Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Frederick Vallaeys - Will Robots Take Over PPC? What the Future of the Industry Looks Like.

2,378 views

Published on

Marketing Festival 2016

Published in: Marketing
  • Be the first to comment

Frederick Vallaeys - Will Robots Take Over PPC? What the Future of the Industry Looks Like.

  1. 1. Will Robots Take Over PPC?
  2. 2. About Me @SiliconVallaeys frederick@optmyzr.com
  3. 3. Agenda: Trends That Will Change PPC Automation The On-Demand Economy Artificial Intelligence
  4. 4. Trend #1 Automation
  5. 5. Making a Case For Automation...
  6. 6. The Case Against Automation...
  7. 7. 5 Levels of automation for PPC
  8. 8. Level 1 - Monitor and Alert Alert a human when something may need attention. Try this AW Script: bit.ly/GranularAnomalyDetector
  9. 9. Level 2 - Manage Individual Components Run automated tasks for each entity, keywords, bids, ads, etc. → Automated Rules
  10. 10. Level 3 - Manage Multiple Systems To Achieve a Simple Goal Set a CPA target and automation finds keywords, manages bids and budgets. Try custom AdWords Scripts
  11. 11. The current state of Bid Management
  12. 12. CPC Bid A Tale of Two Kinds of Bids Demographics / RLSA Geographic Dayparting Device Modifiers
  13. 13. Matrix Bid Management Locations Devices Dayparts Audiences 1 keyword may have tens of thousands of permutations 1000 locations * 3 devices * 6 dayparts * 2 genders * 5 age ranges = 180.000 bids CPC Bid
  14. 14. How to Do Matrix Bidding Requires a very fine grained account with lots of duplication Single Keyword Campaigns (Skamps) AdWords has a 10.000 campaign limit per account You can’t do this at scale without automation Alternatively use Enhanced CPC to get the benefit of real-time auction data
  15. 15. Average Data A Common Bid Management Mistake Since Enhanced Campaigns Started Mobile Data Desktop Data Tablet Data vs
  16. 16. How to Manage Bids Correctly With Multiple Devices Desktop Bid (Your CPC bid) Mobile Bid Modifier
  17. 17. Anchored Bids Introduce Management Complexity and Dependencies Desktop Bid When the bid you are anchored to changes, modifiers must also be adjusted.
  18. 18. Anchored Bids Introduce Management Complexity and Dependencies Desktop Bid Mobile Bid Modifiers
  19. 19. Generic Static Bid OR a bid based on all device types Mobile Bid Modifier Tablet Bid Modifier Desktop Bid Modifier
  20. 20. Bidding By Weather
  21. 21. Discovering a Relevant Signal
  22. 22. Predicting Conversion Rates For Shopping Queries PREDICTIONS 1. Prediction for data: ["big and tall undershirt",0,43,1,"Style Exact","custom0=style exact and product_type_l1=t-shirts and product_type_l2=short sleeve and brand=gildan"] is 0.025902 2. Prediction for data: ["hanes sleevles tees",0,1,1,"Style Color","custom0=style color and product_type_l1=t-shirts"] is -0.000386 3. Prediction for data: ["bulk baseball sleeve shirts",0,1,1,"Style","custom0=style and product_type_l1=t-shirts and brand=anvil"] is - 0.023049 4. Prediction for data: ["big & tall t shirt green",0,1,1,"Style Exact","custom0=style exact and product_type_l1=t-shirts and product_type_l2=short sleeve and brand=gildan"] is 0.066616 5. Prediction for data: ["navy and gray raglan",0,4,1,"Style Color","custom0=style color and product_type_l1=t-shirts"] is -0.015015 6. Prediction for data: ["cuffed long sleeve shirt",0,1,1,"Style Color","custom0=style color and product_type_l1=t-shirts"] is - 0.049287 7. Prediction for data: ["big and tall mens shirts sale",1,41,2,"Style Exact","custom0=style exact and product_type_l1=t-shirts and product_type_l2=short sleeve and brand=gildan"] is 0.242856 8. Prediction for data: ["plain tees",0,19,1,"Style Exact","custom0=style exact and product_type_l1=t-shirts and product_type_l2=short sleeve and brand=gildan"] is 0.045151 9. Prediction for data: ["mens fleece quarter zip pullover",0,5,1,"Style Exact","custom0=style exact and product_type_l1=jackets"] is 0.099721http://bit.ly/PredictShoppingQueries
