INDEX
A
- above the fold (self-service options found on home page), 100
- ACSI. See American Customer Satisfaction Index
- AGL (Australian Gas Light), 228
- AI. See artificial intelligence
- Airbnb, 98
- airline experiences, 131
- Aldi, 8
- Alexa (Amazon), 99
- Amazon
- ACSI scores, 6
- Alexa, 99
- autopopulated list, 162
- contacts per order, 7, 26, 38
- contacts per unit shipped, 22, 38
- conventional retailers and, 8
- customer contact reasons, 26
- customer focus of, 12–13
- customer obsession and ownership culture at, 82
- as digital native Innovator, 98
- Dropdown 1-Click ordering profiles created by, 162
- emergence of, 224
- Flipping the Turtle, 160
- founder of, 22
- four-level approach of, 31
- as Innovator, 13, 98
- as market leader, 4
- mechanisms pioneered by, 129
- as non-contact business, 78
- notification (businesses copying aspects of), 130
- order management, 128–29
- order processing revolutionized by, 91t
- product withdrawal, 159
- promotions council, 82
- recommendations offered to (Amazon), 119
- service redesign at, 233
- “shock and awe” tactics of, 62
- Skyline report, 209, 211
- snowball process, 42, 160
- success of, 250
- testing of returned products, 153–54
- WOCAS, 242
- word-of-mouth marketing by, 2
- American Customer Satisfaction Index (ACSI), 2
- American Prairie (nonprofit), 13
- Anders, George, 1
- ANI. See automatic number identification
- Apple, 223
- Appliances Online, 81
- artificial intelligence (AI)
- analytics mechanism using, 167
- -based analytics (repeat contacts revealed by), 43
- determination of customers affected by power outages, 83
- -enabled chat with machine-learning engine, 244
- “match rate” and, 212
- -powered speech, 99
- questions anticipated using (Xero), 101
- software (contact reasons figured out by), 46
- -tagged reasons in chatbot (N26), 36
- technology (documents recognized using), 112
- tools (claims agent’s use of), 185
- tools (customer personas), 103
- Understand actions and, 25
- assess your ability to
- Redesign, 245
- assess your need to
- Assign and Prioritize, 51–74
- attack squads, 71
- bad stories, 57–60
- “challenge demand” strategy (Cable One), 55–56
- C-level sponsorship, 53
- cross-disciplinary team, 72–73
- culture of ignoring problems, 59–60
- current targets and priorities, 69–70
- demand reduction (bank), 57–58
- description of, 51–53
- digital transformation (Fairfax), 56–57
- fishbone diagram, 70, 70f
- five whys technique, 70
- good stories, 54–57
- hints and tips, 72–73
- how to Assign and Prioritize, 60–72
- importance of (examples) (T-Mobile USA), 54–55
- iteration, 73
- location in path to frictionless, 51f
- minimum viable product, 72
- multichannel action analysis, 52
- multichannel view, 68
- multigame-player giant (Blizzard Entertainment), 57
- ownership model (design of), 60–64
- pension fund (frustrated), 58–59
- risk in, 73
- robotics process automation, 72
- sales through service, 67
- senior sponsorship, 72
- smaller wins, 73
- solution feasibility, 70–72
- strategy for each customer contact reason, 64–69, 66f, 67f
- techniques, 52
- V–I matrix, 65, 68
- assisted channels, 13, 52
- Atlassian, 244
- attack squads, 71
- augmented agent solutions, 116
- Australian Tax Office (ATO), 4, 13, 114
- Australia Post, 225–26
- automatic number identification (ANI), 162
- automation. See also Digitize
- automobile claims (USAA Insurance), 176–77
- autopopulated list (Amazon), 162
B
- “back-to-front” reengineering, 141
- bad stories
- Beissner, Carmen, 36
- BestBuy, 8
- Bezos, Jeff, 22, 26, 224, 240
- BHAG. See big hairy audacious goal
- big data, 128
- big hairy audacious goal (BHAG), 88, 89
- Bla Bla Car, 11–12
- Blackberry, 223
- “bleeding edge,” 236
- Blizzard Entertainment, 57
- success of, 250
- Borders, 8
- Bosch, Harry, 193
- bot, 34f
- Buxton, Charles, 123
C
- Cable One
- caller line identification (CLI), 162
- call-tag mania, 29–30
- Carsales.com, 7
- CES. See customer effort scores
- chat, xiiif
- chatbots
- Christensen, Clayton, 223
- Churchill, Winston, 171
- Cisco Webex, 8
