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Attribution-fu: Using Correlation Data to Track Marketing Attribution
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Attribution-fu: Using Correlation Data to Track Marketing Attribution

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Marketing has become extremely data-driven. I don't love it, but we need to go with it. That means finding more and better ways to track attribution across channels. This slide deck explains some …

Marketing has become extremely data-driven. I don't love it, but we need to go with it. That means finding more and better ways to track attribution across channels. This slide deck explains some basic techniques - Pearson Correlation and holdout testing - that you can use to connect channel performance to business KPIs.

Published in: Marketing, Business, Technology

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  • 1. BECAUSE MATH DIPPING YOUR TOE IN THE WATER W/ CORRELATION Ian Lurie @portentint ian@portent.com #PORTENTU
  • 2. portent.com portent.co/bccorrel
  • 3. HOW THIS WILL GO Disclaimers Use cases & despair Principles 2 ways to test We all collapse
  • 4. THE LINK BUNDLE portent.co/bccorrel
  • 5. DON’T BELIEVE A WORD I SAY
  • 6. MY MATH QUALIFICATIONS A degree in history A JD C- in Calculus No statistics training at all
  • 7. I’VE MADE MISTAKES
  • 8. LUCKY FOR YOU, I’VE HAD SOME GREAT TEACHERS
  • 9. aNNIE CUSHING kevin hillstrom pete meyers avinash kaushik john caples
  • 10. WHAT I WON’T DISCUSS learn the rules before you use the tools GOOGLE ANALYTICS R LANGUAGE TABLEAU SOFTWARE OTHER FANCY STUFF LOVE IT ALL. BUT let's STICK TO TOOLS WE ALL KNOW AND HAVE, NO MATTER what
  • 11. HOW DO WE KNOW IF THIS IS WORKING? WE CAN'T TRACK IT. THOSE ARE CALL CENTER LEADS. INTERNET MARKETING HAD NOTHING TO DO WITH IT. WE’VE ALL KNOWN DESPAIR I WANT TO STOP THE CONTENT CAMPAIGN. IT'S NOT EARNING ANY MONEY. I'M AFRAID THE WEB IS JUST CANNIBALIZING DIRECT MAIL. DON'T BUY PPC FOR OUR NAME. WE ALREADY RANK #1. IT'S A WASTE OF SOCIAL MEDIA MONEY. DOESN'T CONVERT.
  • 12. WE’VE ALL KNOWN DESPAIR gaaaah i can't take it. attribution?!!!! hahahahahah i'll attribute my sanity to finding a job at a bicycle shop bwahahahahahahaha
  • 13. CORRELATION IS YOUR FRIEND Car Speed Car top speed vs. age of American Male 180 160 140 120 100 80 60 40 20 0 CLEAR CORRELATION 30 35 40 45 50 Age 55 60 65 70
  • 14. CORRELATION IS YOUR FRIEND WORST ENEMY Car Speed Car top speed vs. age of American Male 180 160 140 120 100 80 60 40 20 0 BUT… WHY? 30 35 40 45 50 Age 55 60 65 70
  • 15. CORRELATION IS YOUR FRIEND WORST ENEMY MIDDLE-AGED AMERICAN MEN ARE COMPENSATING FOR SOMETHING OR ALL AMERICAN MEN LIKE TOYS, AND CAN AFFORD THEM AT MIDDLE AGE
  • 16. LATE-NIGHT SNACKING MAKES YOU FAT WRONG Late night snacks vs. weight gain 50 Weight gain (lbs) 40 30 20 10 0 0 2 4 6 Snacks/week 8 10
  • 17. WHY IS IT WRONG? THERE IS NO CAUSAL LINK. OR, AS STATISTICIANS LIKE TO SAY…
  • 18. correlation does not equal causation ...but i wouldn't worry about that too much.
  • 19. (WE LOVE YOU, MATT)
  • 20. WE CAN MAKE THIS WORK BY USING EXCEL/GDOCS USING OUR KNOWLEDGE GETTING A BIT GEEKY TESTING ASSUMPTIONS
  • 21. EXAMPLE 1 our e-mail list? make it a low priority. it doesn't sell much anyway.