  23. 23. Level 4 - Intelligent Systems Manage Entire Well Defined Accounts We set parameters for several things and the system manages the account. → locations, products (i.e. business parameters) → goals (e.g. ROAS) → restrictions (e.g. only run on Google Search)
  24. 24. Level 5 - Fully Automated Connect to your business financials, write a blank check to Google and let their robots handle it.
  25. 25. Some Automation is Too Conservative
  26. 26. Humans Can Learn the Robots’ Techniques
  27. 27. Trend #2 The On-Demand Economy
  28. 28. More Freedom and Fewer Responsibilities
  29. 29. Applying Principles From the On-Demand Economy to PPC Break complex PPC management into small tasks that can be done by a freelancer
  30. 30. 30 Keyword Suggestions Example Store a set of keyword suggestions in Google Sheets where they can be reviewed by a freelancer.
  31. 31. Get Freelance Specialists to Process the Suggested Keywords
  32. 32. Expanded Text Ads How to achieve the results Google’s case studies show
  33. 33. Ads That Are Optimized Outperform ETAs “When ETAs do better, they significantly outperform legacy ads. The problem is that advertisers need time to test and tweak their new ads before they will achieve these results.” - A Google Product Manager Google pushed back the sunset date for legacy ad creation to January 2017 Analysis #1 and #2
  34. 34. Boxplots and Quartiles Analysis #1 and #2
  35. 35. Benefits of Using DKI: In Title of Any Type of Text Ad Does the use of dynamic keyword insertion boost an ad’s performance?
  36. 36. Benefits of Using DKI: In Description of Any Type of Text Ad Does the use of dynamic keyword insertion boost an ad’s performance?
  37. 37. Benefits of Using DKI: In Expanded Text Ads
  38. 38. Using Path1 and Path2 Does using the URL paths boost performance of ads?
  39. 39. Benefits of Repeating Path Text in Text of ETA How often are Path1 and Path2 used in Headline1 and Headline2 Do ads perform better when the text from the path also appears elsewhere in the ad?
  40. 40. Does Ad Text Length Matter AdWords doesn’t always show all the text we submitted in our ads. How does the length of our ad impact performance? VS.
  41. 41. Impact of Length of Headline 1 vs Headline 2
  42. 42. Mobile Preferred Expanded Ads Are you upset that mobile preferred ads are not available for Expanded Text Ads?
  43. 43. 95% Of mobile preferred ads were different from the standard ad by only a single word
  44. 44. Run Different Mobile Expanded Ads With Ad Customizers 1. Use the Ad Customizer attribute for “Device preference”: 2. Set up your ad using this new data:
  45. 45. Run Different Mobile Ads with Value Track Coming Soon! ValueTrack {ifmobile:say this} {ifnotmobile:say something else} Already available for use with the final URL Coming soon to visible parts of the ads
  46. 46. Trend #3 Artificial Intelligence
  47. 47. Quality Score - Finding Correlations in CTR Obvious correlations... Less obvious ones...
  48. 48. In our analysis, 71% of keywords with a change in QS had no change to the First Page Bid Estimate on the same day. If you use a Google Bid Strategy that depends on ‘first page bid’ or ‘top of page bid’ estimates, be careful! The Correlation between QS and FPB
  49. 49. • Going from QS 4 to 8 does NOT mean your ad rank doubles • Hence much of the published data on monetary impact is incorrect… The Quality Score You See Is Not Linear
  50. 50. If Quality Score Was Linear
  51. 51. Quality Score Is Not Linear
  52. 52. Decrease in CPC for 1 Point QS Gain Going UP from QS 5 to 6 reduces First Page Bid estimate by 37%
  53. 53. AI Assistants “It’s clear to me that we are moving from a mobile-first to an AI-first world.” –Sundar Pichai, Google
  54. 54. Alexa and Optmyzr
  55. 55. Thanks @SiliconVallaeys frederick@optmyzr.com

×