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Hero conference 2016 - advanced bidding

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Hero conference 2016 - advanced bidding

1. 1. Chris Haleua - Sr. Product Marketing Manager Advanced Bidding
2. 2. 3x3 = 9 Segments CPA Conversions 155.48 1 270.22 1 CV CE CP NV NE NP IV IE IP Cost Conversions 250 0 190 0 Impressions Position 1,100 8.9 870 7.6
3. 3. 3 1 | LAWS - Bidding Dynamics 2 | PATTERNS - Deadend Quadrants 3 | APPLICATION - Optimization Methods 4 | BALANCE - Dimensional Modeling 5 | ADVANTAGE Secret Tools Summary
4. 4. Bidding Giants George Michie Brad Geddes Sid Shah Wijnand MeierHal VarianBen Vigneron tiny.cc/wijnandtiny.cc/halvariantiny.cc/vigneron tiny.cc/michie tiny.cc/sidshahtiny.cc/geddes
5. 5. Marie Curie no fear of perfection; you'll never reach it. Nothing in life is to be feared; it is only to be understood
6. 6. Rene Descartes solved became a rule, which serve afterwards to
7. 7. Vilfredo Pareto many events, roughly 80% of the effects come from 20% of the
8. 8. Isaac Newton I have seen further than others, it is by standing upon the shoulders of giants
9. 9. Newtonian Laws AERODYNAMICS THERMODYNAMICS 1. Inertia 2. Acceleration 3. Equilibrium Transfer Entropy Absolute Zero F=ma A=0m/s2 FA=-FB -W dS 459.67° F
10. 10. Newtonian Application MOTION ENERGY 1. Inertia:Things in motion keep going 2. Acceleration: Smaller things speed up faster 3. Equilibrium: Equal & opposite reaction Transfer: Energy becomes heat & work Entropy: Nothing is 100% efficient Absolute 0: No entropy for the coldest
11. 11. Search Laws OPTIMIZATION ANALYSIS 1. Bidding Inertia 2. Learning Acceleration 3. Modifier Equilibrium Focus Transfer Volume Entropy Absolute Deadweight
12. 12. Search Application OPTIMIZATION ANALYSIS 1. Inertia no contradiction in exclusive segments 2. Acceleration assist & micro > clustering 3. Equilibrium balance volume & efficiency Transfer - filter zero, sort next best Entropy averages lie Deadweight - archive not hoard
13. 13. 13 Overcome bid inertia by reducing mass
14. 14. 14 Extra focus on the critical few
15. 15. 2 Dimensional Cartesian Plane
16. 16. 1 | LAWS - Bidding Dynamics 2 | PATTERNS - Deadend Quadrants 3 | APPLICATION - Optimization Methods 4 | BALANCE - Dimensional Modeling 5 | ADVANTAGE Secret Tools
17. 17. 3x3 Intersection 17 Conversion Success Non-Converting Spend Ignored Impressions Volume Leaders Efficiency Threats Visibility Struggles Conversions > 0 Conversions = 0 Cost > 0 Cost = 0 Impressions > 0 FILTERS Rev. (Conv.) Cost Imp. ROAS (CPA) Pos. CTR Pos. Q Score Pos. SORTS CV CE CP NV NE NP IV IE IP How are we defending our top terms? How are we avoiding waste? How are we capturing interest? How are we supporting growth? How are we balancing returns? How are we maintaining visibility? How are we qualifying prospects? How are we engaging visitors? How are we demonstrating relevance? How should we invest this extra budget? How should we project the potential? How did we grow 25% YOY in non-brand? Dead-end Quadrants
18. 18. FILTERS Volume Leaders Efficiency Threats SORTS Conversion Success Non-Converting Spend Conversions > 0 Conversions = 0 Cost > 0 Revenue ROAS CPCCost Dead-end Quadrants 18 FILTERS
19. 19. FILTERS Volume Leaders Efficiency Threats SORTS Non-Converting Spend Ignored Impressions Conversions = 0 Cost > 0 Cost = 0 Impressions > 0 CPCCost Impressions Quality Score Dead-end Quadrants 19 FILTERS Pick up where we left off
20. 20. Filter zero, then sort the next best volume to identify the critical few leaders resulting in dead-end bottlenecks
21. 21. Dead-ends  You might know your total conversions  ...but do you know the minority of kw driving the majority of \$?  You might know your efficiency threats...  ...but do you know your deadends in the step before?  You might know your loss leaders...  ...but do you know the segments & pivots that caused them?
