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Three Course Requirements and What You Should Do About Them Jim Jansen College of Information Sciences and Technology  The Pennsylvania State University  [email_address]
The Challenge ,[object Object],[object Object],[object Object],[object Object],[object Object],This is a course, so major goal is the learning objectives, but …  …  why not do your best?
The Scoring Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Campaign Statistics ,[object Object],[object Object],[object Object],[object Object],[object Object]
Campaign Statistics ,[object Object],[object Object],[object Object]
Campaign Statistics ,[object Object],[object Object],[object Object]
Campaign Statistics ,[object Object],[object Object],[object Object]
Campaign Statistics ,[object Object],[object Object],[object Object],[object Object]
Written Report Format ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Pre-Campaign Strategy ,[object Object],[object Object],[object Object],[object Object],[object Object]
Client Overview (Pre-Campaign Strategy) ,[object Object],[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]
Communication and readability  (Pre-Campaign Strategy) ,[object Object],[object Object],[object Object],[object Object],[object Object]
Post-Campaign Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Executive Summary   (Post-Campaign Summary ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Industry Component Part 01  (Post-Campaign Summary ) ,[object Object],[object Object],[object Object],[object Object]
Industry Component Part 02  (Post-Campaign Summary ) ,[object Object],[object Object],[object Object],[object Object]
Industry Component Part 03  (Post-Campaign Summary ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Industry Component Part 03  (Post-Campaign Summary ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Industry Component Part 04  (Post-Campaign Summary ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Learning Component Part 01  (Post-Campaign Summary ) ,[object Object],[object Object],[object Object]
Learning Component Part 01  (Post-Campaign Summary ) ,[object Object],[object Object]
Post-Campaign Summary Part 03 ,[object Object],[object Object],[object Object],[object Object],[object Object]
Post-Campaign Summary Part 03 ,[object Object],[object Object],[object Object]
Dr. Jansen’s Recommendations ,[object Object],[object Object],[object Object],[object Object],[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 05 Three Course Requirements

  • 1. Three Course Requirements and What You Should Do About Them Jim Jansen College of Information Sciences and Technology The Pennsylvania State University [email_address]
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  • 31. Thank you! (reminder to do your daily logs) Jim Jansen College of Information Sciences and Technology The Pennsylvania State University [email_address]

Notas del editor

  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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.