Presentation: Philips

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Experiment Design Moving from ideas to business

Dylan EvansSenior Design Lead for Digital User ExperienceNovember 24th 2016

© Philips 2016

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Twitter @veluuria

Where I started…Moving from fields to offices

There is no such thing

as a failed experiment...

…only experiments with unexpected outcomes.

Buckminster Fuller

Why?

On Experimentation

In a lot of ways building a company is like following the scientific method. You try a bunch of different hypotheses, and if you set up the experiments well, then you kind of learn what to do…

We invest in this huge testing framework. At any given point in time, there’s not just one version of Facebook running in the world. There’re probably tens of thousands of versions running because engineers here have the power to try out an idea and ship it to maybe 10,000 people or 100,000 people. And then they get a readout.

As humans, we:

3. When successful, assume we know what made it successful

2. Inflate the impact of a success1. Overestimate the probability of success

If we’re so biased,

how do we inform the

decision to invest?

Validated learning…

… is a process by which we learn by experimenting with an idea and

measuring it to validate its effect.

By using validated learning we can create the best business recommendation based on how it touches:

• the consumer• the business

A point about learning…

Unconscious Incompetence

Conscious Incompetence

Conscious Competence

Unconscious Competence

Ignorance is bliss

I’m not doing it

right!

I can do it if I try

To learn, we must experiment

…is about finding what works best, and quickly.

Experimenting…

…creates the opportunity to

explore multiple directions,

choose the bestand refine it.

Experimenting helps…

Discover fatal flaws early,

before all

time and money has been spent

Reduce the risk of keeping things untested and…

Experimenting helps…

(Highest Paid Person’s Opinion)

Experimenting helps…

Overcome opinion-led decision

making by HiPPOs

How?

Each experiment tests a falsifiable hypothesis.

Focus on speed for faster validated learning.

Experiment Design

Whyweneedtoexperiment

• AShumans,we:• 1. Overestimateprobabilityofsuccess2. Inflatetheimpactofasuccess3. Whensuccessful,assumeweknowwhatmadeitsuccessful

• Changingenvironment

Typical graph for development

Options for Success

Cost of change

Time Launch

Am

ou

nt

Planning

Costs increase, options decrease

The first principle is that you must not fool yourself - and you are the easiest person to fool.

Richard Feynman

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hypothesisPronunciation: /hīˈpäTHəsəs/

NOUNA supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation

assumptionPronunciation: /əˈsəm(p)SH(ə)n/

NOUNA thing that is accepted as true or as certain to happen, without proof.

Assumption 1

Hypothesis1

Hypothesis2

Hypothesis3

Hypothesis4

Experiment1

Experiment3

Experiment2

Break assumptions down in to hypotheses and experiments to gain coverage

It’s child's play

Children iterate towards a solution through trial and error

Yourjourney

Incrementing vs. Iterating

Idea Business

Specify hypothesis

Design experiment

& actions to be taken with output

Run test and take actions

The Experimental Design iterative learning loop

State what we believe to be true and required for the offer’s success

Choose a methodology define the measure and set a target and actions

Run test, capture the outcomes and follow actions to be taken

Prioritise!

If hypothesis is confirmed, we persevere and GO.

If falsified, we pivot and change the proposition.

What will kill the proposition first?

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1

Idea BusinessMany, many iterations

Exp 1 Exp 2 Exp 3 Exp 4

Experiment along the journeyCheck if the performance matches the promise

Idea BusinessMany, many iterations

VideoAdvert(A/B)

Web Page(A/B)

PaperPrototype

1 Placed Facebook ads 2 Clicked through to Landing Page 3 Sign-up

Sequence experiments to test the future experience

4 Recruited for beta product test

Prototypes are the engine of experimental design

Making stuff deepens our thinking and drives ACTION

If you want to make something great, start making.

Tom Kelley, IDEO

Having stuff means we can share with people who will “get it” more easily

We can iterate and make better development decisions

1 2 3

‘‘

The purpose of a Minimum Viable Proposition (MVP) is to maximize learning per euro we spend*.

