SlideShare a Scribd company logo
1 of 54
Advertising should be 
evaluated on its ability to 
move people through a 
series of intermediate steps 
on a continuum that ranges 
from ignorance on one end 
to brand advocacy on the 
other.
AGREE 
DISAGREE
Not able to create a single customer view 
Data not shared/accessible across organization 
Too infrequent data collection 
Too little/no customer data 
Source: 2012 BRITE/NYAMA Marketing in Transition Study 
42% 
51% 
39% 
29%
LOGIC EMOTION
BEFORE 
Define clear objectives 
Train & aline team with these objectives 
Tim Kerrison
DURING 
Monitor fitness & fatigue 
Aline tour tactics on these data 
Tim Kerrison
AFTER 
Analyse data gathered in TdF 
Use learnings to win gold in Olympic games 
Tim Kerrison
A BBDO model
We create effectiveness
We create effectiveness 
Minimize risk of failure 
•KPI frameworks 
•Targeting (who?) 
•Testing (what?)
We create effectiveness 
Inflight optimisation 
•Tracking&reporting 
•Dashboards 
BEHAVIOUR 
BELIEF 
Brand funnel approach
We create effectiveness 
Feed learnings into 
next campaign 
•Responder profiling 
•Campaign evaluation
Consequences of model ?
Consequence # 1 
Mental shift : from ad hoc execution towards 
continuous learning 
LEARN 
LEARN 
LEARN
Consequence # 2 
More adaptive content & media planning
Consequence # 3 
More adaptive budget allocation
5 little data stories
# 1. Building a KPI 
framework for P&G 
For P&G’s pan-European relationship 
marketing program to so-called golden 
households.
New website 
UK Version
New website 
UK Version
New objectives, new KPI’s 
Build stronger relationships with more people 
=
KPI framework 
Build stronger relationships with more people 
KPI Metric Target Tracking source 
REACH Reach+1 Lorem Ipsum GA, DB 
REACH (Aided) awareness vs. 
control Lorem Ipsum Program tracker 
REACH DB coverage - optins Min x % of 25-49 
women DB 
ENGAGE User action engagement 
score 
Min. x% with y% of 
registered user base GA, DB 
ENGAGE Site engagement score Min. x% with y% of 
registered user base GA, DB 
Site engagement score (%) 
= 
# visits per year 
------------------------------------------------- 
# months between first and last visit
KPI framework 
Also on micro-level 
Macro Metric Micro Metric Target Tracking source 
SITE ENGAGEMENT 
SCORE Bounce rate < x% GA 
Repeat visit rate > x% GA 
Dwell time > min. GA
Learnings 
# 1. Include KPI’s into your brief 
# 2. Create your own metrics from existing 
data 
# 3. Micro metrics reveal how macro KPI’s 
behave over time
# 3. Eye-tracking two 
competing d2d folders
Magazine Folder 
1. Magazine content gets attention 
2. Harol is perceived as ‘higher’ quality 
1. Product offering is more clear
1. Promotions get enough attention 
2. Small print is barrier to take action
Automated eye-tracking 
Use a computer model simulating human attention 
+90% predictive accuracy
Let’s test the computer model ;-) 
What do people see in the first 3-5 sec on this page ?
Yellow ?
Black ?
Yellow !
Does this page survive the W-W-W test ? 
WHAT? – WHY ? – WHAT’S NEXT ?
Attention map
Interest area attention vs. avg 
156% (6%) 
37% (2%)
Learnings Eye-tracking 
# 1. Eye-tracking leads to actionable insights 
# 2. Smarter, cheaper, faster solutions are 
becoming available 
# 3. Do the W-W-W test for every creative
# 4. The ROI of targeting 
customers according to 
their lifecycle 
Who? 
What? 
How much ? 
When?
Makro’s customer life cycle 
Welcome 
Acquisition 
DM 
DM 
Non-buyers 
DM 
Reactivation DM 
6 months 
Reactivation DM 
9 months 
Reactivation DM 
12 months
A simple creative and offer 
6 months 9 months 12 months
ROI ? 
