Artificial Intelligence (AI) is a subject in computer science and it aimed at building machines and computers that can enhance logical operations. AI systems are capable of taking data driven decisions naturally associated with human intelligence. Over the past couple of years and with the evolution of MarTech, AI has become a salient part of our lives in some form or other.

Advertising platforms like Facebook/Google are also heavily invested in AI to provide a seamless experience for both users and advertisers on their platforms by using the ability of AI to bring personalized and relevant content closer to the user.

AI is a process which involves constant learning and improvisation to meet an advertiser’s goal. While a platform like Facebook is implementing these learnings, these learning comes at the cost of the media spent by the advertiser. Unfortunately, the learning is not always translated back to the partner agency/advertiser to learn from in future campaigns.

One of such examples is the announcement Facebook made on Campaign Budget Optimization becoming fixed default, early this year they announced that CBO will be a fixed default from 1^st September 2019. The change however was not rolled out. This would mean that Facebook will control the budget allocation across adsets/targeting to meet the campaign goal most effectively.

We at DAN Data Labs ran multiple tests to let our Budget Optimizer compete with this native feature on Facebook. After rigorous testing, found an amazing average of 15% efficiency that the DDL Budget Optimizer was able to bring to a campaign optimized through the tool compared with the Facebook native CBO. How, you ask? The DAN Data Labs Budget Optimzer considers multiple factors like CPA, No. of actions, Audience saturation and volatility before suggesting a recommendation giving you the best possible allocation in budget. Reference output is mentioned below:

We all know and would agree that targeting plays an extremely important role in our campaigns performance. Target groups on Facebook as we all know are a combination of multiple interests that come together to form that target group. The performance, good or bad is decided on the overall target group. It is possible that certain interests within a target group would be doing great compared to others. Facebooks business manager doesn’t give us that granular and deep insights of each interest within a targeting group.

We at DAN Data Labs realized the importance of this is by giving you a granular understanding of your interest targeting performance and take optimization calls by removing the interests that aren’t working well. Since removing interests would in some cases mean reducing scale, it also gives you interests recommendations based on the one’s that are working well to keep the scale growing. A sample output is giving below:

With these tools and our Transparent AI we aim at helping decode these learnings, take the necessary steps of optimization and most importantly bring value and delight to our advertisers. These learnings not only bring us the edge our advertisers are looking for in an agency but also form the foundation for more effective planning for future campaigns.

With over 30 markets across DAN using our products, numerous case studies and Facebook’s FMP (Facebook Marketing Partner) badging is a testimony to the work we’re doing.

We are thankful for your support and are constantly working towards the goal of providing this seamless experience for you and your advertisers.