Index
ISBN: 978-1-83982-687-0, eISBN: 978-1-83982-684-9
Publication date: 3 August 2020
This content is currently only available as a PDF
Citation
Jaworski, B.J. and Lurie, R.S. (2020), "Index", The Organic Growth Playbook: Activate High-Yield Behaviors to Achieve Extraordinary Results – Every Time (American Marketing Association), Emerald Publishing Limited, Leeds, pp. 279-284. https://doi.org/10.1108/978-1-83982-684-920201017
Publisher
:Emerald Publishing Limited
Copyright © 2020 Bernard J. Jaworski & Robert S. Lurie
INDEX
Note: Page numbers followed by “n” indicate end notes.
Ability
, 201–202
Actionable variables
, 100
Allocating spend
across buying process stage
, 208–209
across media channels and tactics
, 210–211
across segments
, 209–210
Amazon’s BCVP to drive organic growth
, 17
Asymptomatic disease (ASD)
, 23, 30–32, 34–35, 39
buying process
, 25–27
objective test for
, 44
Awareness-consideration-purchase-trial- (repeat) model
, 40
Behavior change
drivers and barriers to
, 32–34, 75–78, 120–125, 170–175
high-yield
, 64–69
to–from
, 198
Behavior change value proposition (BCVP)
, 11, 17, 34–35, 78–80, 125–127, 175–180, 184, 188–193, 212
activating value of target behavior
, 200–203
for Caesar Financial
, 196
changing customer behavior
, 200
conventional wisdom
, 185–188
defining targets
, 197
explanation
, 193
finding leverage in different stages of buying process
, 187
mapping differentiation
, 191
moving from attitude to action
, 187–188
template
, 193–197
to–from behavior changes
, 198
value proposition for buying process behavior (change)
, 198–200
Behavioral objectives
, 13, 56–57
picking and defining
, 55–59
testing correlation of customer characteristics and
, 71
upstream vs. downstream
, 59–61
Beliefs and attitudes, preexisting
, 139, 145–149
Bias for drivers
, 132–133
Brazil
, 231, 234
Burke, James (Johnson & Johnson)
, 3
Business-to-business (B2B)
, 229
buying process
, 240–242
industries
, 6
markets
, 18–19, 56, 66, 144, 150, 159, 230, 239–240, 248, 273n32
waterfalls
, 54
Business-to-consumer (B2C)
, 159, 229, 274n39
companies
, 259
market
, 18–19, 131
Buyer behavior
barriers
, 137
ignoring negative aspects
, 133
Buying path
for replenishing everyday wine inventory
, 49
for vintage/investment wines
, 48
Buying process
, 24–30, 47, 64–69, 115–118, 162–167
B2B
, 240–242
excerpt from color cosmetics
, 116
finding leverage in different stages of
, 187
limits of
, 42
quantified wine
, 51
triggering events and objectives in wealth management
, 164
for wine
, 46
Caesar Financial
, 19, 161–162, 205, 256
BCVP for
, 196
behavior change value proposition
, 175–180
buying process and high-yield behavior change
, 162–167
disproportionate investment
, 180–181
drivers and barriers to behavior change
, 170–175
redesigned campaign
, 184
rethinking segmentation
, 167–170
Changing behaviors
, 217
China
, 231
Cisco
, 252
Commercial investment
across areas
, 260–261
to focused spend
, 267
Communications
, 148
Concentration of customers
, 244–245
Consumer
insight
, 148
research to market-driven insights
, 266–267
Context
, 125–126, 139, 150–151
Conventional approach
, 7
to segmentation
, 93
Conventional industry wisdom
, 256–257
Conventional segmentation
, 87–88
Conventional wisdom
, 40–42, 84–88, 130–131, 185–188, 207–208
to system-wide replacement
, 263–264
Customer behavior
changing
, 200
data
, 122
and outcomes
, 141
Customer behavior framework (CBF)
, 120–121, 130, 135–136, 139–140, 152–154, 173, 199
Customer–purchase process
, 41
