Applying Artificial Intelligence to Creative
By Kantar - Boston
For Global Advertisers Brand Kantar Analytics Practice, Insights Division North America
Winner in category Data-Driven
Insights
Project Description
Advertisers budgets are under pressure. There is significant opportunity to reduce waste along the creative development funnel, improve creative performance, and accelerate creative idea-to-execution, primarily through the following pathways:
• Reduce production inefficiencies and costs
• Maximize creative effectiveness
• Accelerate roll-out of creative executions with confidence.
We focused on maximizing the value of existing creative executions by:
• Predicting which creative successfully travel from one market to another and thereby reduce production costs and accelerate creative deployment.
• Ensure deployment of high-quality creatives which have a demonstrable impact in driving increased sales.
We are creating a portfolio of AI/ML solutions to enable advertisers to reduce production costs, maximize creative impact, and accelerate rollout of campaigns.
• Reduce production inefficiencies and costs
• Maximize creative effectiveness
• Accelerate roll-out of creative executions with confidence.
We focused on maximizing the value of existing creative executions by:
• Predicting which creative successfully travel from one market to another and thereby reduce production costs and accelerate creative deployment.
• Ensure deployment of high-quality creatives which have a demonstrable impact in driving increased sales.
We are creating a portfolio of AI/ML solutions to enable advertisers to reduce production costs, maximize creative impact, and accelerate rollout of campaigns.
Agency Solution
Imagine a scenario where the advertiser wants to rollout a campaign for a new market. The advertiser does not know whether to produce new creative for the new market or borrow a successful creative from another market and potentially copy test in the new market and reuse in the new market. Often the advertiser does not have the budget to test ads everywhere. In either case the advertiser has to spend additional production costs and/or copy testing costs and delay rollout of the campaign in the new market. The advertiser needs to have the confidence to not test an ad in each market; previously clients relied on geographic closeness, cultural similarity, some market clustering analysis and so on. Now we can answer whether an ad can travel successfully using AI and machine learning.
How do we do it?
Our robust global database of approximately 200,000 ads tested across over 100 countries provides us an unparalleled view into what drives superior creative performance in every market and how the same creative performs differently in different markets and audiences.
We built an AI/ML model with inputs such as ad characteristics, country characteristics, brand’s category, brand’s BDI/product lifecycle, brand health, etc.
How do we do it?
Our robust global database of approximately 200,000 ads tested across over 100 countries provides us an unparalleled view into what drives superior creative performance in every market and how the same creative performs differently in different markets and audiences.
We built an AI/ML model with inputs such as ad characteristics, country characteristics, brand’s category, brand’s BDI/product lifecycle, brand health, etc.