- CitiPower & Powercor, 154
- C-level sponsorship, 53
- CLI. See caller line identification
- click and collect, 83, 113
- co-browsing software programs, 113
- Colorado Department of Motor Vehicles, as frictionless business, 4
- Community Support VOC (Airbnb), 196
- complacency, 17
- contacts per order (CPO), 7
- contacts per unit (CPU), 22
- contacts per X (CPX), 33, 38, 39f
- containment rates, 102
- COVID-19 pandemic, 99, 128, 153
- CPO. See contacts per order
- CPR. See Customer Permanently Retained
- CPU. See contacts per unit
- CPX. See contacts per X
- credit strategies relaxed (Vodafone), 128
- customer effort scores (CES), 18f
- customer experience (CX), 18, 44f
- Customer and Market Insights (E.ON), 197
- Customer Permanently Retained (CPR), 160
- customers
- control over product-related decisions, 189
- elderly (E.ON), 99
- expectation of, 90
- frustrated (complex technology and), 230
- history (valuing of), 190
- impact of contacts on, 24–25
- inconvenienced, 130
- irate (due to poor quality and testing processes), 84
- language of (messages in), 143
- loyalty of, 126
- needs of (simplifying of), 27–28
- out of date on how business operates, 125
- personas, 103, 185
- power outages affecting, 83
- propensity to complain, 213
- reasons for contact (capture of), 35
- reasons for contacting organizations, 3f
- recommendations offered to (Amazon), 119
- relationships (management of), 135
- rightsizing of, 174
- as silent sufferers, 213
- sources of insight (Red Hat), 198
- tenure with organization, 212
- working from home, 128
- worst metrics, 78
- CX. See customer experience
D
- data lakes, 208, 216
- deep detractors, 200
- deflection. See Digitize
- DHL, 224
- digital native Innovators, 98
- Digitize, 97–121
- above the fold (self-service options found on home page), 100
- assessment of need to Digitize (questions), 121
- augmented agent solutions, 116
- bad stories, 105–107
- classic examples addressed by, 98–99
- click and collect, 113
- co-browsing software programs, 113
- description of, 97–100
- Do It with Me approach, 104
- golden 30 seconds, 110
- good stories, 100–105
- hints and tips, 117–20
- how to Digitize, 107–117, 108f
- location in path to frictionless, 97f
- overlap of Preempt and, 119–20
- V–I matrix, 98
- Dimmeys, 8
- direct to consumer (DTC), 176
- DIWM approach. See Do It with Me approach
- Do It with Me (DIWM) approach, 104
- Domain, 56–57
- downgrade of plan, 124
- downstream costs, 27f
- Dropdown 1-Click ordering profiles (Amazon), 162
- DTC. See direct to consumer
- dumb contacts, 65
- Dyson, 4, 79
E
- Einstein, Albert, 21
- Eliminate, 77–94
- assessment of need to Eliminate (questions), 93–94
- bad stories, 83–85
- big hairy audacious goal, 88, 89
- classic examples of, 79
- click and collect, 83
- complete elimination (investigation of), 89–90
- customer contact reasons, 85
- data-mining techniques (analytics tools and), 87
- description of, 77–80
- disconnects (delivery issues), 83–84
- disconnects (telecommunications retailer and internet service), 84–85
- downstream costs, 78
- elimination of defects (Uber), 82–83
- feasible solutions (identification of), 87–89
- good stories, 80–83
- hints and tips, 90–91, 91t, 92t, 93t
- how to Eliminate, 85–90, 86f
- Ishikawa fishbone diagrams, 87
- joined up organizations, 90
- lateral thinking, 89
- location in path to frictionless, 77f
- look for common causes, 80
- online business (Winning), 80–81
- poor quality and testing processes, 84
- promotions council (Amazon), 82
- solution effectiveness (assessment of), 89
- Streamline versus, 150–51
- test and learn approach, 89
- worst customer metrics, 78
- E.ON
- Estonia (government of), 4, 13
F
- Facebook, emergence of, 224
- Fairfax, 56–57
- FCR. See first-contact resolution
- FedEx, 130, 224
- fintech company
- first-contact resolution (FCR), 27, 40–44f
- fishbone diagram, 70, 70f, 87
- Flipping the Turtle (Amazon), 160
- Flyknit, 153
- FOFA. See Future of Financial Advice
- Fortnum & Masons, 9
- fraud
- French National Railway, 12
- Frictionless Organizations
