digital business
Digital Business course by prof. Stefan Klein. Summary created as preparation for exam. WWU Münster, 2018
1. online search
1.1. bias
1.1.1. each site favors their products
1.2. cognitive issue with information
1.2.1. lower recall rate
1.2.2. higher recall where to later access it
1.3. question of neutrality
1.4. reviews
1.4.1. very important
1.4.1.1. for people
1.4.1.2. in decision making
1.4.1.3. numbers (%) increasing
1.4.2. often defrauded
1.4.2.1. fake positve for yourself
1.4.2.2. fake negative for competitor
1.4.2.3. why?
1.4.2.3.1. for yourself when reputation is weak
1.4.2.3.2. for others when intensive competition
1.4.3. solutions to fight
1.4.3.1. review meta
1.4.3.2. telling what's defrauded
2. model canvas blocks
2.1. one by one
2.1.1. 1) customer segments
2.1.2. 2) value propoitions
2.1.3. 3) channels
2.1.4. 4) customer relationships
2.1.5. 5) revenue streams
2.1.6. 6) key resources
2.1.7. 7) key activities
2.1.8. 8) key partnerships
2.1.9. 9) cost structure
2.2. altogether
2.2.1. financial streams
2.2.1.1. revenue streams
2.2.1.1.1. WTP
2.2.1.1.2. pricing
2.2.1.1.3. types
2.2.1.2. cost structure
2.2.1.2.1. cost driven
2.2.1.2.2. value driven
2.2.1.2.3. Porter's Norm Strategies
2.2.2. key
2.2.2.1. resources
2.2.2.1.1. physical
2.2.2.1.2. financial
2.2.2.1.3. intellectual
2.2.2.1.4. human
2.2.2.2. activities
2.2.2.2.1. categories
2.2.2.3. partnerships
2.2.2.3.1. types
2.2.2.3.2. motivations
2.2.3. customer
2.2.3.1. segments
2.2.3.1.1. separate if
2.2.3.1.2. markets
2.2.3.2. relationships
2.2.3.2.1. motivations
2.2.3.3. value propositions
2.2.3.3.1. qualitative
2.2.3.3.2. quantitative
2.2.3.3.3. questions
2.2.3.3.4. value pyramid
2.2.3.3.5. simplified grid of goals
2.2.4. channels
2.2.4.1. phases
2.2.4.1.1. awareness
2.2.4.1.2. evaluation
2.2.4.1.3. purchase
2.2.4.1.4. delivery
2.2.4.1.5. after sales
2.2.4.2. types
2.2.4.2.1. ownership
2.2.4.2.2. medium
2.2.4.2.3. format
2.2.4.2.4. function
2.2.4.3. multi = "clicks & bricks"
2.2.4.3.1. offline+online
2.2.4.3.2. if integration extensive
2.3. why models fail?
2.3.1. flawed design
2.3.2. poor implementation
2.3.3. not growing enough
2.3.4. strong competitor
2.3.5. disruptive innovation
2.3.6. failing to adjust
2.3.7. legal regulation
3. design
3.1. 1. understand
3.1.1. market
3.1.2. client
3.1.3. technology
3.1.4. constraints of the problem
3.2. 2. observe
3.2.1. real people, real life
3.2.2. confusions?
3.2.3. likes? hates?
3.2.4. what is still not addressed?
