Marketing Analytics and Attribution
Aim: Grow the Business → Objective: Reach $10M ARR by FY27 →
Initiative: Build a marketing analytics and attribution system that
tells you which dollar produces the next dollar of revenue
Fits well at: sub-$5M businesses where every marketing dollar matters
and there's no analyst to assemble the picture. Also valuable at $5M–$25M
where the channels have multiplied but the measurement hasn't kept up.
What this is
The discipline of measuring what marketing actually produces — funnel
definition, source attribution, CAC by channel, LTV by cohort, payback
period. Without it, growth investment is faith-based: you spend, you hope,
you check revenue a quarter later and guess which spend mattered.
This initiative answers one question: "Which marketing dollar produces the
next dollar of revenue?" It connects marketing activity to pipeline to
closed revenue to lifetime value, channel by channel, so you can double
down on what's working and cut what isn't — with data, not intuition.
What "done" looks like
A defined marketing funnel with named stages (impression → visit →
lead → MQL → opportunity → customer) and clear stage-entry criteriaSource attribution on every lead — how they found you, first touch and
last touch, with multi-touch weighting where the data supports itCAC computed by channel, refreshed continuously from accounting and
pipeline dataLTV by acquisition cohort, updated monthly as retention data matures
Payback period by channel — how many months until a channel's
customers repay their acquisition costA channel-level P&L: spend, leads, conversions, revenue, margin — per
channel, per monthA weekly marketing performance dashboard the founder actually checks
A standing Monday brief summarizing the prior week's channel
performance, prepared by the marketing agent
The work, decomposed
Sub-objective: Define the funnel → name the stages, set entry
criteria, instrument the transitionsSub-objective: Instrument attribution → capture source on every
lead, define first-touch and last-touch rules, store the dataSub-objective: Connect spend to revenue → pull marketing costs from
accounting, tie them to channels, compute CACSub-objective: Build cohort analysis → group customers by
acquisition month and channel, track retention and LTV over timeSub-objective: Compute payback → CAC ÷ monthly gross margin per
cohort, by channelSub-objective: Stand up the dashboard and brief → live views for
daily use, weekly summary for the Monday brief
How it runs in HAPPEE
Agents involved
Marketing agent. Owns the analytics system end-to-end. Defines
funnel stages, maintains attribution rules, compiles the weekly
performance brief, and surfaces anomalies ("paid search CAC jumped 40%
this week — here's why"). Posts the Monday brief in #marketing.Finance agent (Alex). Pulls marketing spend from accounting by
channel, computes blended and channel-level CAC, builds the cohort LTV
model, and flags channels where payback exceeds the threshold.Sales agent. Ensures source attribution is captured on every lead
entering the pipeline. Tags opportunities with the originating channel
so closed-revenue attribution flows back to marketing.
Where the work lives
Accounting — marketing spend by channel, categorized in the chart
of accounts so cost-per-channel is always currentDirectory — leads and customers with source attribution fields
(first touch, last touch, channel)Tracker — pipeline with channel attribution on every opportunity,
enabling closed-revenue-by-channel reportingFinancial Models — cohort LTV model, channel-level P&L, payback
calculator with scenario branching (what if we 2× paid search spend?)Analytics time-series — impressions, visits, leads, MQLs,
opportunities, customers — by channel, by week; CAC, LTV, payback —
by channel, by cohortDashboards (Live Views) — marketing performance dashboard with
channel breakdown, funnel conversion rates, CAC trend, LTV by cohortKnowledge Base — funnel definitions, attribution rules, channel
playbooks, experiment logs, weekly brief archiveChannels — #marketing for the Monday brief, experiment results,
anomaly alerts
Rhythms
Daily — marketing agent monitors channel metrics and surfaces
anomalies worth same-day attentionWeekly — Monday brief: prior week's channel performance, funnel
conversion rates, CAC movement, any experiments concludedMonthly — cohort LTV refresh, payback recalculation, channel-mix
review with reallocation recommendations
Data flows
Marketing spend (accounting) + leads by channel (directory) → CAC by
channelLeads → pipeline stages → closed revenue → revenue attributed by
channelCustomers by acquisition cohort → retention curve → LTV by cohort →
payback by channelChannel metrics → analytics time-series → dashboard → Monday brief
Experiment outcomes → channel playbook updates → spend reallocation
decisions
Before HAPPEE vs. with HAPPEE
| Traditional | With HAPPEE | |
|---|---|---|
| Attribution | UTM parameters in a spreadsheet someone updates monthly | Captured on every lead, connected through pipeline to revenue |
| CAC by channel | Quarterly guess from the accountant and marketing manager | Continuous, computed from accounting and pipeline data |
| LTV by cohort | Annual exercise, if ever | Monthly refresh, by channel |
| Weekly performance review | Someone pulls data from 4 tools into a slide deck | Monday brief assembled automatically from live data |
| Channel reallocation decisions | Gut feel plus last quarter's numbers | Data-driven, with scenario modeling |
| Feasible without an analyst? | No | Yes — the marketing agent and Alex handle it |
Day in the life
Monday, 7:15am. The founder opens #marketing and finds the Monday brief
already posted. Last week: paid search generated 34 leads at $127 CAC
(up from $98 — the marketing agent flags a competitor bidding on the
brand terms). Organic content produced 22 leads at $14 CAC, with 3
converting to opportunities. The referral channel delivered only 4 leads
but two are already in late-stage pipeline. Below the summary, a
channel-level P&L shows that organic content's 90-day payback is 2.1
months while paid search has crept to 4.8. The marketing agent recommends
shifting $2K/month from paid search to content production and proposes
an A/B test on the landing page to recover paid search conversion. Alex
has updated the cohort model — Q1 customers are retaining 12% better
than Q4, and LTV is trending toward $4,200. The founder approves the
budget shift, greenlights the A/B test, and asks the marketing agent to
make the Monday brief a standing item. Done. The loop is closed.
Related Initiatives
- Build an outbound sales motion
- Customer success and expansion program
- Pricing and packaging refresh
Features in play: Accounting · Directory · Tracker · Financial Models · Analytics & Dashboards · Knowledge Base · Channels · Agents · Notifications · Imports
Related
Grow existing business
Build an Outbound Sales Motion
Target list, cadence, calls, transcripts, weekly review — the full motion from cold to closed.
Grow existing business
Run a Pricing and Packaging Refresh
Competitive scan, willingness-to-pay, scenario modeling, controlled rollout.
Grow existing business
Customer Success and Expansion Program
Health scores, QBRs, expansion pipeline, renewal forecast — the loop that keeps revenue alive.