22. 22. Keep ratios in context where their volume building blocks are the closest available signal to the bottom line Avg. Pos CTR CPC CVR ROAS ROI
23. 23. 23 1 | LAWS - Bidding Dynamics 2 | PATTERNS - Deadend Quadrants 3 | APPLICATION - Optimization Methods 4 | BALANCE - Dimensional Modeling 5 | ADVANTAGE Secret Tools
24. 24. Keyword Segments Conversion Success Non-Converting Spend Ignored Impressions
25. 25. 25 3 reports hidden in every keyword report
26. 26. Segment by Sorting & Filtering 1. Sort by conversions  Identify the first conversion zero  Filter out blank conversion data 2. Sort the rest by cost  Identify the first cost zero  Filter out blank traffic data 3. Sort the rest by Filter zero then sort by the next best metric Conversion Success Non-Converting Spend Ignored Impressions
27. 27. 3x3 Segments in Rules ROAS or CPA Cost Impressions Filter zero then sort by the next best metric Segment Metric 3x3 Att Micro Weight Path
28. 28. 3 Dimensional Cartesian Coordinates
29. 29. Conversions (Last) Conversions (First) Conversions (Assists) 3x3 to 4x3 Keyword Segments ROAS (last) / CPA (last) Cost Impressions Converting Non-Converting Ignored ROAS (first) / CPA (first) Cost Per Assist Attribution Perspectives
30. 30. Is this how your funnel feels?
31. 31. Prioritize Micro-Conversions According to the Customer Path Traffic Engagement Attribution Conversions Revenue Profit Weight micro-conversions to refine portfolio objectives
32. 32. Traffic Engagement Attribution Conversions Revenue Profit Filter zero then sort by the next best metric Brian Shindurling Use the Best Tool Available Until the Fuel is gone Blake Haleua In the absence of your preferred KPI, choose the metric closest to the bottom-line Cameron Cowan When a more precise metric is missing, fall back to the best derivative Chris Haleua Do what you can, with what you have, where you are. Theodore Roosevelt
33. 33. Beyond the 3x3 36 Conversion Success Non-Converting Spend Ignored Impressions Volume Leaders Efficiency Threats Visibility Struggles CV CE CP NV NE NP IV IE IP Above: CPA  COGS  Profit  Total On/Offline Between: Attribution Assists & Micro-Conversions Below: Long tail learning or Dead Weight Cleanup
34. 34. Conversion Distribution \$0 \$10,000 \$20,000 \$30,000 \$40,000 \$50,000 \$60,000 \$70,000 \$80,000 1 11 21 31 41 51 61 71 81 91 101 111 121 131 141 151 161 171 181 191 201 211 221 231 241 251 261 271 281 291 301 311 321 331 341 351 361 371 381 391 401 411 421 431 441 451 461 471 481 491 501 511 521 531 541 551 561 571 581 591 601 611 621 631 641 651 661 671 681 691 701 711 721 731 741 751 761 771 781 791 Revenue Pre Revenue Post
35. 35. Forecast Adjustments in Predictive Modeling 38  Massive scale  Sparse data  Time delays  Conversion paths  Complex objectives  Micro-conversion weighting 𝑀𝑎𝑥 ෍ 𝑖 𝑅𝑒𝑣𝑒𝑛𝑢𝑒 𝑏𝑖 𝑠. 𝑡. ෍ 𝑖 𝐶𝑜𝑠𝑡 𝑏𝑖 ≤ 𝐵 + 𝑏𝑢𝑠𝑖𝑛𝑒𝑠𝑠 𝑐𝑜𝑛𝑠𝑡𝑟𝑎𝑖𝑛𝑡𝑠
