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PARADOX OF BIG DATA AND
PREDICITIVE MODELING
@claudia_perlich
@dstillery
What AI can and cannot teach us about ourselves ....
ATTENTION DURING SUPER BOWL
@claudia_perlich
@dstillery
Attention
HOW DO I KNOW? @claudia_perlich
@dstillery
@claudia_perlich
@dstillery
Work
with Brand
300 Million (US) consumer
100 Billion
bid requests per day
Ad
Exchange
Measure...
@claudia_perlich
@dstillery
Attention
ATTENTION = DIVERTED EYEBALLS
@claudia_perlich
@dstillery
Bid reduction compared to ...
@claudia_perlich
@dstillery
Measure
Design
Messaging
‘Optimize’
Audience
Typical Use of Programmatic
Third Party
Measureme...
@claudia_perlich
@dstillery
@claudia_perlich
@dstillery
I will try to look good in your chosen metric
MEASUREMENT = AUDIENCE
@claudia_perlich
@dstillery
IoT Device
VALUE OF PROGRAMMATIC DATA
100 Billion Events per Day
@claudia_perlich
@dstillery
buzzfeed.com
3/20/16
Predicting events on pretty much everything
amazon.com
4/11/16
nytimes.co...
@claudia_perlich
@dstillery
buzzfeed.com
3/20/16
Predicting events on pretty much everything
amazon.com
4/11/16
nytimes.co...
@claudia_perlich
@dstillery
@claudia_perlich
@dstillery
SCORINGCONNECT
CAMPAIGN PROGRESS
Conversion
+
+
+
+
No Longer
in Market
XX
Add to
Prospect Poo...
@claudia_perlich
@dstillery
0
5
10
15
20
25
0
1.0M
2.0M
3.0M
4.0M
5.0M
6.0M
NNLiftoverRON
TotalImpressions
median lift = 5...
@claudia_perlich
@dstillery
TAKE A LOOK AT THE DARK SIDE
@claudia_perlich
@dstillery
GOOD PREDICTION ARE HARMFUL FOR BAD METRICS
@claudia_perlich
@dstillery
6%
2011
36%
2015
NON-HUMAN TRAFFIC
@claudia_perlich
@dstillery
PERVASICE FRAUD ON CONVERSIONS
@claudia_perlich
@dstillery
CLICKS
@claudia_perlich
@dstillery
PEOPLE FUMBLE IN THE DARK
@claudia_perlich
@dstillery
CLICK OPTIMIZATION?
@claudia_perlich
@dstillery
A/B TEST: CLOSE TO NO IMPACT …
@claudia_perlich
@dstillery
Measure
Design
Messaging
‘Optimize’
Audience
Typical Use of Programmatic
Third Party
Measureme...
@claudia_perlich
@dstillery
Measure
Design
Messaging
‘Optimize’
Audience
Typical Use of Programmatic
Third Party
Measureme...
@claudia_perlich
@dstillery 25
LET’S TALK ABOUT A POTATO
@claudia_perlich
@dstillery 26
THE REACTIONS
@claudia_perlich
@dstillery
THE CULPRIT
@claudia_perlich
@dstillery 28
THE ‘LESSONS’
@claudia_perlich
@dstillery 29
THE ‘LESSONS’
@claudia_perlich
@dstillery 30
THE ‘LESSONS’
@claudia_perlich
@dstillery 31
THE ‘LESSONS’
RETHINKING PROGRAMMATIC
From Media Execution To Understanding
33
Experiment &
Measure
Design
Messaging
Understand
Audience
Through AI in
Programmatic
New Programmatic: Large Scale Digi...
34
YOUR BUZZWORDS HERE ...
AI, Big Data, Machine Learning
How are things different? Which things are similar?
WHAT MAKES THEM SPECIAL!
YOU CANNOT ASK COOKIES QUESTIONS,
BUT THEY DO NOT HIDE MUCH …
IoT Device
@claudia_perlich
@dstillery 37
SUPERVISED LEARNING
What makes YOUR
customers special?
LEARNING WHAT MAKES PEOPLE SPECIAL?
SAME PROBLEM AS AUDIENCE OPTIMIZATION …
People of interest Everybody else
@claudia_perlich
@dstillery
CASE:
BAUME ET MERCIER
To identify an Baume
audience, we identified all the
devices visiting v...
@claudia_perlich
@dstillery
OVERALL AUDIENCE PROFILE
A machine-learning algorithm learned to
predict who will go to the Ba...