  • 22. A HOLDOUT TEST!!! TEST ONE CHANNEL’S IMPACT ON OTHERS
  • 23. A HOLDOUT TEST!!! SEGMENT YOUR AUDIENCE 5%/5%/90%
  • 24. A HOLDOUT TEST!!! 5% GETS THE USUAL
  • 25. A HOLDOUT TEST!!! 5% GETS NOTHING FROM THE CHANNEL BEING TESTED
  • 26. A HOLDOUT TEST!!! THE RESULT GIVES YOU INSIGHT INTO CROSSCHANNEL IMPACT
  • 27. OVERALL RESULT (all channels) Average revenue value generated from all channels of a single address List Size Total sales Revenue/address Total 400,000 $250,000.00 $0.63 Held out 20,000 $5,000.00 $0.25 E-mailed 20,000 $12,000.00 $0.60 Revenue from all channels for each segment
  • 28. OVERALL RESULT (all channels) E-mail caused these customers to buy more, no matter where they came from. Organic Search PPC Social E-mail Total $0.20 $1.25 $0.11 $0.63 Held out $0.17 $0.90 $0.02 $0.25 E-mailed $0.21 $1.24 $0.13 $0.60 Ah HA! Held out segment generated less value from other channels, too.
  • 29. OVERALL RESULT (all channels) Now you estimate impact by channel. Organic Search PPC Social E-mail Total $0.20 $1.25 $0.11 $0.63 Held out $0.17 $0.90 $0.02 $0.25 E-mailed $0.21 $1.24 $0.13 $0.60 E-mail appears to boost PPC revenue/customer 39%
  • 30. EXAMPLE 2 SOCIAL MEDIA SUCKS. LET'S STOP. FOREVER.
  • 31. UH-OH THIS IS ABOUT EXISTING & NEW CUSTOMER ACQUISITION.
  • 32. UH-OH HOW DO WE TRACK LIFT IN NEW CUSTOMER ACQUISITION?!
  • 33. OPTION 1 TURN OFF ONE CHANNEL. MEASURE CHANGE IN THE OTHERS.
  • 34. GENERALLY UNPOPULAR SHIIIIIIIIIIIII
  • 35. OPTION 2 BOOST SPEND ON ONE CHANNEL. MEASURE IMPACT ON OTHERS.
  • 36. ALSO UNPOPULAR PLUS, LOTS OF NOISE. YOU PROBABLY CAN’T BOOST SPEND 300%. SHIIIIIIIIIIIII
  • 37. OPTION 3 IAN’S SEAT-OF-THE-PANTS CORRELATION METHOD
  • 38. USE AT YOUR OWN RISK. MAY CAUSE
  • 39. WHAT YOU NEED A LOT OF DATA CLEAN DATA ANALYTICS THAT WORK INTERNAL SALES DATA (NOT JUST WEB) AN OPEN MIND
  • 40. WHAT YOU NEED COMMON SENSE
  • 41. STEP 1: GET YOUR DATA YOU MUST HAVE OVERALL SALES!!!!
  • 42. STEP 2: IMPORT IT
  • 43. STEP 3: CREATE SCATTERPLOT THIS TESTS WHETHER YOU HAVE A CHANCE
  • 44. SELECT 2 COLUMNS CMD+SHIFT OR CTRL+SHIFT
  • 45. WHICH COLUMNS? HERE, WE’RE CHECKING FOR CONNECTIONS BETWEEN SOCIAL MEDIA ACTIVITY AND REVENUE, SO I’M STARTING WITH ONE SOCIAL MEDIA METRIC AND OVERALL REVENUE
  • 46. CLICK
  • 47. CHECK THIS BOX
  • 48. IN GENERAL STEEPER UP-AND-TO-THE-RIGHT = TIGHTER CORRELATION R SQUARED CLOSER TO 1 =TIGHTER CORRELATION
  • 49. BUT REMEMBER… I WAS A HISTORY MAJOR.
