Corporate & E-Commerce Performance Review (Weekly Meeting)

Total corporate bookings rose from $91 \to 110$ .
Channel breakdown:
- Cross-network bookings: $67 \to 82$ .
- Paid search bookings: $21 \to 26$ .
- Paid social bookings: remained steady at $2$ .
Meta (Facebook/Instagram) platform-reported conversions doubled:
- $7 \to 14$ week-over-week.
Clarification on lower slide numbers:
- Bottom-line metrics are “in-platform” only (Meta’s own reporting).
- Google Analytics may attribute those conversions elsewhere, so cross-platform discrepancies expected.

Total online purchases dipped slightly: $163 \to 147$ .
Channel breakdown:
- Paid search purchases: $14 \to 15$ (small uptick).
- Paid social purchases: $3 \to 4$ (small uptick).
Summer Sandals campaign highlights:
- Impressions: $56{,}000$ .
- Link clicks: $337$ .
- Click-through rate (CTR): $0.6\%$ .
- Purchases: $49$ .
- Purchase value: $\$9{,}000$ .
- Return on ad spend (ROAS): $13\%$ .
- Formula referenced: $\text{ROAS}=\frac{\text{Revenue}}{\text{Ad Spend}}$ .

Overall campaign performance over refreshed lookback (shorter than 30 days to avoid machine-learning “first-week” noise):
- Impressions: $91{,}000$ .
- Clicks: $497$ .
- Overall CTR: $0.54\%$ .
Version-based performance snapshots (ailment-focused variations):
- V5 (Back Pain):
- Highest CTR: $1.17\%$ .
- Lowest cost per click (CPC): $\$0.84$ .
- Identified by Meta as high-converting but limited-scale audience.
- V2 (reference creative):
- Leads in impressions yet lower CTR and higher CPC vs V5.
- Knee Pain variant shows notably higher CPC, implying competitive auction or narrower qualified audience.
Interpretation & media-buying logic:
- Meta optimizes across multiple levers (cost, predicted conversion, audience size).
- Strong unit-economics (high CTR, low CPC) can be throttled if scale potential is limited.
- Recommendation: extract high-performing ailment (e.g., back pain) into its own standalone campaign to unlock independent scaling and more granular budget control.
- Autonomy may prevent Meta from deprioritizing that creative due to overall ad-set constraints.

Learning Phase vs Optimization Phase:
- First week after launch = Learning. Delivery and results volatile; algorithm tests audiences/placements.
- Post-learning (Optimization) provides more reliable performance signals.
CTR (Click-Through Rate): $\frac{\text{Clicks}}{\text{Impressions}} \times 100\%$ .
CPC (Cost Per Click): $\frac{\text{Ad Spend}}{\text{Clicks}}$ .
ROAS importance: gauges revenue dollar returned per advertising dollar spent.
Scale vs Efficiency Trade-off:
- Meta favors ads that can both convert and spend budget.
- Low-CPC/High-CTR creatives with niche audiences may under-deliver impressions despite efficiency.

Consider developing separate campaigns for distinct ailments (back pain, knee pain, custom orthotics, etc.).
- Allows bespoke budgeting, tailored messaging, and refined bid strategies.
Monitor attribution gaps between Meta’s in-platform reports and Google Analytics to avoid under- or over-crediting channels.
Continue periodic shorter lookbacks for optimization insights; adjust bids/creatives before significant budget shifts.
Re-evaluate knee-pain creative for potential repositioning or audience expansion due to high CPC.
Assess seasonal product focus: sandals currently performing; prepare contingency creatives for upcoming seasons (e.g., fall footwear).

None explicitly noted, but implicit data-privacy best practices when interpreting cross-platform analytics.
Respect algorithmic constraints; avoid over-segmenting audiences causing data scarcity.

Real-world relevance: demonstrates interplay between platform learning algorithms and advertiser control.
Foundational principle: segmentation (ailment-specific) often yields higher efficiency but must balance against reach.
Reinforces importance of triangulating data sources (platform vs GA) for holistic ROI measurement.