@claudia_perlich
@dstillery
Large Jewish Community which views
Baume et Mercier as the celebration brand.
@claudia_perlich...
@claudia_perlich
@dstillery
Insight 2 : Family Car
Land Rover, Range Rover, and more family-
oriented cars are at the top ...
@claudia_perlich
@dstillery
Insight 3 : Maternity Shopping
Maternity and children’s stores - A Pea in the Pod,
Motherhood ...
@claudia_perlich
@dstillery
Insight 4 : Causes
Majority of support toward fighting poverty both in
US and the World.
@clau...
@claudia_perlich
@dstillery
Insight 5 : Sports
Strong Anglo-European Influence:
Soccer & Rugby
@claudia_perlich
@dstillery
@claudia_perlich
@dstillery 46
UNSUPERVISED LEARNING
Are there natural
groups (segments)?
@claudia_perlich
@dstillery
SEGMENTATION = PERSONAS
IoT Device
@claudia_perlich
@dstillery
CASE : NON-DAIRY MILK
MARKET ENTRY
With a new launch in the U.S.,
the brand was looking to
val...
@claudia_perlich
@dstillery
Top Web Visits
www.minimalistbaker.com
www.bobsredmill.com
www.eater.com
www.pcrm.org
www.whol...
4 unique subpopulations emerged from the algorithm. 3 were
manually filtered as they depicted non-US and industry visitor
...
MARKETING PROFESSIONALS
@claudia_perlich
@dstillery
Top Web Visits
www.brand-innovators.com
www.mindsparklemag.com
www.b2b...
The Health Nut
Subpopulation 2
18.8%
The Trendsetter
Subpopulation 5
23.1%
The Curator
Subpopulation 6
17.6%
The Maker
Sub...
Top Web Visits
www.veralistcenter.org
www.twentieth.net
www.india-mahdavi.com
www.cityreliquary.org
www.storefrontnews.org...
Top Web Visits
www.loupcharmant.com
www.maraisusa.com
www.apieceapart.com
www.capbeauty.com
www.saladforpresident.com
www....
Vegan recipe blog
Nutrition blog
Vegan recipe blog
Vegan recipe blog
Vegan recipe blog
Vegan recipe blog
Recipe blog
Vegan...
We drilled down further to find micro-
audiences within this subpopulation
Even Deeper
Drilling into Health Nuts
@claudia_...
Micro-Audience A (4.9%)
www.hilaryseatwell.com
www.eatrightstore.org
www.oregonswildharvest.com
www.kite-hill.com
www.ift....
Micro-Audience B (6.3%)
www.elephantasticvegan.com
www.veggiesdontbite.com
www.cearaskitchen.com
www.thecolorfulkitchen.co...
Micro-Audience C (7.6%)
www.kaleandcaramel.com
www.3-chairs.com
www.sproutedkitchen.com
www.spiritbeautylounge.com
www.rac...
4 unique subpopulations emerged from the algorithm. 3 were
manually filtered as they depicted non-US and industry visitor
...
61
CASE :
CHOBANI
@claudia_perlich
@dstillery
62
Linking store purchase to digital activity
Loyalty Cards
Linking Store Purchase to Digital ActivityCONNECTING DIGITAL A...
How do images impact people who visit fast food?
1.00
1.10
1.20
1.30
1.40
1.50
1.60
1.70
Chipotle Mcdonalds Subway Chick-f...
How do images impact people in food segments?
1.00
1.05
1.10
1.15
1.20
1.25
1.30
1.35
1.40
1.45
Produce-44079 Beverages >
...
@claudia_perlich
@dstillery
QUESTIONS?
Contact:
@claudia_perlich
@dstillery
915 e metrics_claudia perlich
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915 e metrics_claudia perlich

  1. 1. PARADOX OF BIG DATA AND PREDICITIVE MODELING @claudia_perlich @dstillery What AI can and cannot teach us about ourselves ...