Return = Cost-Revenue 
Cost = DM piece (crea + postage) + % reduction 
Revenue (short term) = Revisit (amount * margin) 
Revenue (1 year) = Revisit frequency * amount * margin
If cost = 100 
Return (short term) = ? 
Return (1 year) = ? 
150 
275 
200 
500
If cost = 100 
Return (short term) = ? 
Return (1 year) = ? 
150 
275 
235 
586
Learnings CLC targeting 
# 1. CLC targeting = ROI 
# 2. Short ànd long-term (LTV) 
# 3. Targeting > offer + creative
# 5. About analysing the 
ultimate behavioural data 
The 
rational 
brain 
Stated 
behavior 
The 
rational 
brain 
Stated 
behavior 
Traditional market 
Traditional market 
research 
research 
The 
The 
emotional 
brain 
Actual 
behavior 
emotional 
brain 
Actual 
behavior 
Neuromarketing research
Tracking declared behaviour 
The 
rational 
brain 
Stated 
behavior 
The 
rational 
brain 
Stated 
behavior 
What do you think about this TV commercial (score 1-5)?
Tracking brain activity over time 
“Brains never ever lie” 
Attention Emotions 
The 
The 
emotional 
brain 
Actual 
behavior 
emotional 
brain 
Actual 
behavior
franky.willekens@bbdo.be
THANKS

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Advertising effectiveness evaluated on ability to move people through brand advocacy stages

  • 1.
  • 2. Advertising should be evaluated on its ability to move people through a series of intermediate steps on a continuum that ranges from ignorance on one end to brand advocacy on the other.
  • 3.
  • 5. Not able to create a single customer view Data not shared/accessible across organization Too infrequent data collection Too little/no customer data Source: 2012 BRITE/NYAMA Marketing in Transition Study 42% 51% 39% 29%
  • 6.
  • 8.
  • 9. BEFORE Define clear objectives Train & aline team with these objectives Tim Kerrison
  • 10. DURING Monitor fitness & fatigue Aline tour tactics on these data Tim Kerrison
  • 11. AFTER Analyse data gathered in TdF Use learnings to win gold in Olympic games Tim Kerrison
  • 14. We create effectiveness Minimize risk of failure •KPI frameworks •Targeting (who?) •Testing (what?)
  • 15. We create effectiveness Inflight optimisation •Tracking&reporting •Dashboards BEHAVIOUR BELIEF Brand funnel approach
  • 16. We create effectiveness Feed learnings into next campaign •Responder profiling •Campaign evaluation
  • 18. Consequence # 1 Mental shift : from ad hoc execution towards continuous learning LEARN LEARN LEARN
  • 19. Consequence # 2 More adaptive content & media planning
  • 20. Consequence # 3 More adaptive budget allocation
  • 21. 5 little data stories
  • 22. # 1. Building a KPI framework for P&G For P&G’s pan-European relationship marketing program to so-called golden households.
  • 23. New website UK Version
  • 24. New website UK Version
  • 25. New objectives, new KPI’s Build stronger relationships with more people =
  • 26. KPI framework Build stronger relationships with more people KPI Metric Target Tracking source REACH Reach+1 Lorem Ipsum GA, DB REACH (Aided) awareness vs. control Lorem Ipsum Program tracker REACH DB coverage - optins Min x % of 25-49 women DB ENGAGE User action engagement score Min. x% with y% of registered user base GA, DB ENGAGE Site engagement score Min. x% with y% of registered user base GA, DB Site engagement score (%) = # visits per year ------------------------------------------------- # months between first and last visit
  • 27. KPI framework Also on micro-level Macro Metric Micro Metric Target Tracking source SITE ENGAGEMENT SCORE Bounce rate < x% GA Repeat visit rate > x% GA Dwell time > min. GA
  • 28. Learnings # 1. Include KPI’s into your brief # 2. Create your own metrics from existing data # 3. Micro metrics reveal how macro KPI’s behave over time
  • 29. # 3. Eye-tracking two competing d2d folders
  • 30. Magazine Folder 1. Magazine content gets attention 2. Harol is perceived as ‘higher’ quality 1. Product offering is more clear
  • 31. 1. Promotions get enough attention 2. Small print is barrier to take action
  • 32. Automated eye-tracking Use a computer model simulating human attention +90% predictive accuracy
  • 33. Let’s test the computer model ;-) What do people see in the first 3-5 sec on this page ?