- automation in, 23f
- benefits of being frictionless, 5–9
- collective focus, 14
- customer experience management, 18f
- description of, 1–2f
- digitization in, 23f
- mass-notification mechanisms of, 133
- number of support staff in, 2
- obstacles to becoming frictionless, 15–19
- operation of processes in, 11f
- path to being frictionless, 14f
- proactive thinking of, 124
- research, 213
- self-assessment, 10t
- stages, 14–15
- traits of, 10
- types of, 12–13
- winning strategy of, 4–9
- word-of-mouth marketing by, 2
- frontline agents, 41
- Future of Financial Advice (FOFA), 201
G
- Gateway, 223
- Genius Bars (Apple), 11
- “gig economy,” 12
- golden 30 seconds, 110
- good stories
- Google, 223, 224
H
- hackathons, 243–44
- hardship conversations, 174, 189–90
- Harris Scarfe, 8
- Hey Google, 99
- Hiltz, Kim, 197
- hints and tips
- homeshoring, 239
- Hope, Bob, 143
- how to
- Hywood, Greg, 56
I
- Innovators. See also Amazon
- Airbnb, 98
- borrowing tricks from, 119
- business models of, 98
- classic story (Zip Co), 28–29
- description of, 12–13
- differentiator for, 98
- digital native, 98
- discount airlines emerged as, 226
- fintech (incubation of potential), 241
- go-to market programs (speed of), 223
- leadership team in, 211
- N26, 8, 98
- Netflix, 8, 98
- OLX, 98
- outdated, 223
- Realestate.com, 98
- Redfin, 98
- service redesign by, 233
- Tesla, 9f
- Uber, 8, 13, 98, 119
- Xero, 8, 13f
- Yahoo, 223
- Zillow, 98
- Innovator’s Dilemma, The (Christensen), 223
- insourcing, 241
- interactive voice-response system (IVR), 30
- Ishikawa fishbone diagram, 70, 70f, 87
- ISO 10002-2018 standard, 22
- IVR. See interactive voice-response system
J
- Jaguar Land Rover, 221
- JD Power, customer satisfaction rating awarded by, 55
- Jetstar (Qantas), 227, 250
- Jobs, Steve, 149
- joined up organizations, 90
- Jones, Megan, 198
- journey mapping, 18
K
- key performance indicators (KPIs), 27
- Kodak, 17
- Kohler plumbing-supply business, 112
- KPIs. See key performance indicators
- Krug, Steve, 97
L
- lateral thinking, 89
- Learn, 193–218
- ability to learn (method), 206–8
- assessment of need to Learn (questions), 218
- averages, 214–15
- bad stories, 199–201
- data-collection techniques, 214
- data lakes, 208
- deep detractors, 200
- description of, 193–95
- executives and management (connection with customers), 203–6, 207t
- gaps (indicators), 208–9
- good stories, 195–99
- hints and tips, 214–17
- how to Learn, 201, 202f
- incremental approaches, 215
- integrated data set and repository, 215
- involvement, 215
- location in path to frictionless, 193f
- mechanisms that quantify friction (group), 203, 204t
- mismatches, 216
- ownership, 209–11
- patterns, 211–13
- research, 213
- rhythm (building), 211
- richer qualitative insights (group), 203, 205–6t
- VOC and, 216
- Legere, John, 225
- Leverage, 171–91
- assessment of need to Leverage (questions), 191
- automobile claims (USAA Insurance), 176–77
- bad stories, 178–79
- channel trapping, 178–79
- contacts (experiences needed for), 173
- customer choices, 189
- customer contact (Leverage experience required for), 184–85
- customer’s history, 190
- delivery of Leverage experiences (mechanisms), 185–87
- description of, 171–74
- fraud conversations, 189–90
- good stories, 174–78
- hardship conversations, 184, 189–90
- hints and tips, 188–90
- how to Leverage, 180–88, 181f, 182t
- insurance claims (NZ earthquake), 178
- Leverage experiences (looking behind), 187–88
- location in path to frictionless, 117f
- online-to-independent dealer (Trek Bikes), 176
- order taking, 179
- reasons (dimensions), 172–73
- reasons (typical), 174
- sales (RACV), 175
- steps, 172
- strategy application (determination of), 180–183, 181f, 182t
- value-add conversations (Vodafone Portugal), 177–78
- look for common causes, 80
- Louis Vuitton, 9
M
- machine learning. See artificial intelligence
- Madison-Biggs, Desiree, 196
- minimum viable product (MVP), 72, 223
- model
- AGL, 155
- business (airline), 226–27
- business (Atlassian), 244
- business (customer-focused), 12