  2. 2. ATTENTION DURING SUPER BOWL @claudia_perlich @dstillery
  3. 3. Attention HOW DO I KNOW? @claudia_perlich @dstillery
  4. 4. @claudia_perlich @dstillery Work with Brand 300 Million (US) consumer 100 Billion bid requests per day Ad Exchange Measurement Conversion PROGRAMMATIC
  5. 5. @claudia_perlich @dstillery Attention ATTENTION = DIVERTED EYEBALLS @claudia_perlich @dstillery Bid reduction compared to weekend before
  6. 6. @claudia_perlich @dstillery Measure Design Messaging ‘Optimize’ Audience Typical Use of Programmatic Third Party Measurement ‘Optimizing’ Audience Creative Design TYPICAL USE OF PROGRAMMATIC: Efficient Media Delivery
  7. 7. @claudia_perlich @dstillery
  8. 8. @claudia_perlich @dstillery I will try to look good in your chosen metric MEASUREMENT = AUDIENCE
  9. 9. @claudia_perlich @dstillery IoT Device VALUE OF PROGRAMMATIC DATA 100 Billion Events per Day
  10. 10. @claudia_perlich @dstillery buzzfeed.com 3/20/16 Predicting events on pretty much everything amazon.com 4/11/16 nytimes.com 2/15/16 50.240.135.41 166. 216.165.92 207.246.152.60 108.49.133.218 38.104.253.134 208.76.113.13 Mlb.com 3/15/16 Etrade.com 4/25/16 Zip 4 10023-4592 04/15/16 Zip 4 10023-6924 04/20/16 Zip 4 10016-2324 03/10/16 03/14/16 Web App Phone/Tablet Desktop Phone/Tablet com.mlb.atbat 04/20/16 com.rovio.angry 02/26/16 com.myfitnesspal.android 3/25/16 4/18/16 IDFA 31AB-26FC- 94AE-756B azure.microsoft.com 4/10/16 PREDICTING BRAND EVENTS ON EVERYTHING
  11. 11. @claudia_perlich @dstillery buzzfeed.com 3/20/16 Predicting events on pretty much everything amazon.com 4/11/16 nytimes.com 2/15/16 50.240.135.41 166. 216.165.92 207.246.152.60 108.49.133.218 38.104.253.134 208.76.113.13 Mlb.com 3/15/16 Etrade.com 4/25/16 Zip 4 10023-4592 04/15/16 Zip 4 10023-6924 04/20/16 Zip 4 10016-2324 03/10/16 03/14/16 Web App Phone/Tablet Desktop Phone/Tablet com.mlb.atbat 04/20/16 com.rovio.angry 02/26/16 com.myfitnesspal.android 3/25/16 4/18/16 IDFA 31AB-26FC- 94AE-756B azure.microsoft.com 4/10/16 PREDICTING BRAND EVENTS ON EVERYTHING
  12. 12. @claudia_perlich @dstillery
  13. 13. @claudia_perlich @dstillery SCORINGCONNECT CAMPAIGN PROGRESS Conversion + + + + No Longer in Market XX Add to Prospect Pool and Serve Ad + + - - + + DELIVER MEDIA = HIGH PREDICTIONS
  14. 14. @claudia_perlich @dstillery 0 5 10 15 20 25 0 1.0M 2.0M 3.0M 4.0M 5.0M 6.0M NNLiftoverRON TotalImpressions median lift = 5x Liftoverbaseline <snip> NICE LIFT
  15. 15. @claudia_perlich @dstillery TAKE A LOOK AT THE DARK SIDE
  16. 16. @claudia_perlich @dstillery GOOD PREDICTION ARE HARMFUL FOR BAD METRICS
  17. 17. @claudia_perlich @dstillery 6% 2011 36% 2015 NON-HUMAN TRAFFIC
  18. 18. @claudia_perlich @dstillery PERVASICE FRAUD ON CONVERSIONS
  19. 19. @claudia_perlich @dstillery CLICKS
  20. 20. @claudia_perlich @dstillery PEOPLE FUMBLE IN THE DARK
  21. 21. @claudia_perlich @dstillery CLICK OPTIMIZATION?
