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#SMX #23B James Svoboda @Realicity
James Svoboda, CEO @WebRanking, Co-Founder @MnSearch
#SMX #23B James Svoboda @Realicity
RIVERS: MAIN SEGMENT & POTENTIAL, UNDEFINED INTENT
#SMX #23B James Svoboda @Realicity
WATERFALLS (and Dams): CONTROL the FLOW
#SMX #23B James Svoboda @Realicity
POOLS: IDENTIFIED, TARGETED SEGMENTS based on INTENT
#SMX #23B James Svoboda @Realicity
SELLING and MARKETING to NEEDS and INTENT
#SMX #23B James Svoboda @Realicity
KEYWORD ANCHORS {aka:DKI} for HIGHTER ATTRACTION {aka:CTR}
#SMX #23B James Svoboda @Realicity
LINER ENGAGEMENT MODEL (LEM)LINER ENGAGEMENT MODEL (LEM)
#SMX #23B James Svoboda @Realicity
ASSESS EACH POOL for SEGMENTATION & BUILD-OUT
#SMX #23B James Svoboda @Realicity
#SMX #23B James Svoboda @Realicity
KEYWORD STEM MATCHING ALGO (for each word)
#SMX #23B James Svoboda @Realicity
You’re Searching for… a PEACOCK
#SMX #23B James Svoboda @Realicity
AdWords BROAD MATCH for PEACOCK
#SMX #23B James Svoboda @Realicity
MATCHING RULES for BROAD, BMM, PHRASE & EXACT'ish
#SMX #23B James Svoboda @Realicity
KEYWORD MATCH TYPE USAGE by WORD COUNT
#SMX #23B James Svoboda @Realicity
RISK vs. OPPORTUNITY by WORD COUNT
#SMX #23B James Svoboda @Realicity
INITIAL “Confidence” BID LEVELS for MATCH TYPES
 Initial Bids Based on Expected:
– Conversion Rates
– Cost-Per-Conversion
– Profit-Per-Conversion
 Account for:
– Loose Keyword Matching
(aka Google Tax)
– Match Type Usage
– Word Count in Each Keyword
#SMX #23B James Svoboda @Realicity
SAMPLE CONFIDENCE BID LEVEL STRUCTURE
 SHIFTS SPEND :
– To Exact keywords you have greater
Confidence in.
– Away from Broad keyword pools that
are likely to map to unwanted queries
that tend to waste budget (aka the
Google Tax).
– To Longer, more segmented keyword
pools with identified intent.
– Also, maps longer search queries to
their more appropriate keywords.
#SMX #23B James Svoboda @Realicity
ADJUST STRATEGY for Conservative or Aggressive Approach
#SMX #23B James Svoboda @Realicity
ADJUST STRATEGY for RLSA
#SMX #23B James Svoboda @Realicity
WORKING WATERFALL STRUCTURE
#SMX #23B James Svoboda @Realicity
KEYWORD STEM MATCHING STRUCTURAL BUILD-OUT
#SMX #23B James Svoboda @Realicity
INSIDE “Pool” AD GROUPS
#SMX #23B James Svoboda @Realicity
CONTROLING FLOW with NEGATIVE KEYWORDS
#SMX #23B James Svoboda @Realicity
WORD STEM ANALYSIS CALCULATOR
#SMX #23B James Svoboda @Realicity
EXPADED GEOGRAPHY with CREATIVE KEYWORD TARGETING
Small GEO
HEAD KWs
Moderate GEO
KWs +michigan
Larger GEO
KWs +upper
+peninsula
Huge GEO
KWs +michigan
+upper +peninsula
*Geo-Targeting Accuracy: Country > State > City > Zip
#SMX #23B James Svoboda @Realicity
DEMOGRAPHICS TARGETING for SEARCH
 Consider and Analyze:
– Same Keywords: Different Ad Groups, Ads & LPs for Different Audiences
– Up River Head Term Targeting
#SMX #23B James Svoboda @Realicity
USE LABELS to HELP ESTABLISH ORDER & STRUCTURE
#SMX #23B James Svoboda @Realicity
TAKEAWAYS
- BMM & EXACT are a great combo
- “Word Count” Matters
- Identify Query Patterns & Pools
- Get Creative with RLSA, Geography
& Demographic Targeting
#SMX #23B James Svoboda @Realicity
IDENTIFY and TARGET SEARCHER INTENT
TARGET THIS NOT THIS
#SMX #23B James Svoboda @Realicity
THANK YOU!