Customers
, 88, 131, 158, 165–166
customer experience, redesigned
, 178–179
desired experience
, 142–145
in high-propensity segments
, 91
identification
, 242–244
narrative
, 123, 136, 154–156, 199
scarcity and concentration of
, 244–245
Demographic profile
, 232
Demographic/geographic segmentations
, 85
Desired experience
, 139, 142–145
Digital marketing
, 211
Disney World
, 185
Disproportionate investment
, 11–18, 36–37, 80–81, 127–128, 180–181, 205–207
allocating spend across buying process stages
, 208–209
allocating spend across media channels and tactics
, 210–211
allocating spend across segments
, 209–210
conventional wisdom
, 207–208
disproportionately focused segment-specific campaigns
, 222–224
estimating funding and timing
, 220–222
explanation
, 213–214
overall plan
, 214–216
prioritizing and group segments into implementation waves
, 218–220
segment characterization
, 216–218
segment-specific marketing tactics to activate high-yield behaviors
, 223
sequence segments and spend disproportionately
, 211–213
sequencing waves for successive marketing campaigns
, 219–220
Disproportionately focused segment-specific campaigns
, 222–224
Document behaviors and outcomes
, 140–142
Downstream behavioral objectives
, 59–61
Drivers and barriers
to behavior change
, 32–34, 75–78, 120–125, 134–138, 170–175
to consulting with or selecting
, 77
economic
, 157–158
extracting
, 157–159
E2DBW
, 131, 133–133
Economic barriers
, 137
Economic drivers and barriers
, 157–158
Economy structure
, 232
Ecuador
, 231
Ellison, Larry (Oracle)
, 3
Energy services
mapping buying process waterfall for
, 67
segmentation frame for
, 74
thirteen-step process to purchase
, 65
EnServ
, 19, 63–64, 154, 159, 198–199, 222, 224, 239, 260, 265
BCVP
, 78–80
buying process and high-yield behavior change
, 64–69
disproportionate investment
, 80–81
drivers and barriers to behavior change
, 75–78
drivers and barriers to consulting with or selecting
, 77
R&D organization at
, 258
rethinking segmentation
, 69–75
Environment axis
, 105
EuroMonitor
, 259
Facebook
, 114
Firmographic segmentation
, 85
Food and Drug Administration (FDA)
, 249
Full value system
, 250–251
Function-specific segmentations
, 97
Funding and timing estimation
, 220–222
Germany
, 231
Gerstner, Lou (IBM)
, 3
Goldman Sachs
, 162
Gomez, Susan
, 63, 83
Government-shaped buying processes
, 251
Heating, ventilation, and air conditioning (HVAC)
, 63
business
, 206
system
, 257
Helena Styx Cosmetics
, 113–114
Heterogeneity across segments
, 85
High-innovation (high-tech) markets
, 252–254
High-yield behavior
, 7–8, 10–12, 15–18, 43–44, 55–56, 58–59, 134, 217
change
, 24–30, 64–69, 115–118, 162–167
segment-specific marketing tactics to activating
, 223
High-yield leverage points
, 208
Highest collective correlation
, 103
Highly regulated competitive markets
, 248–249
Homogeneity within segments
, 85
IBM
, 5
Implementation waves, prioritizing and group segments into
, 218–220
India
, 231, 234
Indonesia
, 231
Information sources
, 138
Input behaviors
, 40
Instagram
, 114
Institutional arrangements
, 159
Institutional barriers
, 138
Intrinsic competitive challenge
, 6
Job rotation
, 261–262
Job rotation to longer-term perspective
, 267–268
JPMorgan
, 162
Less developed economy markets
, 230–233
separate economies within
, 233–238
Leverage point
, 116, 118
Living energy management roadmap
, 80
Logistics/transportation infrastructure
, 232
Magnitude
, 216
Mapping buying process waterfall
, 9–10, 12, 39–40, 42–43