  • 36.
  • 38. Does this page survive the W-W-W test ? WHAT? – WHY ? – WHAT’S NEXT ?
  • 40. Interest area attention vs. avg 156% (6%) 37% (2%)
  • 41. Learnings Eye-tracking # 1. Eye-tracking leads to actionable insights # 2. Smarter, cheaper, faster solutions are becoming available # 3. Do the W-W-W test for every creative
  • 42. # 4. The ROI of targeting customers according to their lifecycle Who? What? How much ? When?
  • 43. Makro’s customer life cycle Welcome Acquisition DM DM Non-buyers DM Reactivation DM 6 months Reactivation DM 9 months Reactivation DM 12 months
  • 44. A simple creative and offer 6 months 9 months 12 months
  • 45. ROI ? Return = Cost-Revenue Cost = DM piece (crea + postage) + % reduction Revenue (short term) = Revisit (amount * margin) Revenue (1 year) = Revisit frequency * amount * margin
  • 46. If cost = 100 Return (short term) = ? Return (1 year) = ? 150 275 200 500
  • 47. If cost = 100 Return (short term) = ? Return (1 year) = ? 150 275 235 586
  • 48. Learnings CLC targeting # 1. CLC targeting = ROI # 2. Short ànd long-term (LTV) # 3. Targeting > offer + creative
  • 49. # 5. About analysing the ultimate behavioural data The rational brain Stated behavior The rational brain Stated behavior Traditional market Traditional market research research The The emotional brain Actual behavior emotional brain Actual behavior Neuromarketing research
  • 50. Tracking declared behaviour The rational brain Stated behavior The rational brain Stated behavior What do you think about this TV commercial (score 1-5)?
  • 51. Tracking brain activity over time “Brains never ever lie” Attention Emotions The The emotional brain Actual behavior emotional brain Actual behavior
  • 52.

Editor's Notes

  1. Important! This template has theme colors which can be shared with other Office software (Word &amp; Excel) Click the menu “Design” on PC or “Themes” on a Mac -&amp;gt; then Choose “Colors” -&amp;gt; click “Create New Theme Colors” (at the bottom) The colors of the presentation appear. Name the Color Scheme, e.g. BBDO Colors -&amp;gt; click “Save” This “Theme Colors” can now be used in Word and Excel (go to the menu Design in Word or Excel) –&amp;gt; Colors -&amp;gt; Choose BBDO Colors
  2. Dat is wat anders he - - u dacht: ik ga deze middag nog maar eens naar die bbdo connect sessie, want dat is daar altijd wel een creatieve boel. En plezant ook. Niet dus. Vandaag is het serieus. Het gaat over weten. En meten is weten. En meten is dus ook data.
  3. U kent het verhaal Bovendien is het crisis. We evolueren naar een zero defective reclame – de tijd van 50% is waste, s voorbij &amp;gt; stel dat je bij Philips 50% van de lampen stuk zijn aan het einde van de productielijn, dan vlieg je buiten. Maar als een marketeer 50% response heeft, is hij super fier. Op zch mag dat, maar wat niet mag is dat je niet weet waarom die andere 50% niet bewogen / gekocht hebben. Want dan kan je het de volgende keer niet beter doen. Iedereen akkoord?
  4. Zwart / geel / blauw Iedereen is het eens, maar toch doen we het zo weinig. EN WAAROM?
  5. Nog vaak een gebrek aan dat – of beter gezegd: aan procedures om data op een goede manier te gatheren en samen te brengen. 1 OP DE 3 doet dat goed, de andere niet. Dus als jij daar flink mee bezig bent, kijk dan even LINKS EN RECHTS van jou – die knoeien er dus deftig op los.