- business (of Innovators), 98
- business (low-friction), 8
- business (online), 81
- business (simplified), 9
- digital, 98
- financial advice, 9
- flipping of (digital content), 57
- high-end service, 9
- hub-and-spoke, 239
- operating (realignment of), 231, 232f, 234
- ownership (design of), 60, 61f
- ownership (set of contacts), 53
- “pay for use,” 237
- sales operating (rethinking of), 222
- self-service, 227
- service (AGL), 228–29
- service (questionnaire), 245–46
- service (redesign of), 233
- Skyline, 197f
- “smoke and mirrors,” 223
- streaming service, 234
- taxicab (old), 12
- Team of Experts (T-Mobile USA), 225
- tiered service, 155, 229
- Uber, 82
- Mota, David da Costa, 28
- multichannel contacts, 35f
- MVP. See minimum viable product
N
- N26
- national care preemption, 126–27
- Netflix, 8, 98, 223
- Net Promoter Score (NPS), 18f
- New Zealand, earthquake in (2010–11), 178
- Nielsen, Jakob, 113
- Nike, 152–53
- Nokia, 17, 223
- NPS. See Net Promoter Score
O
- OBP. See outside best practices
- Octopus card (Hong Kong), 114
- OLX
- omnichannel integration, 3f
- order management (Amazon), 129–30
- outage information mechanisms, 127–28
- outside best practices (OBP), 243
- Oyster card (London), 114
P
- Paraschivoiu, Ana, 153
- Pareto report, 197, 209
- Powell, Rachael, 101
- predictive analytics, 128
- Preempt, 123–46
- airline experiences, 131
- application of (situations), 125–26
- assessment of need to Preempt (questions), 146
- “back-to-front” reengineering, 141
- bad stories, 130–32
- capabilities enabling Preemptive actions, 125
- channel choice, 138
- credit strategies relaxed (Vodafone), 128
- critical questions, 124
- customer control, 144–45
- customer languages (messages in), 143–44
- deciding when and what to preempt, 132–36, 134f
- description of, 123–26
- good stories, 126–30
- hints and tips, 142–45
- how to Preempt, 132–42
- intervention stages, 126
- location in path to frictionless, 123f
- missed deliveries, 131
- multiple tailored channels, 142–43
- national care preemption, 126–27
- order management (Amazon), 129–30
- outage information mechanisms, 127–28
- overlap of Digitize and, 119–20
- preemptive message examples, 135t
- “range anxiety,” reduction of (Tesla), 128–29
- snowballs, prevention of, 140
- software updates, 130
- solution design, 136–38, 137t
- solvers versus repeat creators, 142f
- text appearing as fraud, 132, 137
- tools and approaches (success of), 138–39
- two-way communication, 144
- promotions council (Amazon), 82
- propensity to complain, 212–13
- propensity to contact (PTC), 212–13
- PTC. See propensity to contact
Q
- Qantas, 226–27
R
- RACV. See Royal Automobile Club of Victoria
- Realestate.com, 98
- real-time speech analytics, 186
- reasons (for customer contacts), 1f
- Redesign, 221–46
- agile methodologies, 239–40
- assessment of ability to Redesign (questions), 245–46
- bad stories, 229–31
- complex technology (customers frustrated with), 230
- core realignment, 234–40
- decline in mail-delivery business (Australia Post), 225–26
- description of, 221–224, 222f
- discount airlines, 226–27
- failure and success, 231
- globalization, 238
- good stories, 224–29
- hackathons, 243–44
- hints and tips, 242–44
- homeshoring, 239
- how to Redesign, 231–42, 232f
- importance of, 222
- IT transformation (metrics failures with), 230–31
- location in path to frictionless, 221f
- manufacturing redesign (Tesla), 227–28
- minimum viable product, 223
- need to Redesign, 233–34
- outside best practices, 243
- as recurring strategy, 240–42
- service model (rethinking of) (AGL), 228–29
- skills-based routing, 228
- stages, 223
- team of experts (T-Mobile USA), 224–25
- Redfin, as Innovator, 98
- Red Hat, 198
- reengineering, “back to front,” 141
- Renovators
- re-shoring, 239
- Responsive Agencies
- “ride-sharing” services, 12. See also Uber
- Rivian, 9
- robotic process automation (RPA), 72
- Rodig, Kristina, 99, 197
- root cause analysis, 47
- Royal Automobile Club of Victoria (RACV), 175
- RPA. See robotic process automation
