Conversion Hotel 2016 - John Ekman

“We have come to earth to save humans from bad Conversion rates & Web sites that suck”

Traffic Outcomes

4

Your website is a leaky bucket

5

Conversion Rate Optimization is born

✓ Conversion Jam x 6 ✓ Conversion Manager x 200

+ 500 projects + 25 employees

A lot has happened since……

We are nr 1!

@conversionista Amsterdam Berlin Frankfurt London Munich Paris Stockholm Vancouver globaloptimizationgroup.com

>170 Conversion Experts in 10 countries

© Andre Morys, Web Arts AG www.web-arts.comFRANKFURT - HAMBURG - MÜNCHEN@morys Amsterdam Berlin Frankfurt London Munich Paris Stockholm Vancouver globaloptimizationgroup.com

W. Edwards Deming

„If you can't describe what you are doing as a process, you don't know

what you're doing.“

„A bad system will beat a good person every time.“

A process:whathow

sequence

The Optimization

wheel

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What is the one thing Organizations never lack?

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And what is believed to be the source of the BEST ideas?

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So here is your process

Creativity Ideas H.I.P.P.O Your BIG

launch

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What are the problems with this “method”

Not data-driven

Unclear where ideas come from and what they are supposed to

achieve

Hit or miss

Not a repeatable process

BIG problems

4 Data- Driven? Outcome-focused? Hit or miss! Process?

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Here’s our proposal

Creativity Ideas

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Here’s our proposal

Data Ideas

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Here’s our proposal

Data Hypotheses

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Ideas vs Hypotheses

An idea is a loosely formulated ambition

or direction with many possible

variations

An hypotheses is a structured idea that tells you: - Where it came from - How it’s supposed to work - What the intended result is

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The I.A.R. hypothesis formula

Insight

Action

Result

apps.conversionista.se

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So this is our process

Data Hypotheses

Our 4 BIG problems

We are data-driven

We focus on outcomes

There is something of a process

Still a “hit or miss” business

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What do these writers say?

“Validated learnings” “Empirical validation”

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Or in plain english

“Fire bullets. Then Canonballs.”

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The Optimization wheel

Data Hypotheses

Experiments

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Outputs

Data Hypotheses

Experiments

29

Compare to Build-Measure-Learn

Data Hypotheses

Experiments

Data Ideas

Code

Our 4 BIG problems

We are data-driven

We focus on outcomes

We have a process

We are agile

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Hey, we’re not done yet

Data Hypotheses

Experiments

NEW problems

3 The Why? The right project? The unknown?

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The Optimization wheel

Data Hypotheses

Experiments

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The Optimization wheel

Data Hypotheses

Experiments

The insights phase -

Understanding the Why

HypothesesData

Psychology -

Bridging the gap

Data Hypotheses

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How data and hypotheses interact

Data Hypotheses

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How data and hypotheses interact

Data Hypotheses

You come up with rough hypotheses built on best practices,

previous experience etc.

Then you qualify them with data

Start here

1.

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Add to wishlist. Great tool, but…….

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Add to wishlist. Great tool, but…….

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What does the data say?

Converts like crazy Aint nobody got time for that

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How data and hypotheses interact

Data Hypotheses

You dig down in your data to find patterns, anomalies, outliers.

Then you form hypotheses of WHY those patterns exist.

Start here

2.

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Case - IP telephony WTF!

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Case - IP telephony

Flag

What you get

Check

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And then you repeat until you’re done

Data Hypotheses

Psychology -

Bridging the gap

Data Hypotheses

How do we know we have: - All the data we need - The right data?

Data

Experiments

How do we know we have: - All the data we need - The right data?

Data

Experiments

Tools & Research

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Skistar (desktop) Eyetracking

Site catalystBig drop-off in the skipass purchase funnel

Eye trackingUser did not understand the pricing structure and decided to buy on arrival

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Form tracking

4,9 % Form conversion rate

63 % error rate

21 % refills on personnummer

1 ot of 3 is lost here

How do we know we are testing our best hypotheses?

Hypotheses

Experiments

How do we know we are testing our best hypotheses?

Hypotheses

Experiments

Prioritization

Our 3 NEW problems

We know the WHY!

We prioritise our best projects!

We have the right data!

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Build-Measure-Learn

Data Hypotheses

Experiments

PrioritizationTools & Research

Insights

Data Ideas

Code

BuildMeasure

Learn

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Data Hypotheses

Experiments

PrioritizationTools & Research

Insights

HOW!!!?????

Double loop testing

Design

DevelopDeploy & Monitor

Follow-up

Data Hypotheses

Experiments

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Do the maths

Estimated uplift

Testingtime

Tests per year

Compound Uplift

Beginner 5 %

Average Joe 10 %

Stellar 20 %

Based on 3000 daily visitors, 5% baseline conversion rate

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Do the maths

Estimated uplift

Testingtime

Tests per year

Compound Uplift

Beginner 5 % 138 days 3

Average Joe 10 % 35 days 10

Stellar 20 % 9 days 40

Based on 3000 daily visitors, 5% baseline conversion rate

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Do the maths

Estimated uplift

Testingtime

Tests per year

Compound Uplift

Beginner 5 % 138 days 3 16 %

Average Joe 10 % 35 days 10 250 %

Stellar 20 % 9 days 40 150 000 %

Based on 3000 daily visitors, 5% baseline conversion rate

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Shotgun testing

Alibi testing

One hit wonder testing

Double loop

testing

Testing velocity

Win rate

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Shotgun testing

Alibi testing

One hit wonder testing

Double loop

testing

Testing velocity

Win rate

Testing Blues

Testing Blues

Testing Blues

General persuasion techniques

Customer journey

Behavioural typology

OUR customers (personas)

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The 6 questions a visitor will ask

Relevance Value

Trust Action

Ease Assurance

“Am I in the right place?”

“What can I do now?”

“Why should I do this, right here and right now?”

“Can I trust them?”

“How hard will this be?”

“If I do this now, what if….?”

@morys Amsterdam Berlin Frankfurt London Munich Paris Stockholm Vancouver globaloptimizationgroup.com

R E D U C E F R I C T I O N R A I S E M O T I V AT I O N

Average Uplifts of Experiments

67

The 6 questions a visitor will ask

Relevance Value

Trust Action

Ease Assurance

“Am I in the right place?”

“What can I do now?”

“Why should I do this, right here and right now?”

“Can I trust them?”

“How hard will this be?”

“If I do this now, what if….?”

Increase motivation

Reduce friction

Explore

Evaluate

Finish

Confirm

Visitor goals

Our classic funnel

Our classic funnel

The funnel became a shell

Explore

EvaluateFinish

Confirm

The funnel became a shell

Share

The acquisition gap

Relevance

Persuasion Techniques““Am I in the right place?””

Relevance

Keeping the scent

Implicit codes

Limiting cognitive load/Choice paralysis

Brand recognition

E

EF

C

4 Data- Driven! Outcome-focused! Hit or miss Process

3+

The Why! The right project! No unknowns!

@conversionista Amsterdam Berlin Frankfurt London Munich Paris Stockholm Vancouver globaloptimizationgroup.com

Help me solve my toothbrush problem

john@conversionista.se

john@conversionista.se