3.3. 3. visualize
3.4. 4. evaluate, refine
3.4.1. quick iterations
3.5. 5. implement
3.6. extra tips
3.6.1. a) thinking like a traveler
3.6.2. b) field observing with fresh eyes
3.6.3. c) treat life as an experiment
3.6.4. d) cultivate an attitude of wisdom
4. facebook debate
4.1. polarisation
4.1.1. social and politcal cost
4.1.2. not reflected in business model
4.2. data collection
4.3. free basics
4.3.1. little local services/news
4.3.2. collects data
4.3.3. violates net neutrality
4.4. pays not enough taxes
4.4.1. ridiculously low
4.4.2. part of strategy (purposefully)
4.5. news problem
4.5.1. fake new
4.5.2. not checking
4.6. ads
4.6.1. fb doesn't (want to) know who buys them
5. recommender systems
5.1. goal
5.1.1. fully automatic and precise
5.1.2. technology-based
5.1.2.1. AI
5.1.2.2. machine learning
5.2. problems
5.2.1. queries difficult to automatically process
5.2.2. preferences
5.2.2.1. subtle
5.2.2.2. individual
5.2.2.3. difficult to specify
5.2.2.3.1. for new products
5.2.2.3.2. context dependent
5.3. traditional approach
5.3.1. sampling / trial & error
5.3.2. asking
5.3.2.1. peers
5.3.2.2. experts
5.4. modern approach
5.4.1. "wisdom of the crowd"
5.4.2. collaborative filtering
5.4.3. analysis of shopping patterns
5.4.3.1. user/item nearest-neighbor
5.4.4. real-time access to experts
5.5. in tourism
5.5.1. challenges
5.5.1.1. improved user involvement
5.5.1.2. profile management
5.5.1.2.1. transparent
5.5.1.2.2. extended
5.5.1.3. standard templates for travelers' profiles
5.5.1.4. real-time communication integration
5.5.1.5. justify recommending being extra paid
5.5.1.5.1. sophisticated algorithms
5.5.1.5.2. complex computing power
5.5.1.6. simplify and quicken the proccess
5.5.2. background
5.5.2.1. tourist search queries
5.5.2.1.1. complex
5.5.2.1.2. difficult to articulate
5.5.2.2. individuals represent different
5.5.2.2.1. types
5.5.2.2.2. preferences
5.5.2.3. desitinations
5.5.2.3.1. patterns of complex sets
5.5.2.3.2. very individual
5.5.2.3.3. idea
5.6. serendipity?
5.6.1. = finding something good without looking for it
5.6.2. based on economical utility theory
5.6.3. consideration set of each user
6. filter bubble
6.1. causes
6.1.1. depression
6.1.2. extreme polarisation
6.2. google uses
6.2.1. 57 factors
6.2.1.1. location
6.2.1.2. ethnicity
6.2.1.3. age
6.3. you see what you WANT to see
6.3.1. most likely to click
6.3.1.1. $$$
6.3.2. not same as others
6.3.3. less effort
6.3.3.1. to reinforce current view
6.3.3.2. rather than challenge
6.4. example of Malaysian plane
6.4.1. world believes it's Russia
6.4.1.1. in Russia only 3% belive that
6.4.2. in Russia they say it's Ukraine
6.4.3. two different views
6.5. ~ echo chamber
6.6. blame
6.6.1. ourselves first
6.6.2. then companies
6.6.2.1. google
6.6.2.2. facebook
7. long tail
7.1. explained economically by
7.1.1. costs
7.1.1.1. production
7.1.1.2. inventory
7.1.1.3. marketing
7.1.1.4. search/information
7.1.1.4.1. people search until the cost of the search is lower than potential gain
