SuperMomGood product, good team — the targeting was the problem
SuperMom had a real catalog and a dedicated team, but Facebook campaigns weren't reaching the audience that actually buys — and nobody could tell why.
Leads
Cost per lead
Managed spend
Link clicks
Figures verified against a Meta Ads Manager screenshot showing account-level totals across 72 campaigns.
Context
SuperMom serves the moms-and-family shopping audience — a business built around a community, not just a product catalog.
The challenge
Welovesupermom.com needed to attract new leads and increase engagement across the largest parenting marketplace in Asia. The existing Facebook advertising wasn't efficiently turning awareness into qualified leads, and there was no systematic process for testing creative or optimizing against real KPIs.
What we did
- Creative testing: ran systematic creative tests to find the messaging, visuals and formats that actually resonated with parents and expectant mothers.
- Hypothesis testing: built structured hypotheses around audiences, offers and creative angles rather than guessing at what would work.
- KPI-driven optimization: optimized spend continuously against real KPIs — cost per lead, link-click cost and lead quality — not vanity metrics.
Outcome
$275,408.08 in managed Meta spend generated 49,135 leads at a $5.60 cost per lead, with 191,150 link clicks and a $1.44 average CPC. The work was driven by systematic creative and hypothesis testing, then optimized against real KPIs.
Timeline · How it actually unfolded
Twelve weeks, mapped week by week — here's the system, not the luck.
About the client
Welovesupermom.com is the largest marketplace for parents and expectant mothers in Asia — nappies, baby food, strollers, car seats, toys and more — and the largest parenting community in the region, founded by mothers.
Creative testing
Tested ad creative systematically to find what actually resonated with this audience before scaling spend behind it.
Hypothesis testing
Ran structured hypothesis tests on targeting and messaging rather than guessing at what would work.
KPI-driven optimization
Optimized continuously against real KPI data — cost per lead and lead quality — not vanity metrics.
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