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Ads Jim Jansen College of Information Sciences and Technology  The Pennsylvania State University  [email_address]
Pre-Campaign Strategy ,[object Object],[object Object],[object Object],[object Object],[object Object],Need to review and make a check list – review your Pre-campaign Strategy report item by item.
Structure of Pre-Campaign Strategy ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Client Overview (Pre-Campaign Strategy) ,[object Object],[object Object]
Client Overview Part 01  (Pre-Campaign Strategy) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Client Overview Part 02  (Pre-Campaign Strategy) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Client Overview Part 03  (Pre-Campaign Strategy) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Client Overview Part 04  (Pre-Campaign Strategy) ,[object Object]
Ad Words Strategy  (Pre-Campaign Strategy) ,[object Object],[object Object]
Ad Words Strategy  (Pre-Campaign Strategy) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Keyword Advertising Exercise ,[object Object],[object Object],[object Object],[object Object],[object Object],You have 10 minutes. Begin
Writing Key Words Ads ,[object Object],[object Object],[object Object],[object Object]
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 …
Writing Key Words Ads ,[object Object],[object Object],[object Object],[object Object]
 
Successful Keyword Advertising ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Keyword Advertising Exercise ,[object Object],[object Object],[object Object],[object Object],You have 20 minutes. Begin
What to do next? ,[object Object],[object Object],[object Object],[object Object]
Thank you! (reminder to do your daily logs) Jim Jansen College of Information Sciences and Technology  The Pennsylvania State University  [email_address]

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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]
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 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 …
  • 14.
  • 15.  
  • 16.
  • 17.
  • 18.
  • 19. Thank you! (reminder to do your daily logs) Jim Jansen College of Information Sciences and Technology The Pennsylvania State University [email_address]

Editor's Notes

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.