7.1.2. demand patterns
7.1.3. assortment planning/optimalization
7.2. strategies
7.2.1. blockbuster
7.2.1.1. airport bookshop
7.2.1.2. only bestseller
7.2.2. full liner
7.2.2.1. amazon
7.2.2.2. everything
7.2.3. niche focus
7.2.3.1. Soda Pop
7.2.3.2. only long tail
7.3. goods categories
7.3.1. search
7.3.1.1. technical devices
7.3.2. experience
7.3.2.1. information
7.3.2.2. services
7.3.3. trust
7.3.3.1. medication
7.4. technology impact on costs
7.4.1. on supply
7.4.1.1. inventory
7.4.1.2. marketing
7.4.2. on demand
7.4.2.1. search tools
7.4.2.2. price comparison
7.4.2.3. recommender systems
7.4.2.4. peer review
7.5. Three Rules
7.5.1. Make Everything Available.
7.5.2. Cut the price in half. Now lower it.
7.5.3. Help me find it.
8. bundle 2.0
8.1. examples
8.1.1. NYT
8.1.2. Office 365
8.1.3. google
8.1.3.1. gmails
8.1.3.2. maps
8.1.4. amazon
8.1.4.1. prime
8.1.4.2. kindle unlimited
8.1.5. netflix
8.1.5.1. intermediary
8.1.5.1.1. content owners
8.1.5.1.2. consumers
8.1.5.2. need to balance out
8.1.5.2.1. cost of licencing
8.1.5.2.2. number of subscriptions (and fees)
8.1.6. academic publications
8.2. relating to canvas
8.2.1. customer segments
8.2.1.1. segment-specific bundles
8.2.2. VP
8.2.2.1. bundle as VP
8.2.2.2. price convenience
8.2.3. channels
8.2.4. customer relationships
8.2.5. streams/costs
8.3. perspectives
8.3.1. economic
8.3.1.1. effective profit maximizing tool
8.3.1.2. WTP factor
8.3.1.2.1. scenario 1
8.3.1.2.2. scenario 2
8.3.1.3. demand is more...
8.3.1.3.1. homogeneous
8.3.1.3.2. predictable
8.3.1.4. minimal costs of...
8.3.1.4.1. product beyond first copy
8.3.1.4.2. communication (distribution)
8.3.1.4.3. bundling
8.3.1.4.4. storage
8.3.1.5. key advantage
8.3.1.5.1. in competing for
8.3.1.5.2. deterring entry
8.3.1.5.3. capturing close to 100% market share
8.3.2. strategy/business model
8.3.3. social impact
8.4. types
8.4.1. volume discount
8.4.1.1. 2 for 1
8.4.2. forced
8.4.2.1. CD for album
8.4.2.2. MS Office
8.4.2.3. newspaper
8.4.3. subscription (vs PPU)
9. customer relationship
9.1. always A FEELING
9.2. main types
9.2.1. committed partnership
9.2.2. enslavement
9.3. Porter's Competetive Advantage Model
9.3.1. Primary Activities
9.3.1.1. logistics
9.3.1.1.1. inboud
9.3.1.1.2. outbound
9.3.1.2. operations
9.3.1.3. marketing + sales
9.3.1.4. customer support
9.3.2. Support Activities
9.3.2.1. HR
9.3.2.2. technology
9.3.2.3. procurement
9.3.2.4. firm infrastructure
9.4. the model
9.4.1. gain creator
9.4.2. pain relievers
9.4.3. products/services
9.5. elements of value
9.5.1. 30
9.5.2. the more the better
9.5.3. types
9.5.3.1. functional
9.5.3.1.1. saves time
9.5.3.1.2. organizes
9.5.3.2. emotional
9.5.3.2.1. nostalgia
9.5.3.2.2. rewards me
9.5.3.3. life changing
9.5.3.3.1. hope
9.5.3.3.2. self-actualization
9.5.3.4. social impact
9.5.3.4.1. self-transcendence
9.6. stages
9.6.1. single interaction
9.6.2. chain of interactions
9.6.3. microineraction
10. sharing economy
10.1. examples
10.1.1. airbnb
10.1.2. parkatmyhouse
10.1.3. kickstarter
10.1.4. bookswapping
10.1.5. bike sharing
10.1.6. wikipedia
10.2. drivers
10.2.1. renewed belief in importance of community
10.2.2. torrent of P2P social networks, with real-time technologies
10.2.3. pressing unresolved envoirnmental concerns
10.2.3.1. reduce
10.2.3.2. reusue
10.2.3.3. recycle
10.2.4. global recession that shocked consumer behaviours
10.3. differences
10.4. reflection on aspects
10.5. models
10.5.1. redistribution (recycling)
10.5.2. collaborative lifestyles
10.5.3. product service systems
10.5.3.1. uber
10.6. network effects
10.6.1. positive
10.6.1.1. content
10.6.1.2. demand
10.6.1.3. variety of offers
10.6.2. negative
10.6.2.1. increased competition
11. disruptive innovation
11.1. definition
11.1.1. allowing a whole new population of consumers to access good that was previously accessible to only those with a lot of money (or skill)
11.2. disruptive technologies
11.2.1. mobile internet
11.2.2. IoT
11.2.3. cloud
11.2.4. robotics