Attracting customers by adding value optimisation in Meta Advantage+ app campaigns

Hungerstation is an app-based service that delivers everything from restaurant and supermarket food to items from pharmacies and florists. Hungerstation features products from over 20,000 business partners in more than 80 cities in Saudi Arabia and Bahrain.

Hungerstation wanted to maximise the performance of its Advantage+ app campaigns. These automated campaigns improve performance by using machine learning and artificial intelligence to understand what works and then automatically adjust settings across audience, ad creative and placement settings.

Hungerstation usually optimised its Advantage+ app campaigns for app events (orders). But because the company hoped to attract new high-value customers and improve efficiency, it decided to test value optimisation.

When advertisers optimise for value, Meta uses machine learning to predict how much return on ad spend a person may generate and uses this prediction to bid for high-value customers. By bidding more for people who are likely to spend more, advertisers stand a greater chance of maximising the value of conversions for their campaigns.

Hungerstation ran an A/B test to compare the performance of its usual approach of optimising its Advantage+ app campaigns for app events (orders) against the new approach of optimising for value.

The team showed its ads to Arabic-speaking adults 18 and over in Saudi Arabia, excluding people who had who previously ordered from Hungerstation. It also used the Advantage+ placements feature to allow Meta to automatically deliver ads across all placements based on which were most likely to drive the best campaign results at the lowest cost at any given time, and the Advantage+ campaign budget feature to automatically distribute the budget across the best-performing ads in real time.