Sector Failure Brief
Food & Beverage
Where repeat purchase promises meet the reality of subscription churn.
The Food & Beverage Trap
Low AOV products require high repeat rates to justify acquisition costs. But subscription churn is typically higher than modelled, flavour fragmentation kills bidding efficiency, and LTV projections rarely match reality.
LTV Misuse
Food & beverage brands often justify high CAC with 'LTV' projections that never materialise. Repeat purchase rates are lower than assumed, churn is faster than modelled, and the payback period extends beyond cash flow tolerance.
Implications
- →Model LTV conservatively-use actual cohort data, not projections
- →Track 90-day repeat purchase rates as a leading indicator
- →Calculate payback period against actual cash collection
- →Be skeptical of 'we'll make it up on repeat' justifications
Subscription Acquisition Noise
Subscription models conflate trial acquisition with long-term revenue. High initial conversion rates mask cancellation cliffs. The 'subscriber' you acquired churns at month 3-you've already paid acquisition cost for negative contribution.
Implications
- →Measure subscriber LTV net of expected churn
- →Calculate breakeven point for subscription acquisition
- →Track cohort retention curves before scaling spend
- →Differentiate trial-seekers from committed subscribers
Flavour/Variant Attribution Chaos
Multiple flavours and pack sizes fragment conversion data. Smart bidding can't learn effectively across 50+ variants. Best-sellers subsidise underperformers in blended reporting.
Implications
- →Consolidate variants in feed where possible
- →Use custom labels to identify hero SKUs
- →Segment campaigns by conversion volume tier
- →Exclude low-volume variants from acquisition campaigns
Seasonal Demand Distortion
Gift seasons (Christmas, Easter, Valentine's) drive volume spikes that distort annual performance. Non-seasonal efficiency is often much lower than blended numbers suggest.
Implications
- →Analyse performance excluding peak periods
- →Set separate targets for seasonal vs evergreen
- →Plan for efficiency decline in competitive windows
- →Don't extrapolate Q4 performance across the year