Using Account Level Buying Signals & Predictive Analytics To Score Leads
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Using Account Level Buying Signals & Predictive Analytics To Score Leads
- 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!!
- 12. #C2C14! 35%
- 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!