  • 50. HMMMM Overall Rev 30,000.00 Revenue (USD) 25,000.00 20,000.00 R² = 0.40636 15,000.00 LOW R SQUARED= LOW 10,000.00 CORRELATION = LOWHMMM. MIGHT BE A CHANCES THESE ARECONNECTION 5,000.00 CONNECTED - 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Visits from Social Media
  • 51. HMMMM Revenue (USD) PPC Rev $20,000.00 $18,000.00 $16,000.00 $14,000.00 $12,000.00 R² = 0.81774 $10,000.00 $8,000.00 LOW R SQUARED= LOW CORRELATION = LOWHMMM. MIGHT BE A $6,000.00 CHANCES THESE ARECONNECTION $4,000.00 CONNECTED $2,000.00 $1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Visits from Social Media
  • 52. HMMMM Overall Rev 30,000.00 R² = 0.30871 REVENUE 25,000.00 20,000.00 15,000.00 10,000.00 WEAKER RELATIONSHIP BETWEEN OVERALL REVENUE AND SHARES 5,000.00 - 20 40 60 80 SHARES 100 120 140
  • 53. HMMMM REEVNUE (USD) E-mail Rev vs. Social Unique Visits $10,000.00 $9,000.00 $8,000.00 $7,000.00 $6,000.00 $5,000.00 $4,000.00 $3,000.00 $2,000.00 $1,000.00 $- SOCIAL MAY CANNABILIZE E-MAIL R² = 0.04969 - 500 1,000 1,500 SOCIAL UNIQUE VISITS 2,000 2,500
  • 54. STEP 4: USE CORRELATION NUMBERS, TO QUANTIFY THE PLOTS
  • 55. TYPE THIS FORMULA INTO A CELL: =CORREL(RANGE, RANGE2)
  • 56. IN MY EXAMPLE: =CORREL(D2:D363, K2:K363)
  • 57. CLOSER TO 1 = STRONG CORRELATION
  • 58. MY RESULT:
  • 59. MY RESULT: DANG
  • 60. MY RESULT: HOLY @)(*!@#
  • 61. correlation does not equal causation
  • 62. HMMM. A GOOD POINT.
  • 63. STEP 5: APPLY COMMON SENSE REMEMBER OUR SCATTERPLOT OF SOCIAL SHARES VS. OVERALL REVENUE?
  • 64. IT’S A PRETTY GOOD ‘FIT’ Overall Rev 30,000.00 R² = 0.30871 REVENUE 25,000.00 20,000.00 REMEMBER OUR 15,000.00 SCATTERPLOT OF 10,000.00 SOCIAL UNIQUES VS. 5,000.00 OVERALL REVENUE? - 20 40 60 80 SHARES 100 120 140
  • 65. NOT THE STRONGEST, BUT SOMETHING’S GOING ON THERE.
  • 66. (NO, THE NUMBERS DON’T MATCH UP. JUST SAMPLE DATA. PLUS: HISTORY MAJOR)
  • 67. MORE COMMON SENSE KNOWING WHAT I’VE DONE IN SOCIAL MEDIA RECENTLY HELPS, TOO. WE HAVEN’T CHANGED A THING. BUT STILL, THIS CORRELATION.
  • 68. MORE COMMON SENSE WE RAN A PROMO, THOUGH, VIA E-MAIL. THAT MIGHT CREATE ‘NOISE.’
  • 69. MORE COMMON SENSE SO WE DO THE MATH
  • 70. MORE COMMON SENSE THAT MAY MEAN THE E-MAIL PROMO LOOSENED THE RELATIONSHIP BETWEEN EMAIL AND SOCIAL. SO WE RUN ANOTHER CORRELATION EXCLUDING THE DAYS OF THE PROMO.
  • 71. MORE COMMON SENSE THERE’S PROBABLY CANNIBALIZATION GOING ON.
  • 72. THE RESULT YOU CAN AT LEAST DEMONSTRATE THERE’S A STRONG CONNECTION BETWEEN REVENUE AND SOCIAL, EVEN IF SOCIAL DOESN’T DIRECTLY GENERATE THAT REVENUE.
  • 73. NEXT STEP? DO A HOLDOUT TEST (COUGH) – STOP POSTING FOR 2 WEEKS. TRY TO REALLY SPIKE SOCIAL MEDIA ACTIVITY AND SEE HOW THAT IMPACTS OVERALL REVENUE.
  • 74. CAUTION DON’T TRY TO ‘FIT’ THE DATA TO YOUR EXPECTATIONS IF COMMON SENSE <> THE DATA, GO WITH COMMON SENSE UNTIL PROVEN OTHERWISE
  • 75. CAUTION REALLY LEARN THIS STUFF
  • 76. QUESTIONS? IAN@PORTENT.COM @PORTENTINT WWW.PORTENT.COM portent.co/bccorrel
  • 77. NEXT MONTH MICHAEL WEIGAND NEXT-LEVEL SEGMENTATION DIVIDE & CONQUER FEBRUARY 27 TH 11 AM PACIFIC