Discover how Lifesight’s Incrementality Tests and Geo-Experiments empowered a Personal Care Brand to confidently increase its advertising budget Texas-based women’s lifestyle brand, with a $500,000 monthly ad spend and 30 years in eco-conscious personal care, hit a growth plateau. Despite digital savvy and successful Google Shopping campaigns, they struggled with unclear channel efficacy and campaign overlap, prompting an urgent need to scrutinize their marketing impact.

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Castrol - Lifesight
Bath Body Works - Lifesight
Ray Ban - Lifesight
Goodr - Lifesight
Much Better Adventures - Lifesight
Harvey Beef - Lifesight
Mango - Lifesight
KTM - Lifesight
Krispy Kreme - Lifesight
Spendless - Lifesight
New Balance - Lifesight
IKEA - Lifesight
Sealy - Lifesight
- Lifesight
Pretty Fit - Lifesight
Costa Coffee - Lifesight
Scorewarrior - Lifesight
Dyson - Lifesight
OsborneHomes - Lifesight
Grohe - Lifesight
Seidensticker
Sunglass hut - Lifesight
Eu yan Sang - Lifesight
British American Tobacco
Mango 1 - Lifesight
BetterBrand - Lifesight
San Miguel - Lifesight
Subway - Lifesight
KFC - Lifesight
Euromaster
Decathlon - Lifesight
Ponos - Lifesight
Guardian - Lifesight

Unlocking budget potential through Lifesight Incrementality Measurement and Geo-Experiments

Explore how Lifesight's Incrementality Measurement and Geo-Experiments empowered a Personal-care brand to bolster their ad budget and enhance ROI.

Challenges

  • One big question persisted: Was the brand’s lack of growth due to ineffective media strategies, or were other factors involved?
  • With so many digital tactics in use, it was hard for the brand to figure out which ones were actually boosting the bottom line.
  • Issues like unclear accountability and overlapping campaigns made it even more challenging to know where to invest resources effectively.

Solution

Leveraging Lifesight’s Geo-experiment feature, the brand customized a campaign targeting specific geographic areas. Relying on AI-backed insights, they implemented strategic recommendations and monitored real-time metrics. They then analyzed incremental lift across channels and tactics, and optimized future campaigns based on these data-driven findings.

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