Putting the  People   Back in Paid Search Aaron Goldman CMO,  Kenshoo
Agenda <ul><li>Background </li></ul><ul><li>Challenge </li></ul><ul><li>Hypothesis </li></ul><ul><li>Methodology </li></ul...
Background <ul><li>2nd largest self-storage company in U.S.  </li></ul><ul><li>822 self-storage properties in 33 states  <...
Challenge How do you project the value of a searcher and determine what to bid for each keyword?
There is a correlation and association among specific search keywords and the value of a customer. Hypothesis
Methodology Name/Address Bid Higher Bid “ Children First” Age 24–30 Married Home owner Has kids Upper middle income Index ...
Findings <ul><li>Analyzed over 185K transactions and $16MM in revenue </li></ul><ul><li>Appended up to 1,500 demographic e...
Why It Matters <ul><li>Without understanding the  people  behind them, these keywords all look the same!  </li></ul>
<ul><li>The  people  behind the keywords represent very different Life Time Value (LTV) metrics </li></ul>Why It Matters
Why It Matters <ul><li>Find other keywords that high value  people  are searching and bid (higher) on them! </li></ul>
Why It Matters <ul><li>Customize ads to these  people! </li></ul>
<ul><li>Customize landing pages to these  people! </li></ul>Why It Matters
Why It Matters <ul><li>Target display and offline ads to these  people! </li></ul>
Thank You! [email_address]
<ul><li>70 Clusters that roll up to 21 life stage groups </li></ul><ul><li>Demographically based household-level consumer ...
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Putting the People Back in Paid Search - Aaron Goldman - ad:tech SF 2011

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Case study on how Extra Space Storage tapped Kenshoo and Acxiom to find the people behind the keywords and improve SEM while identifying insights to apply across other channels. Presented by Aaron Goldman, Kenshoo CMO, on April 12, 2011 at ad:tech San Francisco.

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  • Current Paid Search Optimization based on: Demand – Clicks, Conversions, Leads, CPA Margin – Profit, ROI, Marginal ROI Ideal Optimization based on: Lifetime Value (LTV) – Projected Future Value
  • analyze historical data (e.g., search words used, order value, customer) and find linkages of words used by individuals who generated more revenue
  • People with HDTV 6x more likely to be a customer
  • (And there would be nothing else to do but bid it up!)
  • Putting the People Back in Paid Search - Aaron Goldman - ad:tech SF 2011

    1. 1. Putting the People Back in Paid Search Aaron Goldman CMO, Kenshoo
    2. 2. Agenda <ul><li>Background </li></ul><ul><li>Challenge </li></ul><ul><li>Hypothesis </li></ul><ul><li>Methodology </li></ul><ul><li>Findings </li></ul><ul><li>Why It Matters </li></ul>
    3. 3. Background <ul><li>2nd largest self-storage company in U.S. </li></ul><ul><li>822 self-storage properties in 33 states </li></ul><ul><li>Over 510,000 units and over 55 million square feet of storage space </li></ul>
    4. 4. Challenge How do you project the value of a searcher and determine what to bid for each keyword?
    5. 5. There is a correlation and association among specific search keywords and the value of a customer. Hypothesis
    6. 6. Methodology Name/Address Bid Higher Bid “ Children First” Age 24–30 Married Home owner Has kids Upper middle income Index Value: $50 Acquisition Score $50 Purchase / Lead $21 SEM Technology
    7. 7. Findings <ul><li>Analyzed over 185K transactions and $16MM in revenue </li></ul><ul><li>Appended up to 1,500 demographic elements per individual </li></ul><ul><li>Higher income households = more stuff and greater need for storage space </li></ul><ul><li>Renters are better customers than homeowners </li></ul><ul><li>Families are better customers than singles </li></ul><ul><li>People with moderate sq. footage are better customers than those with large sq. footage </li></ul>
    8. 8. Why It Matters <ul><li>Without understanding the people behind them, these keywords all look the same! </li></ul>
    9. 9. <ul><li>The people behind the keywords represent very different Life Time Value (LTV) metrics </li></ul>Why It Matters
    10. 10. Why It Matters <ul><li>Find other keywords that high value people are searching and bid (higher) on them! </li></ul>
    11. 11. Why It Matters <ul><li>Customize ads to these people! </li></ul>
    12. 12. <ul><li>Customize landing pages to these people! </li></ul>Why It Matters
    13. 13. Why It Matters <ul><li>Target display and offline ads to these people! </li></ul>
    14. 14. Thank You! [email_address]
    15. 15. <ul><li>70 Clusters that roll up to 21 life stage groups </li></ul><ul><li>Demographically based household-level consumer segmentation powered by InfoBase-X ® </li></ul><ul><li>Life stage-based – proven predictor of consumer behavior </li></ul><ul><li>Classifies households into manageable groups more likely to respond to similar marketing messages </li></ul>Acxiom PersonicX Segments the U.S. into 70 individual clusters and 21 life stage groups

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