Discover and read the best of Twitter Threads about #MarketingAcad

Most recents (3)

👻👻👻 WHAT PROBLEM DOES GHOST ADS SOLVE? 👻👻👻
This is THREAD #1 about our 2017 JMR paper "Ghost Ads: Improving the Economics of Measuring Online Ad Effectiveness” with @EconInformatics & @enub
#MarketingAcad #DigitalMarketing #EconTwitter #AdFX 1/9 Image
Advertisers like Macy’s want to know the ROI of their #advertising campaigns. To understand the #incremental effect of ads, Macy’s need to know what consumers would do *had they not advertised*. Ad experiments deliver these answers. 2/ Image
#Experiments randomly assign users to Treatment or Control groups. Treatment users can see Macy’s ads and other ads too) but Control users can not. In “PSA” experiments, Control users see unrelated ads (e.g. Red Cross public service announcements) in place of the Macy’s ad. 3/ Image
Read 10 tweets
🔥👿🔥 New working paper alert! 🔥👿🔥
"Inferno: A guide to field experiments in online display advertising"
ssrn.com/abstract=35813…

THREAD: This guide reviews challenges & solutions from a decade of research.
#marketingacad #econtwitter #fieldexperiments Image
“Abandon all hope, ye who enter here” - Dante’s Inferno👿
Online display ad experiments are hell. They are also a proving ground for field experimenters, & have much to teach us. The guide is organized into the nine 9 circles of 🔥hell🔥 as applied to #displayad #fieldexperiments Image
🔥Circle 1🔥 Display ad effects are so small🤏 that observational methods fail🤦‍♀️. Ad effects explain so little variation in ad outcomes, that they get swamped🌊 by unobserved confounds. Like Dante entering the inferno👿, we resign ourselves to the necessity of experiments.😭😭 Image
Read 11 tweets
Have you ever calculated the sample size for an #abtest and come up with a sample size that is bigger than you can ever practically get?

Does this mean you shouldn't run the test?

No!

A paper thread for #MarketingAcad #EconTwitter #Measure #epitwitter 1/17
@marketsensi and I thought about this and came to the conclusion that the standard hypothesis test used to analyze A/B tests doesn’t fit well with the marketing problem that we are usually trying to solve.
2/17
Hypothesis tests are used by academics who want to find small effects with high confidence, but in marketing we care about the big effects. Big effects are where the profit comes from!
3/17
Read 17 tweets

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