Index
A
A/B testing
Agile approach
Agile development
Analysis phase
checking
conclusion or headline result
data
evidence
SeeEvidence, examination
interpretations, results
result implications
false assumptions
improvement
intriguing patterns
knock-on effects
mini-retrospectives
missed opportunities
new knowledge
product strategy
B
Backlog of questions, prioritizing
broad backlog
deep backlog
value of answer
criteria
example
final score
why, ask
Backlog, reexamining
broadvs.
deep
business wider strategy
raw material
re-score and re-prioritize
Breaking new ground
baseline experiment
careful design
right question
what to work question
Broad backlog
Business stakeholders
C
Conditions
control
exploratory
motivating factor
Confirmation bias
D
Data analysis
Deep backlog
Design phase
E
Evidence, examination
answering, question
plausible answer
p value
significance level
health metrics
organizing
saving for later
Existing behavior analysis
current behaviors
data analysis
experimental approach
live experiment
Experiment
A/B tests
multiarmed bandits
multivariate testing
user research
innovation
resolve disagreement
Experimental mindset
Experiment card
communication
defined
front side
reverse side
Experiment-driven product development (XDPD)
basic process
benefit
challenge the premises
defined
design phase
hypothesis, define
low cost of failure
questions, importance
questions, new ideas
Experiment-ready questions
A/B tests
belief-led questions
exploratory questions
five Ws (and one H)
qualvs.
quant
scale of experiment
F
Fine-tuning, existing product
G
Google Data Studio
Google testing
H, I, J, K
Hypothesis
difference/change
exploratory questions
falsifiable
measurable
method-questioning-answering loop
statement
testable
XDPD
L
Lean approach
Lean UX
M
Measures
baseline experiments
choosing
health metrics
tracking
Method
A/B framework
health metrics
object of inquiry
running experiments, parallel
Method-questioning-answering loop
Minimum detectable effect (MDE)
absolute change
relative change
Minimum viable product (MVP)
definitions
maker’s privilege
minimum and viable
product development
viable, acceptable
viable product
Multi-team environment
experiment team
innovation team
product team
sharing knowledge
team size
Multivariate testing
N
Null hypothesis
O
Objectives and key results (OKR) framework
P
Planning phase
Principles
acknowledge
data informed
design, experiments
evidence, seek
experiment kick off
details
experiment cards
index card
stakeholders
team members
no failed experiments
shared understanding
strong opinions, loosely held
clear boundaries
solutionizing
usvs.
them situation
p value
Q
Qualitative user research
Question-based data analysis
R
Raw material
assumptions
claims
to experiment-ready questions
SeeExperiment-ready questions
ideas
knowledge gaps
Regular communication
analyzing, results
collaboration
distraction
experiment cards
prior warning
reminder of team or goals
soon-to-be-run experiments
target
S, T, U, V, W, X, Y, Z
Scale
baseline experiments
belief-led experiments
certainty
designing, experiment
exploratory experiments
certainty, patterns
precision/granularity
representative sample
minimum detectable effect
possible outcomes
precision
significance level
statistical power
Sharing and planning
setting targets
shareback session
sprint planning
stakeholders
structure, regular communication
SeeRegular communication
Simplest Useful Thing
simplest, minimum
thing, not product
useful
Sprint approach
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