IDS Case Study: Optimizing Digital Results Through Machine Learning

By Keiter CPAs

IDS Case Study: Optimizing Digital Results Through Machine Learning

Challenge and Opportunity

An ad agency wanted to optimize the results of its digital advertising strategy for clients while reducing man hours.

 

Approach

  • Converting sales through digital advertising takes enormous resources because of the nature of each customers’ unique tastes or triggers.
  • Our team developed a tool that would use a historical copy of data to optimize digital ads based on viewers’ preferences. This included changing text, color scheme, photography or imagery, and other characteristics.
  • Then the tool ran continuous experiments sending the ads to various demographics. 80% of the recipients were from a targeted market based on preferences the last 20% were a random sample from another market. This was used to target new markets and help automate demographic selection.

Results

The optimization tool yielded results which were four times greater than the agency had previously secured for clients.

 

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About the Author


Keiter CPAs

Keiter CPAs

Keiter CPAs is a certified public accounting firm serving the audittax, accounting and consulting needs of businesses and their owners located in Richmond and across Virginia. We focus on serving emerging growth businesses and companies in the financial servicesconstructionreal estatemanufacturingretail & distribution industries and nonprofits. We also provide business valuations and forensic accounting servicesfamily office services, and inbound international services.

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The information contained within this article is provided for informational purposes only and is current as of the date published. Online readers are advised not to act upon this information without seeking the service of a professional accountant, as this article is not a substitute for obtaining accounting, tax, or financial advice from a professional accountant.

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