download: www.webranking.com/presentation
James Svoboda
CEO WebRanking, Co-Founder MnSearch
t: @realicity
e: james.s@webranking.com
b: www.webranking.com/blog

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Rivers of Opportunity: Creating PPC Account Structures That Produce Performance Pools

  • 1. #SMX #23B James Svoboda @Realicity James Svoboda, CEO @WebRanking, Co-Founder @MnSearch
  • 2. #SMX #23B James Svoboda @Realicity RIVERS: MAIN SEGMENT & POTENTIAL, UNDEFINED INTENT
  • 3. #SMX #23B James Svoboda @Realicity WATERFALLS (and Dams): CONTROL the FLOW
  • 4. #SMX #23B James Svoboda @Realicity POOLS: IDENTIFIED, TARGETED SEGMENTS based on INTENT
  • 5. #SMX #23B James Svoboda @Realicity SELLING and MARKETING to NEEDS and INTENT
  • 6. #SMX #23B James Svoboda @Realicity KEYWORD ANCHORS {aka:DKI} for HIGHTER ATTRACTION {aka:CTR}
  • 7. #SMX #23B James Svoboda @Realicity LINER ENGAGEMENT MODEL (LEM)LINER ENGAGEMENT MODEL (LEM)
  • 8. #SMX #23B James Svoboda @Realicity ASSESS EACH POOL for SEGMENTATION & BUILD-OUT
  • 9. #SMX #23B James Svoboda @Realicity
  • 10. #SMX #23B James Svoboda @Realicity KEYWORD STEM MATCHING ALGO (for each word)
  • 11. #SMX #23B James Svoboda @Realicity You’re Searching for… a PEACOCK
  • 12. #SMX #23B James Svoboda @Realicity AdWords BROAD MATCH for PEACOCK
  • 13. #SMX #23B James Svoboda @Realicity MATCHING RULES for BROAD, BMM, PHRASE & EXACT'ish
  • 14. #SMX #23B James Svoboda @Realicity KEYWORD MATCH TYPE USAGE by WORD COUNT
  • 15. #SMX #23B James Svoboda @Realicity RISK vs. OPPORTUNITY by WORD COUNT
  • 16. #SMX #23B James Svoboda @Realicity INITIAL “Confidence” BID LEVELS for MATCH TYPES  Initial Bids Based on Expected: – Conversion Rates – Cost-Per-Conversion – Profit-Per-Conversion  Account for: – Loose Keyword Matching (aka Google Tax) – Match Type Usage – Word Count in Each Keyword
  • 17. #SMX #23B James Svoboda @Realicity SAMPLE CONFIDENCE BID LEVEL STRUCTURE  SHIFTS SPEND : – To Exact keywords you have greater Confidence in. – Away from Broad keyword pools that are likely to map to unwanted queries that tend to waste budget (aka the Google Tax). – To Longer, more segmented keyword pools with identified intent. – Also, maps longer search queries to their more appropriate keywords.
  • 18. #SMX #23B James Svoboda @Realicity ADJUST STRATEGY for Conservative or Aggressive Approach
  • 19. #SMX #23B James Svoboda @Realicity ADJUST STRATEGY for RLSA
  • 20. #SMX #23B James Svoboda @Realicity WORKING WATERFALL STRUCTURE
  • 21. #SMX #23B James Svoboda @Realicity KEYWORD STEM MATCHING STRUCTURAL BUILD-OUT
  • 22. #SMX #23B James Svoboda @Realicity INSIDE “Pool” AD GROUPS
  • 23. #SMX #23B James Svoboda @Realicity CONTROLING FLOW with NEGATIVE KEYWORDS
  • 24. #SMX #23B James Svoboda @Realicity WORD STEM ANALYSIS CALCULATOR
  • 25. #SMX #23B James Svoboda @Realicity EXPADED GEOGRAPHY with CREATIVE KEYWORD TARGETING Small GEO HEAD KWs Moderate GEO KWs +michigan Larger GEO KWs +upper +peninsula Huge GEO KWs +michigan +upper +peninsula *Geo-Targeting Accuracy: Country > State > City > Zip
  • 26. #SMX #23B James Svoboda @Realicity DEMOGRAPHICS TARGETING for SEARCH  Consider and Analyze: – Same Keywords: Different Ad Groups, Ads & LPs for Different Audiences – Up River Head Term Targeting
  • 27. #SMX #23B James Svoboda @Realicity USE LABELS to HELP ESTABLISH ORDER & STRUCTURE
  • 28. #SMX #23B James Svoboda @Realicity TAKEAWAYS - BMM & EXACT are a great combo - “Word Count” Matters - Identify Query Patterns & Pools - Get Creative with RLSA, Geography & Demographic Targeting
  • 29. #SMX #23B James Svoboda @Realicity IDENTIFY and TARGET SEARCHER INTENT TARGET THIS NOT THIS
  • 30. #SMX #23B James Svoboda @Realicity THANK YOU! download: www.webranking.com/presentation James Svoboda CEO WebRanking, Co-Founder MnSearch t: @realicity e: james.s@webranking.com b: www.webranking.com/blog