  6. Maar niet te fier worden – zelfs als je de data op een goede manier managed, loopt het vaak nog fout. Want er learnings uit halen, en die nadien ook nog toepassen - - daar wringt meestal het schoentje nog harder. En dat heeft toch nog altijd te maken met onze typische mkt ingesteldheid. 3 fenomenen: We meten niet graag, omdat we bang zijn dat het slecht gaat zijn We meten niet graag, omdat we eigenlijk al met ons volgend project bezig zijn We meten niet graag, gewoon omdat we dat niet graag doen
  7. Jullie dus liefst bezig met de rechterzijde – wij niet. Je ziet dat overigens ook aan de slides – die waren de vorige sessies veel mooier, maar het voordeel van vandaag is wel dat wat er op staat, juist is. Zelfs als we het hebben over het meest emotionele der emotionele dingen: de koers
  8. Een prangende vraag: waarom won Wiggins de tour? Omdat hij het meeste pillekes pakte? Of omdat hij de beste was? Neen, omdat deze jongens
  9. Doelstelling= tour winnen (en bvb niet ook ritten winnen, tot spijt van Cavendish) Training en teamdaarop afgestemd &amp;gt; trapfrequentie en nodige wattage voor de cols in deze tour &amp;gt; die renners die dat aankunnen (350 w bergop / maximaal 1200 – flesha)
  10. Vermoeide renner &amp;gt; geen opdrachten qua aanvallen of helpen anderen / gewoon rusten in peleton Hier zie je de curves van Flesha – die blij was dat
  11. Learnings voor OG - - goud Dus eigenlijk heeft Tim Kerrison de tour en goud gewonnen, en wat meer is - hij is de inspiratiebron voor het BBDO model. En dat gaat Franky u eens uitleggen si.
  12. BBDO’s adagium: wij creëeren effectiviteit. Daarvoor gebruiken we beide hersenhelften, maw de linker data-kant en de rechter-creatieve kant. Ideeën die werken. Of ze werken ? Kunnen we we alleen maar achterhalen door data, door te meten. Wij gaan met data aan de slag op 3 niveaus: pre-, tijdens, post campagne (naar analogie van Tour/Tim Kerrisson)
  13. Voor de campagne proberen we zoveel mogelijk risico op falen van de campagne te elimineren. Of anders gezegd de verwachte return optimaliseren. Hoe ? Door onder andere : Het scherp stellen van Objectieven / wat we willen bereiken met de campagne omvormen naar KPI-frameworks zodat we / klant weet wanneer we succes bereikt hebben / op dezelfde golflengte zitten qua verwachting en vooral ook bepalen hoe we succes zullen meten , een heel belangrijke stap. Twee andere gaat over is targeting waardoor we duiken in gedragsdata om een beter beeld te krijgen van de doelgroep en dus relevanter/effectiever kunnen bereiken Derde is de boodschap/content scherper stellen via testing allerhande (vnl gedragsdata). Vandaag niet alles vertellen. Straks volgens 5 individuele korte data verhaaltjes die elk inzoomen op een stuk. Laat me eerst zeer kort de overige niveaus uitleggen.
