Designing to Learn: Creating Successful MVP Experiments

Designing to Learn: Creating Effective MVP Experiments

Melissa Perri @lissijean | #LeanUXFest

Melissa Perri !

ProdUX Labs melissaperri.com

@lissijean

@lissijean#LeanUXFest

Define Design Develop Deploy

Traditional Product Development Cycle

Some learning

Very little learning

Most learning

DO NOT WANT@lissijean

@lissijean

Measure

@lissijean

@lissijean@lissijean

Traditional Process

@lissijean

MVP Process

@lissijean

Focus on problem not features.

Crappy products

Crappy products everywhere

@lissijean

Experiment

VALUE@lissijean

Setting Up Experiments

What is our goal?

What is your problem hypothesis?

What do we want to learn?

What’s the minimum we can build to learn?

How do we measure success?

What is our goal?

Increase traffic by 10%.

Increase sections visited by 40%.

@lissijean#LeanUXFest @lissijean

Increase existing customer engagement by 20%.

Your goal is to increase conference attendee satisfaction by 25%.

what’s your problem?

@lissijean

What’s your biggest problems at conferences?

FINDING THE PEOPLE I COULD

@lissijean

Introduce yourself & your biggest

problem.

@lissijean

Dot vote on the problems. Each person gets 2 votes.

FINDING THE PEOPLE I COULD

@lissijean

What is our goal?

Solving problems delivers value.

@lissijean

Shoppers who visit the site at least twice a month but

have not purchased.

CUSTOMER

{Customer}s want twitter-like messages in their feed.

PROBLEM

Customers want twitter-like messages in their feed.

Not a problem.

{Customer}s aren’t engaging with our site because they think

curators are not authentic.

PROBLEM

Shoppers want to save their items to a wishlist so they can

purchase them later.

Shoppers who are not ready to buy yet want to save items so they can easily purchase

them later.

Shoppers want to save their items to a wishlist so they can

purchase them later.

Shoppers who are not ready to buy yet want to save items so they can easily purchase

them later.

GOODBAD

CUSTOMER PROBLEM

Who is your customer?

What is their problem?

We think that we can achieve

if we solve

Hypothesis

PROBLEM CUSTOMER

What is our goal?

There’s a reason why they’re called

assumptions.@lissijean

What are the dependencies?

Will shoppers engage more if curators post authentic messages in the feed?

What do you want to learn first?

What is our goal?

There are many types of MVPs…

“Do customers have this problem?”

InterviewsGet out of the building and talk to people.

“Are customers interested in my

solution?”

Landing PageA pitch of your product, to gauge idea reception.

“What do customers value in the solution?”

ConciergeDelivering a service manually.

Delivering a service manually.Concierge

“Will people pay for my solution?"

Wizard of OzLooks real, but manual on the back end.

@lissijean

Subscription

@lissijean

Wizard of OzLooks real to the customer,

completely manual on the backend.

What is the minimum we can build to learn?

@lissijean

Every time you start with a minimum feature set, a

kitten dies.

@lissijean

What is the smallest amount you can build

to learn?

SMALLEST BUILD

What is our goal?

What’s the minimum we can build learn?

What does success

look like?

@lissijean

10% increase in adds to cart in A/B test.

@lissijean

How do you measure success?

SUCCESS METRIC

Iterate.

0% change over other products.

Increase existing customer engagement.

Customers aren’t engaging with our site because they think curators are not authentic.

PROBLEM

Will shoppers engage more if curators write

personal stories in emails?

What is the minimum we can build to test?

20% increase in purchases and CTR.

SUCCESS METRIC

Success!2x Open Rate 3x Purchases

Effort Learning

It’s all about the process.

“We should test that.”

@lissijean

Melissa Perri !melissa@produxlabs.com !Lots more info on: melissaperri.com !! @lissijean

Designing to Learn: Creating Successful MVP Experiments

Design

Transcript of Designing to Learn: Creating Successful MVP Experiments

Designing To Learn: Creating Effective MVP Experiments - Lean UX NYC 2014

13-1 Designing Engineering Experiments

Designing great products and the skinny on MVP, Minimum Viable Products

Designing Economic Experiments

Innovators toolkit 1 designing pedagogical experiments - 2

NOTE SHEET 1 – Designing Controlled Experiments

Designing and Conducting Phishing Experiments

Designing an MVP that works for your users - LeanUX NYC 2014

Designing Experiments, ANOVA and Correlation Coefficients

Evaluation Designing Controlled Experiments

Designing Experiments - Oxford Reproducibility School

Identifying variables designing experiments

Designing and Conducting Laboratory Experiments

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Designing Microarray Experiments