  22. 22. @claudia_perlich @dstillery A/B TEST: CLOSE TO NO IMPACT …
  23. 23. @claudia_perlich @dstillery Measure Design Messaging ‘Optimize’ Audience Typical Use of Programmatic Third Party Measurement ‘Optimizing’ Audience Creative Design TYPICAL USE OF PROGRAMMATIC:
  24. 24. @claudia_perlich @dstillery Measure Design Messaging ‘Optimize’ Audience Typical Use of Programmatic Third Party Measurement ‘Optimizing’ Audience Creative Design TYPICAL USE OF PROGRAMMATIC:
  25. 25. @claudia_perlich @dstillery 25 LET’S TALK ABOUT A POTATO
  26. 26. @claudia_perlich @dstillery 26 THE REACTIONS
  27. 27. @claudia_perlich @dstillery THE CULPRIT
  28. 28. @claudia_perlich @dstillery 28 THE ‘LESSONS’
  29. 29. @claudia_perlich @dstillery 29 THE ‘LESSONS’
  30. 30. @claudia_perlich @dstillery 30 THE ‘LESSONS’
  31. 31. @claudia_perlich @dstillery 31 THE ‘LESSONS’
  32. 32. RETHINKING PROGRAMMATIC From Media Execution To Understanding
  33. 33. 33 Experiment & Measure Design Messaging Understand Audience Through AI in Programmatic New Programmatic: Large Scale Digital Focus Group LARGE SCALE DIGITAL FOCUS GROUP @claudia_perlich @dstillery
  34. 34. 34 YOUR BUZZWORDS HERE ... AI, Big Data, Machine Learning How are things different? Which things are similar?
  35. 35. WHAT MAKES THEM SPECIAL!
  36. 36. YOU CANNOT ASK COOKIES QUESTIONS, BUT THEY DO NOT HIDE MUCH … IoT Device
  37. 37. @claudia_perlich @dstillery 37 SUPERVISED LEARNING What makes YOUR customers special?
  38. 38. LEARNING WHAT MAKES PEOPLE SPECIAL? SAME PROBLEM AS AUDIENCE OPTIMIZATION … People of interest Everybody else
  39. 39. @claudia_perlich @dstillery CASE: BAUME ET MERCIER To identify an Baume audience, we identified all the devices visiting various Baume-et-mercier.com pages. The Homepage and the Watches Page provided the most signal.
  40. 40. @claudia_perlich @dstillery OVERALL AUDIENCE PROFILE A machine-learning algorithm learned to predict who will go to the Baume watches page based on digital & physical activity (no media needed). We found a few surprising insights. @claudia_perlich @dstillery … . What makes Baume customers special?
  41. 41. @claudia_perlich @dstillery Large Jewish Community which views Baume et Mercier as the celebration brand. @claudia_perlich @dstillery Insight 1 : Jewish Community & Celebration
  42. 42. @claudia_perlich @dstillery Insight 2 : Family Car Land Rover, Range Rover, and more family- oriented cars are at the top of the list. @claudia_perlich @dstillery
  43. 43. @claudia_perlich @dstillery Insight 3 : Maternity Shopping Maternity and children’s stores - A Pea in the Pod, Motherhood Maternity and Pottery Barn Kids. @claudia_perlich @dstillery
  44. 44. @claudia_perlich @dstillery Insight 4 : Causes Majority of support toward fighting poverty both in US and the World. @claudia_perlich @dstillery
  45. 45. @claudia_perlich @dstillery Insight 5 : Sports Strong Anglo-European Influence: Soccer & Rugby @claudia_perlich @dstillery
  46. 46. @claudia_perlich @dstillery 46 UNSUPERVISED LEARNING Are there natural groups (segments)?
  47. 47. @claudia_perlich @dstillery SEGMENTATION = PERSONAS IoT Device
  48. 48. @claudia_perlich @dstillery CASE : NON-DAIRY MILK MARKET ENTRY With a new launch in the U.S., the brand was looking to validate and/or disprove their assumptions from the European home market. However, it was not initially available through retail channels