- Runyan, Jon, 51
- Ryanair, 226
S
- SaaS accounting software, 4
- sales through service (STS), 67
- SBR. See skills-based routing
- service levels, 6f
- Ship-It Days (Atlassian), 244
- silent sufferers, customers as, 213
- Siri (Apple), 99
- skills-based routing (SBR), 228
- Skyline, 197, 209
- smart routing, 167
- “smoke and mirrors” models, 223
- SMS, 52f
- snowballs
- Soccer Without Borders (nonprofit), 13
- Sondheim, Stephen, 250
- Southwest Airlines, 226
- Sparklight Internet, 55
- speech analytics, 186f
- Speth, Ralf, 221
- S&P 500 Index, 4
- Sprint, 225
- Start, 247–250
- Stevenson, Troy, 82
- Stoller, Bryan, 101
- Streamline, 149–69
- analytics, 167
- antithesis of, 156
- assessment of need to Streamline (questions), 168–69
- automation, 164
- avid runners (Nike), 152–53
- bad stories, 155–57
- complaint handling, 160–61
- complaints team (unqualified), 155–56
- complaints threat, 155
- defective products (Amazon), 153–54
- description of, 149–52
- Eliminate versus, 150–51
- exceptions (isolation of), 165–66
- frontline teams, 166
- good stories, 152–55
- hints and tips, 165–67
- how to Streamline, 157–165, 158f, 163f
- location in path to frictionless, 149f
- market challenges during pandemic (Vodafone Romania), 153
- network fault (energy business), 154–55
- open-ended questions, 161–62
- root cause analyses, 159
- smart design, 166–67
- special cases, 150
- streams, 152
- vehicle recall, 156–57
- STS. See sales through service
- Sydney Morning Herald, 56
T
- Target, 8
- Team of Experts (TEX), 225, 235
- Tesla, 9
- test and learn approach, 89
- TEX. See Team of Experts text analytics, 38f
- text messaging, 138f
- tiered service model (AGL), 155, 228–29
- Tiffany’s, 9
- TikTok, 234
- T-Mobile USA
- tNPS. See transactional Net Promoter Scores
- top-issues management, 197
- toxic revenues, 124–25
- Toys R Us, 8
- transactional Net Promoter Scores (tNPS), 27f
- Trek Bikes, 176, 216, 250
- TriumphPay, 8
- two-way text messaging, 144
U
- Uber, 11
- as digital native Innovator, 98
- elimination of defects, 82–83
- as example of Frictionless Organization, 12
- as Innovator, 8, 13, 98, 119
- as non-contact business, 78
- original model of, 82
- revenue growth of, 82
- success of, 12, 250
- UberEats, 82
- unassisted channels, 52
- Understand, 21–49
- analytics techniques, 44
- assessment of need to Understand (questions), 48–49
- automation and digitization, 23
- bad stories, 29–31
- call-tag mania, 29–30
- classic Innovator story (Zip Co), 28–29
- CPX, 33, 33t, 38, 39f, 48
- customer contact (reasons for), 24
- customer contact (tracking of), 23–24
- customer contact channels, 33
- customer contact with organization (tracking of), 31–35, 34
- customer feedback system (Airbnb), 28
- customer impacts of contacts, 24–25, 44–46, 45t
- customer needs simplified (OLX), 27–28
- description of, 21–25
- “failure demand,” 24
- first-contact resolution, 40–44, 42f
- frontline agents, 41
- global standardization (Vodafone), 27
- good stories, 26–29
- hints and tips, 46–48
- indirect post-contact costs, 37
- interactive voice-response system, 30
- location in path to frictionless, 21f
- multichannel contacts, 35
- ownership test, 47–48
- process framework, 31–46, 32f
- reasons (Amazon), 26
- reasons (too numerous), 30
- reasons for customer contacts, 35–40
- repeat contact rates, 24
- root cause analysis, 47
- snowballs (management of), 42–43
- text analytics, 38
- visualization tools, 34, 34f
- United Airlines, 13, 101–2, 250
- Upass (Korea), 114
- UPS, 130
- USAA Insurance, 4, 176–77
V
- value-add conversations (Vodafone Portugal), 177–78
- Value–Irritant matrix (V–I matrix), 65, 69, 98
- V–I matrix. See Value–Irritant matrix
- visualization tools, 34
- VOC. See voice of customer
- Vodafone, 13
- voice of customer (VOC), 18, 216
W
- Walmart, 8
- Wave, 82–83
- web chat, xiif
- Webex (Cisco), 8, 231
- what our customers are saying (WOCAS), 196, 242
- Winning, John, 80–81
- Winnings Group, 80
- WOCAS. See what our customers are saying
X
- Xero
Y
Z
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