Digital Campaign Optimization Algorithms Reduce Customer Acquisition Costs By 50%

Business Objective

Our client is a global multinational financial services corporation, headquartered in the US.

Their key business need was to bring down customer acquisition costs for social media campaigns while also achieving new customer growth targets. Previous attempts had yielded less than desired results in this direction. They wanted to do  Digital Campaign Optimization.

  • 5 different types of credit cards to take to market in 10 countries across continents
  • Conversions are typically rare events when compared to the volume of clicks. For example, a million impressions can lead to just one conversion

Solution Methodology
  • Developed an analytics framework to:
    • Identify high performing segments
    • Identify ad creatives with high ROI
    • Determine optimal bidding price – CPC vs CPM
    • Allocate budgets across segments and ad creatives
    • Optimize spend based on time of day and day of week
  • Classified the audience into tens of thousands of segments based on factors such as granular geographies, demographics, interests, etc.
  • Identified, statistically, high-performing segments based on parameters such as CTR, CPC, CPA, etc.
  • Aligned ad bidding to segment performance
  • Used bandit strategies to allocate budget toward relevant audience segments and ad creatives. Optimized campaigns by time of day and day of week.
Business Impact
  • The solution reduced the cost of customer acquisition by about 50% for a multi-million dollar digital campaign.

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