conventional wisdom
, 40–42
for energy services
, 67
explanation
, 44–52
high-yield behavior
, 43–44
picking and defining behavioral objective
, 55–59
standard purchase funnel analysis
, 52–55
upstream vs. downstream behavioral objectives
, 59–61
Mapping differentiation
, 191
of PVP and BCVP
, 191
Market segmentation map
, 209
Marketers
, 208
Marketing management
, 97
McDonald’s
, 5
Media availability
, 232
MOA Model
, 193, 201–203
Morocco
, 231
Motivation
, 201–202
Multiple, siloed views to organization-wide views
, 265
Needs-based segmentations
, 86
Nestle
, 259
Netflix
, 5
New product development (NPD)
, 241
Nordisk, Novo (Lars Rebien S⊘rensen)
, 4
Occasion-based marketing
, 144
Opportunity
, 201–202
Organic growth
BCVP
, 17
CEO of the Year and
, 4–6
principles and choices
, 13
reigniting for sparkle brand
, 125
Organic Growth Challenge
, 5
Organic Growth Playbook, The
, 7–9
BCVP
, 11, 17
invest disproportionately
, 11–18
mapping buying process waterfall
, 9–10, 12
path forward
, 18–21
propensity-based segmentation
, 10–11
unearthing critical drivers and barriers of target behavior
, 11
Organizational context
, 151
Organizational roadblocks
, 255–256
conflicting views and maps
, 257–258
conventional industry wisdom
, 256–257
from conventional wisdom to system-wide replacement
, 263–264
growth roadblocks and playbook solutions
, 264
from job rotation to longer-term perspective
, 267–268
from multiple, siloed views to organization-wide views
, 265
Playbook Approach
, 262
promotion cycles and job rotation
, 261–262
from spread of commercial investment to focused spend
, 267
spreading commercial investment across areas
, 260–261
underfunding consumer research
, 259–260
from underfunding consumer research to market-driven insights
, 266–267
Output behaviors
, 39
Pakistan
, 231, 234
Parker, Mark (Fortune magazine)
, 4
Path dependent process
, 41
Patient segmentation
, 31
Peanut butter marketing
, 41
Peru
, 231, 234
Pharma markets
, 237
Physical barriers
, 137
Physical context
, 151
Playbook Approach
, 229–230, 255, 262
B2B buying process
, 240–242
B2B markets
, 248
complex, government-shaped buying processes
, 251
customer identification
, 242–244
full value system
, 250–251
high-innovation (high-tech) markets
, 252–254
highly regulated competitive markets
, 248–249
less developed economy markets
, 230–233
position in value system
, 245–248
scarcity and concentration of customers
, 244–245
to segmentation
, 93
separate economies within less developed markets
, 233–238
traditional B2B markets
, 239–240
Point-of-entry customers
, 114, 122–124
Presentation
, 125–126
Primary care physician (PCP)
, 29, 57
Procter & Gamble
, 259
Product
, 125–126
centricity
, 131–132
Product value propositions (PVPs)
, 78, 183, 186, 188
mapping differentiation of
, 191
Promotion
, 168
cycles
, 261–262
Propensity
, 217
heat map
, 102–108
Propensity-based segmentation
, 10–11, 83–84, 88–93, 108–110
constructing segmentation frame and propensity heat map
, 102–108
conventional vs. playbook approach to segmentation
, 93
conventional wisdom
, 84–88
explanation
, 93–99
identifying actionable and meaningful segmentation variables
, 99–102
maps
, 91, 94
of new wealth management clients
, 169
process
, 95
for women purchasing color cosmetics
, 119
Psychographic segmentations
, 86
Purchase behaviors
, 45
Purchase-based behavior segmentation
, 86
PVP-driven model
, 186
Qualitative analysis
, 53
Quantification
, 54
Ratan Tata (Tata Group)
, 3
Requests for proposals (RFP)