  14. Tijdens de campagne zorgen we dat de campagne metrics die het succes of falen van de campagne visualiseren. Via tracking / reporting. Al dan niet voor real-time dashboards zodat we de campagne continu kunnen opvolgen. Want we tracken niet om te tracken. We tracken om bij te sturen, te optimaliseren (en als dat kan, liefst tijdens de Tour of tijdens de rit). En dit kan natuurlijk voor gedragsdata (online bezoek, coupon redemptie, …), maar ook voor belief data (wat is campagne effect op de zogenaamde brand funnel van awareness tot purchase intent) ? Meestal gebeurt dit wel .. .maar …
  15. De volgende belangrijke stap (die veeeel te weinig gezet wordt) is Post Campagne. Doelstelling hiervan is de learnings van de campagne gebaseerd op de campagne tracking door te geven naar de volgende campagne. Daarvoor hebben o.a. 2 tools : responder profiling en campaign evaluation. Responder profiling: Wie heeft er nu eigenlijk gereageerd ? Zijn dat de mensen die we wilden bereiken ? Is het juiste profiel ? Of zijn de respondenten/deelneemers aan de volgens het volume succesvolle activatie ook klanten/mensen die effectief kopen ? Wat is het aandeel ‘spelers’ vs. ‘kopers’ van het merk of product ? Allemaal vragen die beantwoord kunnen worden door een responder profiling. Een andere tool is zogenaamde close out reports wat we bvb. systematisch doen voor het Zin in meer programma van P&amp;G. Op basis van de campagne reporting maak je een overzicht van de campagne / een campagne case waarin steevast 4 dingen terugkomen : 1. Objectieven campagne 2. Content/mechaniek/kanalen hoe we die objectieven willen bereiken. 3. Resultaten / het succes of falen 4. Learnings Dat op zich vormt de basis voor een campagne evaluatie workshop waarin we alle partijen (media, productie, agentschap, klant, …) samenbrengen en de resultaten en conclusies vanuit elke invalshoek verrijken en omvormen naar actiepunten voor “de volgende keer”. En waarbij we alle aspecten van de campagne onder de loep nemen van strategie tot executie.
  16. Als je het model rigoureus toepast – campagne na campagne &amp;gt; jaarplan. Als je dit model doortrekt op jaarbasis, zie ik 3 gevolgen voor manier van werken.
  17. Mentale shift &amp;gt; focus verleggen van executie naar continu leren. We zijn dikwijls bezig met de executie van de volgende campagne. We staan te weinig stil bij de lopende of afgelopen campagne. Dit betekent mentale ruimte en ook nodige tijd investeren in het leren uit de vorige campagne of volgens het model in elke tussenfase.
  18. 2. Dit bekent flexibel omspringen met (jaar)planning. Zowel qua inhoud en media plan. Gedaan met het maken van een plan dat 1 jaar vooruitkijkt. Cyclischer plannen. Bvb. Domino’s Pizza in UK. Die hebben uit data gemerkt dat ze bij regenweer meer pizza’s thuisbezorgen dan bij zonnig weer. Logisch. Hun mediaplan is dan ook aangepast aan het weer – meer investeren bij verwacht regenweer en regionaal op die plaatsen in de UK waar dit verwacht wordt (online zelfs realtime). Ook logisch?!
  19. 3. Meer flexibele budget investering. Een reserve/potje aanhouden voor experimenteren en leren. Bvb. Coca-cola. 70% aan “certainties” : wat ze kennen en wat werkt (GRP) 20% aan meer gerichte advertising (op bepaalde doelgroepen) 10% aan “experiment &amp; learn” – misschien wel het tegenovergestelde van de pizza’s van daarnet (investeren als/waar het warm is) Het interesssante daaraan is dat slechts 50% van tijd aan ‘certainties’ wordt besteed en de rest van de tijd (2x25%) verdelen over de twee overige aan waardoor een voortdurende vernieuwing in aanpak / instroom van nieuwe dingen die werken in ‘certainties’, waar bulk van budget naartoe gaat. Dus tijd, budget en plan flexibel maken.
  20. Genoeg theorie. Laten we dit toepassen. 5 verhaaltjes. Gefocust op die eerste faze – pre-campagne. Want daar liggen de meeste ‘gains’. En in elke story geven we ook een paar learnings mee. Ah ja…
  21. Het opbouwen van een KPI framework voor P&amp;G en meer bepaald voor hun pan-Europees relatieprogramma dat meerdere merken omvat naar zogenaamde Golden house holds = huishoudens met aan het hoofd vnl vrouwen van 25-49j. die proportioneel meer geld uitgeven aan A-merken zoals P&amp;G
  22. Belangrijk onderdeel in het programma is de website om die doelgroep te bereiken. UK versie, vers gelanceerd. Een paar weken terug.
