Data Science for advertising is like accounting. In both areas, you measure and identify exactly which parts of a business are – or aren’t – profitable. Advertising ROI improves dramatically by cutting out, "the fat."
Let's compare Traditional Advertisers to Data Science Advertisers:

Why does this matter? With data science, you can:
· Know which ads are working versus guessing by conversion rate.
· Run more experiments without uncertainty.
· Get faster insights.
· Get faster, more efficient results.
· Reduce spending while increasing corporate revenue.
Without exception, every client working with traditional advertisers wastes 60% of their spending – even including the most highly skilled marketers. In many cases, these advertisers fail to produce a positive ROI at all.
This waste of ad spend is largely due to traditional marketers assuming that clicks, conversions, and online interest translates to company revenue. Often times, a good conversion rate on a "good" keyword is assumed to work. We've found that's only the case about 50% of the time. Often, other opportunities exist with ads and/or copy that people weren't sure about. Traditional marketers outside of e-commerce often have customer surveys indicating “how did you hear about us.” This won’t indicate which ads/strategy are optimal when running multiple different keywords, ads, etc. The inability to determine what is efficient at a lower level is a key skill offered by Data Analysts.
The most important lesson?
Clicks & Conversions ≠ Customers.
In the next post we will cover some specific examples.
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