Lesson 11 Writing Good Ads
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Lesson 11 Writing Good Ads
- 1. Ads Jim Jansen College of Information Sciences and Technology The Pennsylvania State University [email_address]
- 13. Look at it this way … … to get a potential customer’s attention ~ 2 inches ~ 1/2 inch = 1 square inch = 1 second For a given ad …
- 19. Thank you! (reminder to do your daily logs) Jim Jansen College of Information Sciences and Technology The Pennsylvania State University [email_address]
Notes de l'éditeur
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.
- So what did we actually decide on? We didn’t want to solely look at performance so we ended up incorporating 30 different signals within 5 distinct categories. Performance, as discussed earlier. Account structure Tool and feature usage Advertiser savviness Budget management To come up w/ the final list, we worked closely with focus groups consisting of AdWords Optimizers, Managers and Engineers and determined the ideal mix of signals, thresholds and weights based on their feedback. We then validated and refined the initial algorithm using Beta competition groups that started before the actual challenge. And based on qualitative rankings of those accounts, we fine-tuned and measured the performance of the algorithm.