk-through with your CFO and CMO. Sign-off in writing on the eight numbers. Quarterly audit cadence set. We hand over the dbt repo and the warehouse credentials. You own everything.

Tools and stack

What we use. And what we don't.

Open warehouse stack. We don't resell or take affiliate fees.

Warehouse
BigQuery · Snowflake
Single source of truth. Pick depends on your existing cloud. Both are first-class for us.
Transformation
dbt
All transformations in dbt. Version-controlled. Documented. Auditable by your data team after handoff.
Pipelines
Fivetran · Airbyte
Source ingestion. Fivetran on enterprise stacks. Airbyte where budget is tighter.
Reverse ETL
Hightouch · Census
Warehouse back to operational tools. CRM enrichment. Audience syncs. Ad platform conversions API.
BI
Looker · Hex
Dashboards and exploratory views. Looker for ops cadence. Hex for ad-hoc analyses.
Event tracking
Segment · Rudderstack
Behavioural event pipeline. Single tracking plan. Documented schema.
Product analytics
Amplitude · Mixpanel
Product-side analytics layered on the same event stream. Cohort retention reports.
Project
Notion + Linear · Git
KPI definitions in Notion. Engineering work in Linear. dbt code in your Git.
KPIs we report monthly

How we measure a SaaS marketing analytics engagement. Eight numbers.

Most SaaS marketing analytics agency dashboards report 40+ metrics and obscure the ones that matter. We report eight. The CFO can read them in two minutes.

01
Pipeline attribution accuracy
Cross-checked against closed-won deals. Above 90% accuracy means the model is sound.
02
Reporting freshness
Hours from data event to dashboard update. Below 4 hours is healthy.
03
Data quality score
Composite of fill rate, deduplication and timestamp accuracy. Above 95% is the target.
04
CRM hygiene
Percent of records with required fields populated. Above 92% is the threshold.
05
Cross-channel attribution
Multi-touch model with fractional credit. Single channel never exceeds 60% of credit.
06
Forecast accuracy
Quarterly. Marketing-sourced pipeline forecast vs actual. Above 85% accuracy.
07
Time to insight
Hours from question to answer. Above 4 hours means the dashboard is wrong.
08
CFO sign-off rate
Quarterly. Percent of marketing numbers the CFO defends in board prep. Should be 100%.

No vanity metrics. No platform-attributed ROAS that overcounts. No "we hit 4 million impressions" if zero closed. Eight numbers your team can defend in a board meeting. See the full reporting cadence →

Case studies

Two analytics engagements. The math.

Analytics questions

What do buyers ask about SaaS marketing analytics?

More on the audit call.

What if we don't have a warehouse?+

We provision one in week one. Typical monthly compute for a SaaS at our client tier is $400 to $1,200. Billed on your account.

Will you replace our existing data team?+

No. We work alongside. If you don't have one we ship the dbt repo and dashboard pack and hand it to whoever inherits. We can also recommend candidates if you're hiring.

Which attribution model do you use?+

Two are shipped in every engagement. First-touch and a multi-touch position-based model. You pick which is canonical. All multi-touch models are approximations. We don't oversell either.

How long until the dashboard is live?+

First dashboard live week four. CFO sign-off typically week six. Full pack of 6 to 12 dashboards delivered by week eight.

Do you do server-side conversions?+

Yes. Warehouse-to-ad-platform conversion uploads using Hightouch or Census. Improves bidding signal. Critical for SaaS where the conversion event happens days or weeks after the click.

What does the CFO sign-off involve?+

A working session walking the eight KPIs end-to-end. Source data, transformation logic, definition, dashboard. The CFO either signs the document or sends us back to fix. Sign-off rate first try is around 60%.

Will Apple, Google and Meta privacy changes break this?+

They've already broken platform attribution. The warehouse model is more resilient because it sits on first-party data we control. We add server-side conversion uploads on top to compensate where signal is lost.

What happens when the engagement ends?+

You keep everything. dbt repo, warehouse, dashboards, KPI documentation. We hand over credentials and run a 30-day support tail. Most clients keep us on a quarterly retainer for upkeep.

Pricing context

What a SaaS marketing analytics engagement actually costs.

A SaaS marketing analytics retainer in our pricing model sits at $7,500/month minimum with a six-month commitment. The retainer covers warehouse attribution rebuilds, dashboard design, CRM hygiene, event tracking and forecasting work across BigQuery, Snowflake, Looker, Metabase or Hex. Tooling (Fivetran or Stitch at $500 to $4,000/month, dbt at free to $300/month) runs separately. We do not mark up tooling or warehouse compute. The audit and roadmap engagement is fixed-fee at $18,000 if you want an analytics rebuild plan. Most analytics rebuilds pay back inside one quarter because the reporting accuracy unlocks budget decisions that were blocked. The full SaaS marketing analytics engagement includes warehouse build, attribution model design, dashboard rollout and CRM hygiene work. Most clients see the source-of-truth dashboard come online inside 60 days and use it in board reporting by quarter end. We do not lock you into our tool stack. The warehouse, the dbt models and the dashboards stay in your account. If you part ways with us at any point you keep the infrastructure. The cost of doing nothing here is usually a quarter of wasted ad spend before someone notices the dashboard was lying.

See all three engagement models Book the 30-minute audit

30 minutes. Your data sources. Our verdict.

Send your URL and a list of the platforms feeding your reporting. We'll come back with a written read on the data layer rebuild.

Book a 30-minute audit call See the case studies
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