Creating 16:9 Presentations

Kyle FindlaySenior R&D ExecutiveConstantin MichaelModelling ConsultantJan HofmeyrChief Research Officer

many very little living animalcules, very prettily a-moving

~ Anton van Leeuwenhoek, 1693Traditional metrics break down at an individual levelAwareness metricsBrand strength metricsUsage metricsRespondent levelAggregate levelSurvey metric correlations with actual purchasing behaviour in subsequent 12 months at a respondent (blue) and aggregate level (green).6 datasets | Countries: USA, UK, China Categories: retailers, laundry detergents0.480.120.860.210.870.250.860.510.960.510.940.560.960.730.190.140.840.220.950.380.950.51Macro-validity, micro-opacitySurveySaid that they were daily drinkersSaid drink dailyActually drink dailySaid drink dailyActually drink dailySaid drink dailyActually drink dailyDiaryLouw, A, Withington, V & Jansen, A. 2005. Self-reported Behavior: Fact or Fiction, paper presented at the 2005 South African Marketing Research Association conference

The Chaos Beneath the Surface

Buying behaviour is surprisingly complexSurvey-derived UK laundry dual usage network demonstrating the amount of movement between brands beneath the surface. There is much more inter-brand usage than many marketers expect.

How to read: node size represents brand penetration (% users in past 12 months); thickness of connecting lines represents % dual users of the two brands in past 12 months

People are surprisinglymobile

33211Source: Hofmeyr & Bongers. 2010. A Critique of the Law of Double Jeopardy: Why Modeling Averages isnt Good EnoughA two year purchase stream of an individual panelist buying chocolate

Millions of transactions...Time period2006-20072007-20082008-20092009-20102010-2011Number ofpurchasesShampooN/A24,41870,74574,938N/ALaundryN/A537,521210,948202,320N/ASoft drinksN/A1,413,2353,849,7871,724,778N/ASummary of number of active panellists and purchase instances in each year. Note: 2006 and 2010 data was used in defining active panellists in some cases and so was not analysed directly . Source: KWP

Repeat purchase cycle lengthFrequency distributions of repeat purchase cycles. Source: KWPHow do people really behave?

Transition matrix for shampoo in the UK showing how people changed their share of wallet (SOW) from 2007 to 2008. Source: KWP2008SOW 0SOW 10SOW 20SOW 30SOW 40SOW 50SOW 60SOW 70SOW 80SOW 90SOW 1002007SOW 0SOW 10SOW 20SOW 30SOW 40SOW 50SOW 60SOW 70SOW 80SOW 90SOW 10099.60.10.10.10.00.00.00.00.00.00.078.010.47.52.11.00.30.30.10.00.00.175.75.48.64.92.11.11.00.50.30.20.368.44.29.76.93.41.72.61.40.40.31.062.83.37.77.56.73.13.22.51.10.61.747.12.79.39.56.85.47.32.92.92.43.756.21.35.48.05.44.07.34.11.92.64.043.62.06.58.83.94.99.17.54.61.67.531.02.37.810.16.24.79.38.56.24.79.317.00.04.35.35.39.613.87.46.412.818.144.70.22.74.54.01.18.14.53.84.521.8How Do People Really Behave?

What proportion of people spend the same after a year?

% steadyProportion of panellists that gave a brand the same SOW two years in a row. These patterns are consistent across all years. Source: KWP10%100%SOW10%100%SOW10%100%SOWWhat proportion of people stay with a brand after a year?

% users that stay% transient usersProportion of people that leave a brand after one year (defectors) versus those that stay with the brand (non-defectors). Source: KWP3128286972725955564145445150494950512007-20082008-20092009-20102007-20082008-20092009-20102007-20082008-20092009-2010Defection rates by share of wallet

% defectorsProportion of each SOW group that stopped using the brand after a year. Source: KWP10%100%SOW10%100%SOW10%100%SOWNew users by share of wallet

% new usersProportion of each SOW group represented by new users since last year. Source: KWP10%100%SOW10%100%SOW10%100%SOW

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWP

Year 1:Year 2:Active panelists x Share of Wallet (SOW) UK shampoo 2007-2008. Source: KWPWheres the Value?

Spend by share of wallet% spendShampoo (2008 to 2009)Laundry (2008 to 2009)Soft drinks (2008 to 2009)% of users (incidence)Proportion spend that comes from each SOW group. Source: KWP10%100%SOW10%100%SOW10%100%SOW

Value from loyal customers% value from loyal customersProportion of spend that comes from customers who give a brand 70-100% share of wallet in year 1. Source: KWP1822212626241212122007-20082008-20092009-20102007-20082008-20092009-20102007-20082008-20092009-2010

Value from transient customers% value from transient customersProportion of spend that comes from customers who stop using the brand from one year to the next. Source: KWP5358581924231719192007-20082008-20092009-20102007-20082008-20092009-20102007-20082008-20092009-2010Managing the Flows

Managing the flows100%Year 1115%Year 2-16%+24%-21%Surf (laundry)DefectionSlide downSlide up+29%New users100%Year 2121%Year 3-18%+22%-21%DefectionSlide downSlide up+38%New usersNOTE: Unweighted data might not accurately represent real-world brand movements. Source: KWP30%

Managing the flows100%Year 1Year 2100%-18%+15%-19%Persil (laundry)DefectionSlide downSlide up+22%New users100%Year 2Year 3-14%+16%-17%DefectionSlide downSlide up+20%New usersNOTE: Unweighted data might not accurately represent real-world brand movements. Source: KWP103%20%

21%Managing the flows100%Year 1Year 294%-16%-20%Head & Shoulders (shampoo)DefectionSlide downSlide up+23%New users100%Year 2Year 3100%-22%DefectionSlide downNew usersNOTE: Unweighted data might not accurately represent real-world brand movements. Source: KWP+8%-13%+14%Slide up70%20%

What about other categories?Source: Coyles, S & Gokey, TC. 2002. Customer Retention is Not Enough, The McKinsey Quarterly 2002 No.2What Does It All Mean?

Measures must correlate at an aggregate AND respondent level

Markets are dynamic. Most people will change their spend over time

Many customers are transient

Brands lose and gain fractions of a person, not a whole person.

Strong memory structures are created (and activated) through sophisticated mass marketing and brand building

Manage the flows

Thank you!many very little living animalcules, very prettily a-moving

~ Anton van Leeuwenhoek, 1693

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