  23. Met content maar offers zoals coupons en samples van de deelnemende merken.
  24. Doelstelling. Nog sterkere relaties met nog meer mensen uit de doelgroep. Nieuwe doelstellingen? Nieuwe KPI’s ? Nieuw &amp;gt; engagement doorweegt op reach. Waarom ? We hebben dankzij data gezien - via match met shopper panel data - dat mensen in het programma vs. buiten het programma, meer besteden op total P&amp;G merken dan average. En hoe hoger de engagement met het programma (maw respons/bezoek), hoe hoger de spend. Dus een directe relatie tss engagement en sales. Vandaar het belang.
  25. Die nieuwe objectieven en KPI’s uit briefing hebben we vertaald naar verschilende metrics – targets - tracking source ? Enkele voorbeelden. Naast reach met evidente metric zoals bvb. de derde hier &amp;gt; DB coverage - optins (we moeten doelgroep natuurlijk kunnen bereiken), Hebben we dus ook nieuwe engagement metrics ingevoerd met aantal voorbeelden hier. Bvb. de laatste &amp;gt; site engagement score. We willen voor het meten van engagement zowel frequency als recency laten meetellen. Daarom hebben we een eigen metric gecreeerd op basis van output van GA-data : nl. visits en periodiciteit.
  26. Ook gedaan op micro-niveau. Micro metrics beinvloeden macro metrics. Macro metrics &amp;gt; typisch in maandelijks dashboard / mgmt summary - ‘stuur’ van je programma Micro metrics = verklarend waarom bepaalde metrics op macro – niveau zich op een bepaalde manier gedragen Bvb. evident dat bounce rate, bezoekers van 1 pagina aan de site en dan weggaan, de site engagement score bepaalt, ook hier passen we dezelfde systematiek toe (metrics &amp;gt; target &amp;gt; bron), Let wel : de targets hier bepalen mee je targets op makro-niveau. Zelfde techniek ook toepassen op advertising kpi’s.
  27. De learnings
  28. 2 verschillende h-à-h folders  magazine (Harol, onze klant) vs. product folder (Winsol, de concurrent) Zelfde objectief  drive people to website and store (ongeveer op hetzelfde moment in de bus --- voorjaar &amp;gt; opendeurdagen) Vragen Harol: Wordt de magazine content gelezen ? Vallen de promoties voldoende op ? Worden de juiste merk associaties gemaakt ? Harol = kwaliteit / vakmanschap
  29. Hoe werkt het ? 10 mensen in de markt voor zonnewering Bril &amp;gt; hoe roder gekleurd hoe meer aandacht Achteraf diepte interview De conclusies.
  30. Nog een conclusie. 3 learnings voor Harol : Hou het format: magazine Iets meer structuur &amp;gt; producten Small print eruit.
  31. Steeds snellere, goedkopere eyetracking oplossingen op de markt. Een voorbeeld is eyequant. Dat dankzij een computermodel – gebaseerd op effectieve waarnemingen hoe mensen naar een scherm kijken, de output van een eyetracking onderzoek simuleert. Met +90% voorspellende kracht, ondertussen.
  32. Bvb. deze nieuwe homepage van Mercedes. Het model voorspelt wat mensen zien in de eerste 3-5 sec. Laten we even de test van het computermodel doen. We gaan allemaal de ogen sluiten en dan opnieuw gedurende 5 sec. kijken naar dit beeld. Sluit de ogen (Jan Bardi). Open de ogen. 1-2-3-4-5
  33. Belangrikere vraag. Doorstaat deze pagina de WWW-test ? Maw. Is het duidelijk waarover het gaat (what) Is het duidelijk waarom dit mij moet interesseren (why) Is het duidelijk wat ik vervolgens moet doen (what’s next)
  34. Klassieke attention map zegt al dat er weinig aandacht naar de WHAT’s NEXT gaat. Eerder op de WHAT en de WHY.
  35. De tool laat ook toe met data te berekenen hoeveel aandacht een bepaald punt krijgt tov het gemiddelde. Bvb. WHY ? WHAT ? Neemt 6% van totale scherm opp in (getal tss haakjes) en krijgt 156% meer aandacht dan het gemiddelde aandachtspunt op het scherm. Terwijl de CFA button die 2% inneemt, nog altijd 37% meer aandacht krijgt, maar zit toch in de oranje zone. Maw te optimaliseren.
