Understand what's really driving revenue — and invest confidently.
A 90-day sprint to make your analytics reliable, see which channels actually drive profitable revenue, and use attribution to guide budget, bids, and creative decisions.
Book Your Attribution ReviewSee the Sprint PlanBusiness types: DTC brands, ecommerce stores (single or multi-brand), consumer subscription products, and B2C apps with web acquisition funnels.
Typical situation: You're investing in paid channels (Meta, Google, TikTok, influencers, affiliates), but ad platforms report different numbers than your store or GA4, attribution feels messy post-iOS, and budget decisions rely on last-touch or gut feel.
Stakeholders: Head of Ecommerce / Growth / Marketing, Performance Marketing Lead or Agency Partner, Analytics / Data Lead, Ecommerce / Product Owner.
What you'll have by the end of the 90-day sprint.
Clean, dependable measurement of purchases, revenue, AOV, subscriptions, and repeat purchases
A pragmatic attribution approach — simple, understandable models that match how your buyers behave
Clear rules for when to trust platform data vs analytics vs backend
Unified dashboards with channels ranked by revenue, orders, and ROAS/POAS
2–3 concrete attribution-driven optimizations (budget shifts, bid/creative changes, channel tests)
Upfront alignment so we move fast once the sprint starts.
Primary revenue event (e.g., online purchase, subscription start, first in-app purchase).
Key secondary events (add-to-cart, checkout start, email/SMS sign-up, repeat purchase).
Source of truth for revenue (ecommerce platform, billing/subscription system, app backend).
Attribution approach: start with transparent rule-based models; lean into algorithmic only after data is clean and validated.
AAJ rarely relies on a single model — we use multiple views in parallel for different decisions.
| Model | When We Use It | Pros | Cons |
|---|---|---|---|
| Last Click (Non-Direct) | Simple baseline; lower volume or early data maturity | Easy to interpret; useful for quick sanity checks | Over-credits retargeting, branded search, email; under-credits discovery |
| Time Decay | Short journeys (hours to days) with multiple interactions | More weight to touchpoints closer to purchase; realistic for multi-touch | Rule-based decay curve is an assumption; can under-credit top-of-funnel |
| Position-Based (40-20-40) | Value both discovery (first touch) and conversion (last touch) | Balances discovery and conversion roles; intuitive for full-funnel teams | Weights are partly arbitrary; needs volume and consistent tagging |
| Data-Driven / Algorithmic | Sustained spend and enough volume; robust modeled conversion tools or MMM | Handles complex journeys and privacy-driven data loss | Opaque 'black box'; always cross-check with backend revenue and experiments |
Deliverables
Analytics & Tracking Health Audit (B2C) — what's working, what's broken, priority fixes.
Client input: Grant access to analytics, ecommerce platform, and ad accounts.
Weeks 4–6Deliverables
Tracking Fix Plan, UTM & Campaign Naming Guide, Baseline Dashboard & Performance Summary.
Client input: Coordinate dev team for tracking changes; confirm naming conventions.
Weeks 7–9Deliverables
Attribution Comparison Report (B2C), Experiment Briefs & Read-outs.
Deliverables
Attribution Playbook (B2C), Dashboard links, SOP Pack, 60-minute training session.
The funnel we'll map together and the metrics that matter.
Real-world tests to sanity-check models and guide trust.
Client-ready assets you receive throughout the engagement.
What's working, what's broken, priority fixes — concise PDF or deck.
Definitions for each funnel step and KPI with targets/benchmarks.
Specific, prioritized tracking tasks for your dev/ops team.
Simple, shareable reference for consistent campaign tagging.
Current snapshot, funnel leaks, and platform vs store disagreements.
Side-by-side views for major channels with model recommendations.
Which models/views for which decisions, limitations, and review cadence.
Weekly review checklist, monthly budget review template, experiment log.
Live walkthrough of dashboards, attribution views, and decision-making.
Three dashboards AAJ hands off to your team.
How decisions get made and who owns what.
Weekly Performance Review (15–30 min)
Check spend vs budget, core KPIs vs last week and target, anomalies or tracking alerts. Decide on tactical budget shifts and creative adjustments.
Monthly Attribution & Budget Review (45–60 min)
Review platform vs analytics vs backend views, attribution comparison for major channels, experiment results. Decide next month's budget allocation and new experiments.
Access & Change Controls
Define who can change analytics events, pixel settings, dashboard logic, and attribution windows in ad platforms.
Three steps to launch your B2C attribution sprint.
1Walk through your current tracking, spend levels, and reporting challenges (30-min review call).
2AAJ scopes a 90-day sprint mapped to this playbook and your current stack.
3Fix data foundations, validate what's working, and start making confident, attribution-driven decisions.
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