Sector Failure Brief
Home & Living
High-AOV categories with hidden complexity-and hidden margin traps.
The Home & Living Challenge
High average order values create the illusion of advertising efficiency. But long consideration cycles, high fulfilment costs, and seasonal volatility often erode margins faster than ROAS reports suggest.
AOV Lag Misleads Efficiency
High AOV products skew ROAS upward, masking poor conversion rates and high CAC. A £500 sofa sale at 4x ROAS sounds great until you realise you spent £125 to acquire one customer who may never return.
Implications
- →Calculate CAC and LTV separately from ROAS for high-AOV items
- →Consider contribution margin per customer, not per order
- →Factor in long consideration cycles (often 30-90 days)
- →Measure assisted conversions-high-AOV often requires multiple touchpoints
PMAX Misreads Purchase Intent
Performance Max conflates browsing with buying. Home décor has high visual engagement but long research cycles. PMAX may over-weight top-funnel signals and under-deliver on conversions.
Implications
- →Segment PMAX asset groups by purchase intent level
- →Use longer attribution windows for consideration-heavy categories
- →Monitor new vs returning customer split in PMAX
- →Compare PMAX efficiency to dedicated Shopping campaigns
Fulfilment Cost Blindness
Large, heavy, or fragile items cost more to ship. Free shipping thresholds designed for apparel destroy margins on furniture. Damaged goods add a second layer of cost.
Implications
- →Calculate true cost-per-order including shipping and handling
- →Segment campaigns by product weight/size tier
- →Adjust ROAS targets to reflect fulfilment reality
- →Consider whether certain products should be excluded from acquisition campaigns
Seasonal Demand Volatility
Home & living has extreme peaks (Black Friday, Boxing Day, spring refresh). Scaling into peaks without margin awareness leads to volume at the expense of profitability.
Implications
- →Plan for aggressive efficiency decline during peaks
- →Separate seasonal campaign structures from evergreen
- →Model expected CAC increase during competitive periods
- →Resist the temptation to 'win' peak season at any cost