, 64, 67–68, 142, 222, 242
Research and development (R&D)
, 240, 253, 255, 258
Rethinking segmentation
, 167–170
Rethinking segmentation
, 30–32, 69–75, 118–119
Revenue growth
, 3
Scarcity of customers
, 244–245
Schmidt, Eric (Alphabet)
, 3
Schwab, Charles
, 162
Segment characterization
, 216–218
Segment-by-segment
, 206
Segment-specific marketing tactics to activate high-yield behaviors
, 223
Segmentation
, 84
dueling
, 97
variables
, 99–102
Segmentation frame
, 70, 72, 93–94, 102–108
for energy services
, 74
Self-termination
, 65–6
Sequence segments and spend disproportionately
, 211–213
Sequencing waves
, 220
for successive marketing campaigns
, 219–220
Shin, Eugene
, 161, 205
Situation axis
, 105
Situation-based consumption
, 153
Situational variables
, 73
Snapchat
, 261
Social context
, 151, 159
Social experience
, 121
South Africa
, 231, 234
Sparkle cosmetics
, 19, 113–115, 129–130, 144, 198, 202, 224
behavior change value proposition
, 125–127
buying process and high-yield behavior change
, 115–118
customer behavior data
, 122
customer behavior framework
, 121
customer narrative
, 123
disproportionate investment
, 127–128
drivers and barriers to behavior change
, 120–125
excerpt from color cosmetics buying process
, 116
propensity-based segmentation for women purchasing color cosmetics
, 119
reigniting organic growth
, 125
rethinking segmentation
, 118–119
Stakeholder influence
, 66
Standard purchase funnel analysis
, 52–55
Target behavior, activating value of
, 200–203
Terrafix
, 1–3, 23–24, 28–30, 39, 184, 198, 239, 251, 262
behavioral objective
, 92
buying process
, 44
choices
, 37
Terrafix Integrated Marketing Choices
, 19
Texas Instruments
, 252
Theory of business
, 269
Three-phase process
, 135
Turkey
, 231
Twitter
, 261
Type/mix of channels
, 232
Uber
, 188, 191
Underfunding consumer research
, 259–260
Unearthing critical drivers and barriers of target behaviors
, 11, 129–130
bias for drivers
, 132–133
CBF
, 139–140, 152–154
conventional wisdom
, 130–131
customer’s desired experience
, 142–145
document behaviors and outcomes
, 140–142
document preexisting beliefs and attitudes
, 145–149
drivers and barriers of behavior change
, 134–138
easy to do business
, 133–134
explanation
, 138–139
extracting drivers and barriers
, 157–159
product centricity
, 131–132
social and physical context
, 149–152
writing customer narrative
, 154–156
Unilever
, 259
Upstream behavioral objectives
, 59–61
Value proposition for buying process behavior (change)
, 198–200
Value system, position in
, 245–248
Variability, actionable and meaningful, proprietary and alignment (VAMPA)
, 95–96
Venezuela
, 231
Viagra
, 187
Welch, Jack (GE)
, 3
Wilcox, Sam
, 1, 18, 23, 26, 39
YouTube
, 114
- Prelims
- 1: Overview of the Organic Growth Playbook
- 2: Terrafix: Reigniting Blockbuster Growth in Pharmaceuticals
- 3: First Principle: Map the Buying Process Waterfall
- 4: EnServ: “Everyone Sees the Market the Same Way”
- 5: Second Principle: Use Propensity-Based Segmentation
- 6: Sparkle Cosmetics: Winning at the Wall
- 7: Third Principle: Unearth the Critical Drivers and Barriers of Target Behaviors
- 8: Caesar Financial: “We Need the Whole Client Portfolio!”
- 9: Fourth Principle: Develop a Behavior Change Value Proposition
- 10: Fifth Principle: Invest Disproportionately
- Implementing the Playbook
- 11: Applying the Playbook in Different Markets
- 12: Overcoming Organizational Roadblocks
- Notes
- References
- Index
- Acknowledgments
- About the Authors