Conflicting revenue
Meta, Google, email and Shopify all claim different sales totals for the same period.
Marketing & customer analytics
See which marketing brings customers who stay.
Advertising, ecommerce, email and analytics platforms often report different versions of performance. Hon Method connects those views to actual business totals and customer behaviour so growing brands can make more informed investment decisions.
Discuss one business problem ↗The problem
More data does not always create a clearer answer.
Each platform is designed to explain its own contribution. That can leave teams comparing incompatible attribution windows, duplicated revenue and customer-acquisition numbers that do not reconcile to the business.
The useful question is not which dashboard is “right.” It is what each measure can support, what the business totals confirm and what still needs a test.
Signs to investigate
Does this sound familiar?
First-sale focus
Acquisition cost is visible, but repeat purchasing and later customer value are not.
Budget uncertainty
The team has reports but still cannot explain which evidence should guide the next change in spend.
Questions we can examine
How does platform-attributed revenue compare with actual order totals?
Which channels acquire customers who make another purchase?
How long does it take customers to place a second order?
Where is a controlled test needed before changing spend?
Information reviewed
Use what the business already has.
- Ecommerce orders, refunds and customer records
- Advertising spend and platform attribution exports
- Website analytics and campaign tagging
- Email performance, promotions and launch timing
- Available product costs or contribution measures
The exact sources depend on the decision. More data is not collected simply for the sake of having it.
Focused ways to start
Marketing performance
Marketing Performance Clarity Review
Reconcile marketing views to actual business totals and clarify what each measure can support.
- One defined marketing or budget decision
- Review of attribution models and windows
- Reconciled revenue and spend baseline
- Separate blended return on ad spend and acquisition-cost baseline
- Limitations and recommended next test
Customer value
Customer Lifetime Value & Cohort Review
Understand who returns and how observed value develops across channels, first products or launches.
- One retention, acquisition or launch decision
- Repeat-purchase rate and time to second purchase
- Observed customer value by cohort
- Lifetime-value estimate only when history supports one
- Visible assumptions and observation limits
Questions, answered
Before we start.
Do the platforms need to agree?
No. Different attribution methods answer different questions. The work makes those differences explicit and reconciles them to reproducible business totals.
Does attribution prove a channel caused a sale?
No. Attribution organizes observed customer paths; it does not establish causation. A controlled test may still be needed.
Can you calculate customer lifetime value immediately?
Only when the available history supports a useful estimate. Otherwise, observed customer value and cohort maturity are shown instead of inventing a projection.
Start with one question
What marketing or customer decision are you trying to make?
We can look at the question, the information you currently have and whether a focused analysis would provide a useful next step.
Discuss one business problem ↗