PepsiCo experiments with weather activations on Facebook & Instagram for Lipton Ice Tea
PepsiCo experiments with weather activations on Facebook & Instagram for Lipton Ice Tea
Campaign Overview:
Background
PepsiCo is a major multinational food, snack, and beverage corporation. Formed in 1965 and with annual net revenues of over $70 billion, PepsiCo is the second largest food and beverage company in the world. One of PepsiCo’s products is Lipton Ice Tea – a chilled tea-based soft drink which comes in various flavors.
Challenge
The digital ads team at PepsiCo wanted to test whether pairing live weather signals with weather specific ad creative for Lipton Ice Tea would result in improved performance of their ads. “We wanted to see if different weather would trigger different responses from the user” explained Francisco, ecommerce manager at PepsiCo.
Objective
The objective of the campaign was to build awareness amongst the target demographic on Facebook and Instagram. Given that Lipton Ice Tea is an ‘offline’ CPG product, the key metrics PepsiCo tracked were ad click-through rates and engagement rates.
Strategy & Execution
Lipton devised and executed a series of experiments aimed at testing the effect that weather signals and weather specific creative had on ad performance. For example, two sets of weather relevant creative were paired with unique weather scenarios – a ‘Sunny Version' ad activated by a real-time sunshine index, and a ‘Rainy Version' ad, activated by real-time rainfall. There was also a control group of non-weather related ads which did not utilize weather triggers.
Results
The team saw an increase in click through rate (CTR) amongst the weather relevant ads, although there did not appear to be any major differences in engagement between the sunny and the rainy version - with geo location (e.g. Manchester vs London) appearing to have a bigger impact on ad performance across the two versions.
The feedback from the Pepsico advertising team was very positive. Experiments are ongoing, with further weather variables to be tested, more data to be gathered and more learnings to be gleaned.
“[We were able to obtain] great learnings to know what truly impacts the user”
- Francisco, Ecommerce Manager, PepsiCo
