Case study summary
• Nescafe wanted to drive sales though an online competition, but improve costs and entries on previous year and with the same media budget.
• Boost in entries would come from both new users and extra purchases from loyal users who entered the competition in previous years.
• Banner ad campaign targeted at different segments using past data to create 8000 variations of banner ads using dynamic creative optimisation.
• Data was optimised as it came through during the competition, via a real-time dashboard, using both machine learning and human input.
Nescafe usually run a national on-pack promotional competition every year in Turkey, getting entrants to enter their code from a pack into an online competition. The aim was to drive sales through enhanced ad targeting of their customers, but improve costs and entries on the previous year
The coffee brand wanted a 10% participation increase on their previous year, but with same media budget. The boost in entries would come from both new users and extra purchases from loyal users who had entered in previous years.
The coffee brand reran the competition from the previous year in 2018, but this time targeted at different segments to be more relevant to each, defining these segments based on past competition data. 8000 banners variations of banner ads using dynamic creative optimisation (DCO).
The data was analysed and used to improve targeting of the creative, and was changed in real time as it came through in the competition, via a real-time dashboard. The optimisation was a combination of machine learning and human input.
• Increased code entry users by 35%
• CPA cost reduced by 12%
• 15% Increase in participation (beating their 10% target)
• Code entries: 11.8m
Why it matters
Brands need to be applying “test & learn” thinking to their marketing to sharpen the tactics, explore new channels and unlock marketing innovation.
Previous campaigns are a brilliant resource to build new ones. Here, Nescafe was using past data to inform new customer behaviour. Brands that are proactive with ongoing tests and that embed optimisation can learn and adapt as campaigns evolve to change creative when needed. This boosts the live ROI during the campaign as well as the strategic ROI between one campaign and the next.
Let machine learning do the bulk of data crunching for you, but always have your team add the human touch and check for any conflicts within the AI.