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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/31597
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| Title: | Evaluating and Optimizing Online Advertising: Forget the click, but
there are good proxies |
| Authors: | Dalessandro, Brian
Hook, Rod
Perlich, Claudia
Provost, Foster |
| Issue Date: | 22-Aug-2012 |
| Series/Report no.: | ;CBA-12-02 |
| Abstract: | A main goal of online display advertising is to drive purchases (etc.)
following ad engagement. However, there often are too few purchase
conversions for campaign evaluation and optimization, due to low
conversion rates, cold start periods, and long purchase cycles (e.g.,
with brand advertising). This paper presents results across dozens of
experiments within individual online display advertising campaigns, each
comparing different 'proxies' for measuring success. Measuring success
is critical both for evaluating and comparing different targeting
strategies, and for designing and optimizing the strategies in the first
place (for example, via predictive modeling). Proxies are necessary
because data on the actual goals of advertising (e.g., purchasing,
increased brand anity, etc.) often are scarce, missing, or fundamentally
difficult or impossible to observe. The paper presents bad news and good
news. The most commonly cited and used proxy for success is a click on
an advertisement. The bad news is that across a large number of
campaigns, clicks are not good proxies for evaluation nor for
optimization: buyers do not resemble clickers. The good news is that an
alternative sort of proxy performs remarkably well: observed visits to
the brand's website. Specifically, predictive models built based on
brand site visits do a remarkably good job of predicting which browsers
will purchase. The practical bottom line: evaluating campaigns and
optimizing based on clicks seems wrongheaded; however, there is an easy
and attractive alternative|use a well-chosen site visit proxy instead. |
| URI: | http://hdl.handle.net/2451/31597 |
| Appears in Collections: | NYU Stern Center for Business Analytics
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