  49. 49. @claudia_perlich @dstillery Top Web Visits www.minimalistbaker.com www.bobsredmill.com www.eater.com www.pcrm.org www.wholefoodsmarket.com www.onegreenplanet.org www.kitchentreaty.com www.peta.org www.flysfo.com www.brickunderground.com www.traderjoes.com www.thisamericanlife.org www.vegetariantimes.com www.lamag.com www.mindbodygreen.com www.coned.com www.seriouseats.com www.luckyvitamin.com www.landmarktheatres.com www.nypl.org 27.6 20.5 20.0 18.1 14.7 14.0 12.9 12.6 12.1 11.8 11.6 11.5 11.4 10.8 10.6 10.6 10.4 9.9 9.8 9.7 WHO IS VISITING THE WEBSITE ? Recipe Brand Recipe Health Brand Interest Recipe Charity Local Local Brand Podcast Recipe Print Health Local Recipe Health Interest Charity
  50. 50. 4 unique subpopulations emerged from the algorithm. 3 were manually filtered as they depicted non-US and industry visitor behavior X X X✔ ✔ ✔ ✔ FINDING SUBPOPULATIONS @claudia_perlich @dstillery
  51. 51. MARKETING PROFESSIONALS @claudia_perlich @dstillery Top Web Visits www.brand-innovators.com www.mindsparklemag.com www.b2bmarketing.exchange www.traackr.com www.theadvertisingclub.org www.ad-tech.com www.bpando.org www.packagingoftheworld.com www.oneclub.org www.martechconf.com www.advertisingweek.com www.cew.org www.newscred.com www.rebrand.com www.ruderfinn.com www.demandgenreport.com www.mmaglobal.com www.thingindustries.com www.skyword.com www.incite-group.com www.dandadimpact.com 831.7 823.5 613.5 599.6 581.3 565.5 536.6 523.4 520.6 512.5 458.4 457.3 454.1 450.4 448.0 447.1 441.9 439.8 435.0 429.0 420.6
  52. 52. The Health Nut Subpopulation 2 18.8% The Trendsetter Subpopulation 5 23.1% The Curator Subpopulation 6 17.6% The Maker Subpopulation 7 15.6% image image image WHY DO PEOPLE BUY MY PRODUCTS? 4 RELEVANT SUB-POPULATIONS @claudia_perlich @dstillery
  53. 53. Top Web Visits www.veralistcenter.org www.twentieth.net www.india-mahdavi.com www.cityreliquary.org www.storefrontnews.org www.trnk-nyc.com www.albertine.com www.mociun.com www.pizzamoto.com www.cheimread.com www.roughtradenyc.com www.thearrivals.com www.eastwindsnackshop.com www.showroomsoftware.com www.littlefieldnyc.com www.cherryandmartin.com www.zeromariacornejo.com www.stevenalan.com www.electricfeathers.com www.thedreslyn.com 1417.0 1162.6 1084.4 961.5 954.9 931.2 712.0 711.9 705.6 694.1 677.4 664.2 659.1 642.0 636.7 629.5 624.3 621.8 605.1 593.7 Index ScoreDomains Art and Politics Furniture and Lighting Paris Architect/Designer NYC Museum Art and Architecture Upscale Homegoods Reading Room Jewelry and Home Goods NYC Pizza Truck Art Gallery NYC Venue Fashion NYC Dumpling Counter Designers and Architects NYC Venue LA Art Gallery Fashion Fashion Fashion Fashion and Home Décor Category 53
  54. 54. Top Web Visits www.loupcharmant.com www.maraisusa.com www.apieceapart.com www.capbeauty.com www.saladforpresident.com www.3-chairs.com www.kickpleat.com www.matteau-swim.com www.bonadrag.com www.tammyfender.com www.thebrooklynkitchen.com www.journelle.com www.jinsoon.com www.mynameisyeh.com www.theundone.com www.cerihoover.com www.shop-foglinen.com www.thedreslyn.com www.thingindustries.com www.fortressofinca.com 1108.3 1017.5 937.1 910.2 878.1 791.5 751.9 742.6 737.2 671.4 669.8 637.4 635.8 622.3 619.1 610.7 583.0 573.1 560.1 512.6 Index ScoreDomains Fashion Fashion Fashion Skincare Food/Style Food Fashion Fashion Fashion Skincare Food/Style Fashion Spa Food/Style Fashion Fashion Décor Fashion Décor Fashion Category
  55. 55. Vegan recipe blog Nutrition blog Vegan recipe blog Vegan recipe blog Vegan recipe blog Vegan recipe blog Recipe blog Vegan recipe blog Vegan recipe blog Vegan recipe blog Vegan recipe blog Vegan recipe blog Vegan recipe blog Vegan recipe blog Recipe blog Vegan recipe blog Vegan recipe blog Vegan recipe blog Recipe blog Vegan recipe blog Top Web Visits www.veganyackattack.com www.thereallife-rd.com www.sweetsimplevegan.com www.fullofplants.com www.elephantasticvegan.com www.yourveganmom.com www.kaleandcaramel.com www.vegannie.com www.veggiesdontbite.com www.thecolorfulkitchen.com www.greenevi.com www.plantpoweredkitchen.com www.thevietvegan.com www.katalysthealthblog.com www.withfoodandlove.com www.keepinitkind.com www.tworaspberries.com www.tworaspberries.com www.sproutedkitchen.com www.theveganversion.com 836.8 832.1 811.8 806.3 789.1 781.1 698.5 673.7 653.2 652.9 652.7 643.7 633.1 632.4 626.2 617.2 610.4 608.1 602.7 601.2 Index ScoreDomainsCategory
