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SMX Munich 2018 - In A Nutshell: Advanced Shopping Campaigns

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In this fast-paced presentation, I ran (very quickly) through 3 businesses can use to scale their Shopping efforts more effectively. Making better bidding decisions for Shopping campaigns using a combination of these 3 approaches:

- Contextual Feeds
- Proactive RLSAs
- Search Query Sculpting (Advanced)

Thanks for having me SMX!

Veröffentlicht in: Marketing
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SMX Munich 2018 - In A Nutshell: Advanced Shopping Campaigns

  1. 1. @Digital_Liam Advanced Shopping Campaigns Making Better Bidding Decisions Liam Wade Impression
  2. 2. @Digital_Liam Who am I? ➔ Head of PPC at Impression ➔ Joined Impression in 2014 ➔ Frequent speaker at HeroConf (Voted ‘Most Actionable Talk 2017’ in London) ➔ Speaking at AdWorld Experience 2018 in April (Bologna) ➔ @Digital_Liam
  3. 3. @Digital_Liam What are we talking about? Making better bidding decisions in Shopping campaigns (either manually, automated rules, smart bidding or scripts) What do we know about this user? What are they searching for? What do we know about this product?
  4. 4. @Digital_Liam #1 Search Query Sculpting Variations on a Theme
  5. 5. @Digital_Liam Search Query Sculpting | Reminder: The Problem luxury watches rolex submariner watch silver Low-Intent Query High-Intent Query Same Bid
  6. 6. @Digital_Liam Allows you to bid on search queries, so you can be more aggressive in the auction for key queries without sacrificing traffic quality READ: Taking Google Shopping To The Next Level (2014) by Martin Roetterding @bloomarty Search Query Sculpting | Reminder: The Solution
  7. 7. @Digital_Liam - Same products in multiple campaigns - Campaigns show in priority order - Neg. KWs force away Search Query Sculpting | Reminder: The Solution CAMPAIGN PRIORITY SETTING NEGATIVE KEYWORD EXAMPLE QUERY Generic High +Rolex +Submariner “Watches” Brand Med +Submariner “Rolex Watches” Brand & Model Low - “Rolex Submariner Watches”
  8. 8. @Digital_Liam Using Modifiers
  9. 9. @Digital_Liam Specifications Search Query Sculpting | Modifiers CAMPAIGN PRIORITY NEGATIVE KEYWORDS EXAMPLE QUERY Generic High +750, +500, +litre - Measure Low - “750 litre fish tank” +750 +litre
  10. 10. @Digital_Liam Quality Signals Search Query Sculpting | Modifiers CAMPAIG N PRIORITY NEGATIVE KEYWORDS EXAMPLE QUERY Generic High +luxury, +lambswool - Quality Low - “luxury jumpers” “lambswool scarves” +luxury +lambswool
  11. 11. @Digital_Liam Automated Modifiers
  12. 12. @Digital_Liam Automatic query sculpting based on: query phrase performance Search Query Sculpting | Automation
  13. 13. @Digital_Liam Automatic query sculpting based on: query phrase performance Search Query Sculpting | Automation
  14. 14. @Digital_Liam Automatic query sculpting based on: query phrase performance Search Query Sculpting | Automation CAMPAIGN PRIORITY NEGATIVE KEYWORDS EXAMPLE QUERY Everything else High { All 2 word phrases, with a conversion rate 7%+ } - High conversion rate phrases Low - { All 2 word phrases, with a conversion rate 7%+ }
  15. 15. @Digital_Liam #2 Feed Optimisation Contextual Feeds
  16. 16. @Digital_Liam Contextual Feeds Use extra-campaign data in order to influence advertising decisions
  17. 17. @Digital_Liam Bidding strategies that don’t use context are inherently flawed. Why? Unless you do, making decisions based only on campaign data. Feed Optimisation | Contextual Performance data is reacted to with bidding Products gather data Products are submitted to Feed
  18. 18. @Digital_Liam Feed Optimisation | Contextual Custom Labels ● For the advertiser - can be whatever you'd like ● 5 slots available (CL0 to CL4) ● Limit of 1,000 unique values (you shouldn't need more than this!)
  19. 19. @Digital_Liam Contextual feeds allow you to make more informed bidding decisions by grouping products by external data
  20. 20. @Digital_Liam How do we already group products? product type brand item ID (often too granular) - Focus on Data Density
  21. 21. @Digital_Liam Feed Optimisation | Contextual Basics - Price
  22. 22. @Digital_Liam Better product data - Margin - Value AFTER Margin Feed Optimisation | Contextual Use boundaries rather than actual % value (limit on # Custom Labels)
  23. 23. @Digital_Liam Feed Optimisation | Contextual Basics - # of Sales
  24. 24. @Digital_Liam In future, new products that share these groups are given more informed starting bid Contextual feeds help us to make better bidding decisions (script / automated rules / smart bidding / manual) Feed Optimisation | Contextual Products are submitted to Feed Bidding is informed from Day 1 Products are grouped by contextual information Initial bid is set based on business context
  25. 25. @Digital_Liam Integration with other business areas - In Stock vs Drop Shipped (need to shift!) Feed Optimisation | Contextual vs
  26. 26. @Digital_Liam Feed Optimisation | Contextual Calculated data sources | Coverage (Size) - What size are they? - How do we answer this? Hint: we can’t!
  27. 27. @Digital_Liam Feed Optimisation | Contextual Calculated data sources | Coverage (Size) But we can anticipate conversion rates!
  28. 28. @Digital_Liam Calculated data sources | Coverage (Model) Feed Optimisation | Contextual What % of the full range of this brands products do we have on site? Eg. “Less than 20” = We stock less than 20% of this brand’s products
  29. 29. @Digital_Liam #3 Proactive RLSA Qualifying Traffic
  30. 30. @Digital_Liam “All Non-Converting Users” - Past 30 Days “Cart Abandoners” - Past 14 Days Typical Usage Of RLSA In Shopping
  31. 31. @Digital_Liam Stop viewing RLSAs as a supplement to your Shopping campaigns. Use other channels to build qualified audiences for your campaigns
  32. 32. @Digital_Liam Broader queries can profitable, for the right user BEFORE AFTER Proactive RLSA | Qualifying Users ??? +RLSA
  33. 33. @Digital_Liam Targeted Audience We know which price point this person is likely to purchase at - Proactively seeking your audience, before you push your product Proactive RLSA | Qualifying Users Targeted to Women That Already Like Competitors
  34. 34. @Digital_Liam Occupational audiences (Can also use Facebook / Twitter; less targeted for B2B but a lot cheaper) Job title: Office Managers Company size: 500+ Employees Proactive RLSA | Qualifying B2B Users +RLSA
  35. 35. @Digital_Liam Using all 3 to make a bidding decision
  36. 36. @Digital_Liam Using all 3 to make a bidding decision Search Query Sculpting Proactive RLSA ??? This user has never clicked on our ads ??? Only used generic terms ??? We only have 6% of sizes in stock Contextual Feed Data
  37. 37. @Digital_Liam Using all 3 to make a bidding decision Search Query Sculpting Proactive RLSA User is a “football fan” and has engaged with us User specified colour “Burgundy” We have the entire range of sizes in stock Contextual Feed Data
  38. 38. @Digital_Liam Using all 3 to make a bidding decision Search Query Sculpting Proactive RLSA What do we know about this user? What are they searching for? What do we know about this product? Contextual Feed Data
  39. 39. @Digital_Liam Thank You Liam Wade Impression @Digital_Liam

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