36. 36. Portfolio Modelling Summary Apply portfolio theory to make bid tradeoffs for maximum marginal return Maximize return for any budget through media mix modeling Build and show granular bid unit model tables for traffic & conversions Combine forecasts with dimensional algorithms for accurate simulations Build trust in forecasts through model accuracy trends by metric & day
37. 37. Simulation Yield Curve 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 Average Daily Spend Average Daily Conversions 17% 59%
38. 38. -20 -15 -10 -5 0 5 10 15 Average Cost accuracy Average of cost_accuracy_no_dow Average of cost_accuracy_w_dow
39. 39. Tough Questions to Ask 3rd Party Tools Method Optimization types available Most Popular optimization types Intraday frequency Advantage Unique differentiators Competitor threats Innovation pace Budgeting Manual overrides Spend strategies Pacing visualizations Modifiers Report segments for traffic / conversions Geo, device, time, audience manually Fully automated dimensional modeling Attribution Intra-channel Cross-channel Cross-device Objectives Position Efficiency Multiple weights Assignment Cross-engine Cross-account Execution granularity Learning Clustering Engagement / Micro-conversions Prediction accuracy
41. 41. 1 | LAWS - Bidding Dynamics 2 | PATTERNS - Deadend Quadrants 3 | APPLICATION - Optimization Methods 4 | BALANCE - Dimensional Modeling 5 | ADVANTAGE Secret Tools
42. 42. Bid Modifiers Programmatic Display Traditional SEM Enhanced Campaigns Audience Keyword Match Type [exact] +broad Bidding Geo Device Time Category Frequency
43. 43. Difficult Decisions 50 First PPC Platforms Enhanced Campaigns AdWords Facebook Ads Real-Time Bidding Shopping Campaigns Complexity
44. 44. DIMENSIONAL PORTFOLIORULES Growing Complexity KW1 KW2 Desktop Mobile SaturdayFridayThursdayWednesdayTuesdayMondaySunday SaturdayFridayThursdayWednesdayTuesdayMondaySunday Desktop Mobile SaturdayFridayThursdayWednesdayTuesdayMondaySunday SaturdayFridayThursdayWednesdayTuesdayMondaySunday KW1 KW2 KW1 KW2 PORTFOLIO
45. 45. Device
46. 46. Geo
47. 47. 54 1 | LAWS - Bidding Dynamics 2 | PATTERNS - Deadend Quadrants 3 | APPLICATION - Optimization Methods 4 | BALANCE - Dimensional Modeling 5 | ADVANTAGE Secret Tools
48. 48. FREE STUFF!  Bid Rule Playbook: tiny.cc/rule  Bid Rule Library: tiny.cc/templaterule  3x3 Template: tiny.cc/3x3template  3x3 Macro: tiny.cc/3x3macro I hear and I forget. I see and I remember. I do and I understand.
49. 49. Time Targeting Analysis Testing BiddingCoverage Structure Life IDEAL COMMON
50. 50. Why 57
51. 51. What 58
52. 52. How 59
53. 53. Key Takeaways 60 Performance Segments Matched Metrics 3x3 Pattern Micro- Conversions Attribution Perspectives Weighted Objectives Conversion Paths Excel Template Filters Saved Views Sorts Multi-Purpose Rules If Zero, Sort the Next Best Metric Look Beyond Last for Influencers Refine Portfolio Objectives Multi-Metric Simulations
54. 54. Certified Knowledge Audit Series on Bidding tiny.cc/wijnand
55. 55. QUESTIONS?