* using customers and not testers

Real“Test” products

Consumerperception

Our perception

MVP 1.0

Prototypes

€/real & LCM

1.0

Propositions on the market

MVP MVP

Learning tools

MVPs are prototypes that customers believe to be real

Proto A Proto B Proto C Proto DProto AProto C

Experts can guide to the right experiment design

Low Fidelity - FASTER

Buy Use

High Fidelity - SLOWER

Wizard of Oz

ConciergeImposter Judo

Analog/Physical

Dry-Wallet High Hurdle

Video Trailer

Crowd-Funding

Pitch

Landing page

Qualitative interviews / groups

Survey

Web Prototype

Paper Mockup / POP

Keynote / InVision Prototype

Online Ads

TypeForm Landing

Native OS Prototype

Role Play

QuantitativeProduct Usage

tests

Technical / sensory testing

BASES / Concept test

Classic methodsRecent digital-enabled methods

Shop alongs

© Philips 2016

Example journey

Exp 1 Exp 2 Exp 3 Exp 4

Experiment along the journeyCheck if the performance matches the promise

Idea BusinessMany, many iterations

Video

Concept video

When we involve real customers, we need to engage them through storytelling

Addpic

1. Create a story2. Make the video3. Fix the video

Toocomplex?

A simple structure is your friend:Confrontation/tensionEnlightenment/ChangeExplorationClosure } e.g. try a four

act structure

Exp 1 Exp 2 Exp 3 Exp 4

Experiment along the journeyCheck if the performance matches the promise

Idea BusinessMany, many iterations

VideoAdvert(A/B)

Web Page(A/B)

A/B testBig directionsIn the early stages, it’s not a small variable vs. small variable (aka optimisation)

We have to answer and find the big directions before we can optimise.

Choose the best channel for your communication

http://www.growthtribe.io/blog/brass-method-your-ultimate-guide-to-prioritising-which-customer-acquisition-channel-to-test-first/

Facebook isn’t always the right channel to reach your audience.

AnalyticsHow many & when?

- e.g. Google Analytics

- e.g. Advert analytics

What did they do?

- E.g. Hotjar

n.b. The numbers never match

Exp 1 Exp 2 Exp 3 Exp 4

Experiment along the journeyCheck if the performance matches the promise

Idea BusinessMany, many iterations

VideoAdvert(A/B)

Web Page(A/B)

PaperPrototype

1st consultskills

2nd consulthabit

3rd consultLast resort

basic instruction one remedy one Talcum powder (messy but it works)

basic instruction two remedy two

gauge skill level advanced instruction

introduction to new skill error strategy

terminology understanding confront habit

surprising instruction

Concierge MVPTeam identified an advice model which appears to very effective

Paper Prototype

GoodBad

While the one on the left looks nicer, it is not usable.Iterate through your sketches, throw lots away, keep the best stuff.

How useful?Try http://popapp.in and see how quickly you can get a prototype running.

Use this to test navigation & meaning very early on. Use the results to iterate through a web app with full analytics. Use this to understand if a feature is worth building.

Your Team

Draw on expertise around you to:

Structure Effective Hypotheses

Identify the right Risks in the Idea - Elephant in the room

Ensure Stakeholders stay accountable to the Results

Create the ability to Run Quick, Iterative Experiments

Stop the experiment when you’ve collected the full data

Hire statistical knowledge (sample # you must use to find a significant result)

Run at same times - compare apples with apples

Create control variables across experiments

Integrate traditional testing where relevant

Build your individual expertise

Use clear assessment criteria (Desirability, Feasibility, Viability)

A TEAMMARKETING PROFESSIONALSDESIGNERS & STRATEGISTSTECHNOLOGY SPECIALISTSDEVELOPERSSUBJECT MATTER EXPERTSSTAKEHOLDERS

Closing

After each experiment, there are always 4 possible outcomes

1. GO You are confident that your hypothesis is valid and have the evidence to show it

2. Confirm

3. Pivot

4. STOP

You are confident that your hypothesis is correct but you need more evidence to support it

You no longer believe that this offer is a right for you to pursue at this time.

You believe in the vision but you need to re-visit the means & path to get to the vision

Experiment DesignKey Take Aways

KPI driven

Simple

As close to reality as possible

Prioritized

Statistically significant

Allowed to fail!

Experiments must be:

Build the whole journey

Speed is your ally. Perfection comes later

Your first experiment is a rehearsal

Your approach & mindset

Fail Fast, learn fast.

The only way to

proceed is to get

your feet wet

Thank you