  36. Why does it (not) work ? Compared to competition ? Compared to different versions ?
  37. 4de verhaaltje gaat over targeting. Van Makro. Makro weet – dankzij de kaart – veel over hun klanten en hun gedrag. Wie ze zijn, wat ze kopen, hoeveel € ze uitgeven, wanneer ze komen… De droom van elke data analist of planner… je kan bvb. basket analysis, predictive modeling doen, etc. (hier in BE nog in kinderschoenen --- als tijd over is (13.48), verhaal van Target). Ook Makro is daarmee bezig. Maar vandaag wil ik het hebben over een certainty die we al jaar en dag toepassen op Makro. Omdat het ROI opbrengt. Hun lifecycle targeting.
  38. Hier zie je Makro’s customer life cycle. Afhankelijk van in welk stadium een klant zich bevindt (opsommen – links/rechts), bepaalde acties – voorgesteld door de dots Bvb. nieuwe klanten. Andere kant wegglijdende klanten – 6 maanden niet geweest, 9 maanden niet geweest, 12 maaanden niet geweest.
  39. Simpele brief Simpel aanbod &amp;gt; 3%, 5%, 10%
  40. Wat is return ?
  41. Tenslotte: 2 breinen &amp;gt; rationele brein (blauw) en het emotionel brein (purper + geel). Wat is het verschil ? Het rationele brein probeert te verklaren hoe we met ons emotioneel brein ons gedragen, hoe we ons voelen of hoe we echt denken. En waarom we bepaalde beslissingen nemen. Bvb. vrouwen voor een schoenenetalage. In onderzoek krijgen we in traditionele technieken input van het rationele brein. Via neuromarketnig input van het emotionele brein. En dat leidt letterlijk tot diepere inzichten waarom mensen zich gedragen of hoe ze zich voelen
  42. Ge kent dit wel. Liking studies. Twijfel bij de waarde voor effectieve impact én bijsturing. Verhaal van de kikker. 3 kikkers op de kant &amp;gt; heel koud water 1 zegt : ik spring erin. Hoeveel kikkers nog aan de kant ? Alle 3. Waarom? Kikkers zeggen niet wat ze doen. Mensen ook niet. En omgekeerd: mensen doen niet wat ze zeggen.
  43. Nu door het emotionele brein te monitoren – via van die patchkes op het hoofd – kan je wel effectieve impact meten. De output zijn positive and negative peaks. Afhankelijk van de timing/plaats , the peak can mean different things … welke elementen krjigen aandacht vs. saai, welke elementen triggeren grotere emotionel involvement, zowel positief als negatief. Nu een al paar keer dat ik predik voor meer van dit type van gedragsanalyse bij klanten. Maar zelfde – iets sterkere - reactie als bij overige data projecten. Moet dat wel/werk dat wel ? Tijd en investering waard ? Misschien verwachten jullie een case, jammer genoeg kan ik er geen tonen. Nog een klant kunnen overtuigen. Echter, langs de andere kant &amp;gt; een primeur vandaag. Want zonder dat jullie het zelf weten waren jullie deel van een onderzoek via een revolutionaire onderzoekstechniek. Ontwikkeld hier in het huis van de toekomst. Waardoor we in staat zijn om jullie aandacht (emotie lukt nog niet) – via het meten van hersenactiviteit – zonder die patches te volgen. Dus we hebben ongeveer 2x 20 min gemeten hoe fel gevolgd, niet nodig om achteraf te vragen.
  44. Hier het verloop van de presentatie in 2 stukken. De resulaten worden nu ingeladen. Hopelijk dat het werkt. (feit goed samenzit is gemakkelijker/Kinepolis is geinteresseerd) Resultaten &amp;gt; begin hoge aandacht, verslapping, terug wakker, wat pieken/dalen en terug verhoging de laatste 5 minuten. 2 dingen: Uitkijken wanneer stopt het Of Verhoogde aandacht omdat het over jullie ging. Of &amp;gt; Interesse in neuro onderzoek (cheque)