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Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
Using Account Level Buying Signals & Predictive Analytics To Score Leads
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Using Account Level Buying Signals & Predictive Analytics To Score Leads

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  • 1. PRESENTED BY! #C2C14! Using Account-Level Buying Signals and Predictive Analytics to Score Leads! Brian Kardon! CMO! Lattice Engines!
  • 2. #C2C14!
  • 3. #C2C14! Stock price: from $13 to $35!Forrester  stock  went  from  $13  to  $34  per  share  
  • 4. #C2C14!
  • 5. #C2C14! About Brian Kardon …! ! CMO ! CMO! CMO ! CMO ! Partner ! ! @bkardon! 5  
  • 6. #C2C14! From  Art  to  Science  …   Tradi<onal  Marke<ng   “Modern”  Marke<ng”   “Predic<ve”  Marke<ng  and  Selling  
  • 7. #C2C14! Doing all the right things …! §  Marke<ng  automa<on   §  Sales  force  automa<on   §  Lead  nurturing   §  Lead  scoring   §  Personas   §  SLAs  in  place   §  Great  marke<ng  team   §  Awesome  Sales  team   94%  of  your   Marke<ng-­‐Qualified  Leads   (MQLs)   will  never  close  
  • 8. #C2C14! What’s wrong here?! §  94% of all Marketing Qualified Leads will never close1! ! §  52% of sales reps in US did not make quota last year2! ! §  Sales reps spend 68% of their time on administration and preparation, not speaking with customers3! ______________________________________   Source:  1  Sirius  Decisions;  2  CSO  Insights;    3  IDC  
  • 9. What is the pattern?! Then! Radio! Cable TV! Taxi! Bookstore! Hotels! Thermostat! Now! Pandora! Netflix! Uber! Amazon! Airbnb! Nest!
  • 10. #C2C14! §  Purchases! §  Items you have added to cart, but abandoned! §  “Dwell” times! §  Product ratings ! §  Address! §  What your neighbors buy! §  Birthday! §  Sizes: yours + family + friends! §  If you are cheating on your partner!!
  • 11. #C2C14! $4.95 In Stock
  • 12. #C2C14! 35%  
  • 13. #C2C14!Proprietary  &  Confiden<al   13  
  • 14. #C2C14!Proprietary  &  Confiden<al   14  
  • 15. #C2C14! Source! Selected  A,ributes! Marke<ng  Automa<on! Contact  name,  <tle,  company,  open  rates,  unsubscribes,  web   visits,  pages  visited,  lead  score,  video  views,  downloads" CRM  System! Company,  contact  informa<on,  win/loss,  deal  value" Product  Usage  Logs! Features  used,  logins,  session  length,  collabora<on" Purchase  History! Products  purchased,  prices  paid,  discounts,  contract  terms" Customer  Support  History! Complains,  resolu<ons" Public  Websites! Job  pos<ngs,  grants,  li<ga<on,  patents,  contracts,  loca<ons.   growth" Company  Websites! Language(s),  products,  shopping  cart,  execu<ve  team  profiles" Social  Websites! Company  and  personal  profiles,  likes,  comments,  updates,   friends/connec<ons/followers,  usage" Media! News  ar<cles  and  stories,  product  launches,  announcements,   press  releases,  li<ga<on" Private  Databases! Credit  ra<ngs,  financial  history,  construc<on  permits/starts,   deployed  technologies"
  • 16. #C2C14! 16  Proprietary  &  Confiden<al   Algorithmic  trading  has  replaced  human  trading.      
  • 17. #C2C14! 17  Proprietary  &  Confiden<al   Who  is  the  Jeopardy  player  in  the  middle?  
  • 18. #C2C14!
  • 19. #C2C14! What is a predictive attribute?!
  • 20. #C2C14!
  • 21. #C2C14! Finding the Trigger …! Category   Predic5ve  Trigger   Likelihood  to   Convert  from   MQL  to  SQL   Foreign  Exchange  Services   New  office  opened  overseas   5x   Switches  &  Routers   New  lease  is  signed   3x   Marke5ng  SoFware   Spike  in  social  media  ac<vity   3x   Financial  SoFware   New  CFO  hired  who  previously   bought  from  you   8x  
  • 22. 0%   5%   10%   15%   20%   25%   30%   35%   40%   0   1,000   2,000   3,000   4,000   5,000   6,000   7,000   Purchase  Probability   Accounts   Average    20%      40%      60%      80%      100%     Predic5ve  Targe5ng      0%     22" Business   Banking   Example  
  • 23. 0%   5%   10%   15%   20%   25%   30%   35%   40%   0   1,000   2,000   3,000   4,000   5,000   6,000   7,000   Purchase  Probability   Accounts   Predicted   Average   Predic5ve  Targe5ng   Accounts  Likely  to  Have    Specific  Financial  Service  Need  in  Next  90  Days    20%      40%      60%      80%      100%      0%     Highest  Probability   Segment   23"
  • 24. 0%   5%   10%   15%   20%   25%   30%   35%   40%   0   1,000   2,000   3,000   4,000   5,000   6,000   7,000   Purchase  Probability   Accounts   Predicted   Average   Predic5ve  Targe5ng      20%      40%      60%      80%      100%      0%     Companies  with  the  following  condi5ons…     "   Balance  of  Trade  Change   Business  has  experienced  >100%  increase  in  balance  of   trade  with  Canada,  China  or  Mexico  in  the  past  30  days     "   Recent  Hire  of  Finance  Execu5ve   Business  has  hired  a  Chief  Financial  Officer  or  senior   controller  within  the  past  ninety  (90)  days     "   >30%  Increase  in  Search  Adver5sing  in  the  past  30  days     "   Recent  Expansion  in  Hiring  &  Recrui5ng   24"
  • 25. 0%   5%   10%   15%   20%   25%   30%   35%   40%   0   1,000   2,000   3,000   4,000   5,000   6,000   7,000   Purchase  Probability   Accounts   Predicted   Average   Different  Contact  Strategy  by  Segment    20%      40%      60%      80%      100%      0%     Engage  via  Front-­‐ Line  Bankers   Mid-­‐stage   Nurture   25"
  • 26. #C2C14! Where is Marketing Automation? Cumula5ve   Adop5on   Time   A B C D E F 50-70% penetration Source: Sirius Decisions Where  is  marke5ng  automa5on?  
  • 27. #C2C14! Where is Predictive Marketing and Selling? Cumula5ve   Adop5on   Time   A B C D E F Source: Lattice Engines Where  is  predic5ve  lead  scoring?  
  • 28. #C2C14! Predictive Analytics for Marketing! §  The era of big data and predictive analytics is NOW! ! §  There is more information to discover about a prospect than ever before – at the account level! ! §  Leading marketing organizations are embracing predictive analytics to dramatically improve performance! ! §  Marketing can do more – from lead scoring to predictive lead scoring! ! §  Find your trigger … target selectively and quickly!
  • 29. #C2C14!
  • 30. #C2C14! Thank you!! Brian Kardon! CMO, Lattice Engines! ! bkardon@lattice-engines.com! ! @bkardon!

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