  56. 56. We drilled down further to find micro- audiences within this subpopulation Even Deeper Drilling into Health Nuts @claudia_perlich @dstillery
  57. 57. Micro-Audience A (4.9%) www.hilaryseatwell.com www.eatrightstore.org www.oregonswildharvest.com www.kite-hill.com www.ift.org www.alaffia.com www.chosenfoods.com www.veganstore.com www.eatrightpro.org www.chefswarehouse.com www.vansfoods.com www.inmybowl.com www.symrise.com www.mineralfusion.com www.followyourheart.com www.foodingredientsfirst.com www.ancientharvest.com www.gmaonline.org www.lightlife.com www.vrg.org 1008.6 793.8 753.5 685.6 656.7 652.8 590.1 564.9 524.6 522.4 517.4 448.6 408.9 401.2 397.5 392.8 391.6 390.4 383.9 369.1 Index ScoreDomains Emphasis on nutrition and ingredients. Includes resources for professional nutritionists and other alternative food products. @claudia_perlich @dstillery
  58. 58. Micro-Audience B (6.3%) www.elephantasticvegan.com www.veggiesdontbite.com www.cearaskitchen.com www.thecolorfulkitchen.com www.veggieinspired.com www.keepinitkind.com www.veganosity.com www.theedgyveg.com www.blissfulbasil.com www.hotforfoodblog.com www.wallflowerkitchen.com www.rachlmansfield.com www.lazycatkitchen.com www.inmybowl.com www.unconventionalbaker.com www.edibleperspective.com www.contentednesscooking.com www.mydarlingvegan.com www.yupitsvegan.com www.emilieeats.com 1788.0 1494.0 1259.8 1194.5 1143.3 1120.7 1100.7 1096.9 1002.1 998.1 974.1 961.9 958.3 940.7 926.6 922.6 922.0 892.5 877.3 873.6 Index ScoreDomains Dominated by vegan recipe blogs. @claudia_perlich @dstillery
  59. 59. Micro-Audience C (7.6%) www.kaleandcaramel.com www.3-chairs.com www.sproutedkitchen.com www.spiritbeautylounge.com www.rachlmansfield.com www.maraisusa.com www.electricfeathers.com www.thegreenlife.ca www.blissfulbasil.com www.theppk.com www.hotforfoodblog.com www.thefirstmess.com www.momfilter.com www.thecolorfulkitchen.com www.capbeauty.com www.loomstate.org www.keepinitkind.com www.kite-hill.com www.nutritionstripped.com www.veganbeautyreview.com 944.5 718.6 692.4 689.1 590.0 589.3 546.2 500.6 486.6 455.5 436.2 436.1 424.5 423.1 418.4 415.9 410.5 392.1 388.7 387.8 Index ScoreDomains Focus on food as wholesome, green, organic, and beautiful. @claudia_perlich @dstillery
  60. 60. 4 unique subpopulations emerged from the algorithm. 3 were manually filtered as they depicted non-US and industry visitor behavior X X X✔ ✔ ✔ ✔ DO SUBPOPULATIONS MATTER? @claudia_perlich @dstillery Message Testing and Alignment
  61. 61. 61 CASE : CHOBANI @claudia_perlich @dstillery
  62. 62. 62 Linking store purchase to digital activity Loyalty Cards Linking Store Purchase to Digital ActivityCONNECTING DIGITAL ADS TO PURCHASE
  63. 63. How do images impact people who visit fast food? 1.00 1.10 1.20 1.30 1.40 1.50 1.60 1.70 Chipotle Mcdonalds Subway Chick-fil-a Wendys Dominos Quiznos Arbys family human lifestyle logo packopen packsfamily individual lifestyle logo variety product
  64. 64. How do images impact people in food segments? 1.00 1.05 1.10 1.15 1.20 1.25 1.30 1.35 1.40 1.45 Produce-44079 Beverages > Coffee, Tea & Cocoa-104052 Meat & Seafood- 49528 Beverages-104049 Sauces, Spices & Seasonings-44089 Snacks, Cookies & Candy-44106 Frozen Foods- 104081 family human lifestyle logo packopen packs
  65. 65. @claudia_perlich @dstillery QUESTIONS? Contact: @claudia_perlich @dstillery

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