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Targeting Online Ad Budget
Technology Category
- Analytics & Modeling - Predictive Analytics
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Demand Planning & Forecasting
- Predictive Replenishment
Services
- Software Design & Engineering Services
- System Integration
The Challenge
The company was interested in using digital media to drive new customer acquisition but they were unsure if their investments would generate high ROI. The bank had tested online ads in some markets, but due to weekly volatility, impact of local market conditions, and other external factors, the client had a difficult time isolating the cause-and-effect relationship between online ads and new account generation in the branch.
About The Customer
A top US bank, which is a major player in the financial industry, was looking to leverage digital media to enhance its customer acquisition strategy. The bank had previously experimented with online advertisements in various markets but faced challenges in determining the effectiveness of these ads due to fluctuating market conditions and other external factors. The bank's primary goal was to identify whether their digital media investments were yielding a high return on investment (ROI) and to understand the specific conditions under which these ads were most effective. With a large customer base and numerous branches across the country, the bank needed a robust solution to accurately measure the impact of their online advertising efforts.
The Solution
The client turned to APT’s Test & Learn software to help them measure the in-branch impact of online ads. APT software used patented algorithms to construct a custom, well-matched control group from markets where online search and display ads were not being shown. Test & Learn analysis showed that, on average, the online ads improved branch new account acquisition by 3%. However, automated de-averaging determined that the increase was greatest in markets with greater brand presence in the previous year, areas with a higher median income, and where there were more college graduates. Based on these identified drivers of performance, APT software built a predictive model, which targeted markets scientifically proven to respond positively to the test.
Operational Impact
Quantitative Benefit
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