Analytics – The next Level

Marcel Martschausky / Kay Lehmann / Markus Nagel

Levels of Data Driveness

Analog – Multi Retailers are here

TRANSFORMATION

Decision Preparation

OUTPUT

Marketing Actions

INPUT

Data Collection

Website

Mobile

Apps

Offsite

CRM

SCM/ERP

Payment

3rd Party

Market

Research

Marketing

Teams

Onsite

Mobile

Apps

Display

SEM/SEO

TV

Email

Social

Media

Data transformation process needs weeks here and is driven only by humans

TRANSFORMATION

Decision Preparation

OUTPUT

Marketing Actions

INPUT

Data Collection

Website

Mobile

Apps

Offsite

CRM

SCM/ERP

Payment

3rd Party

Data

Warehouse

Business

Intelligence

Marketing

Teams

Onsite

Mobile

Apps

Display

SEM/SEO

TV

Email

Social

Media

Digital Tier 1 – Most E-Commerce Players are here

Data transformation process needs days here and is driven by humans (BI for decision) and technology

(DWH for transforming the data)

Digital Tier 2 – Some really developed Players are here

TRANSFORMATION

Decision Preparation

OUTPUT

Marketing Actions

INPUT

Data Collection

Website

Mobile

Apps

Offsite

CRM

SCM/ERP

Payment

3rd Party

Data

Management

Platform

Marketing

Teams

Onsite

Mobile

Apps

Display

SEM/SEO

TV

Email

Social

Media

Data transformation process will be done in realtime here and is driven by technology (DMP). BI is only

needed to set up the technology in the right way.

Digital Tier 3 – This is an Unicorn right now

TRANSFORMATION

Decision Preparation

OUTPUT

Marketing Actions

INPUT

Data Collection

Website

Mobile

Apps

Offsite

CRM

SCM/ERP

Payment

3rd Party

Marketing

Teams

Offline Data

Stores

Cars

…

Onsite

Mobile

Apps

Display

SEM/SEO

TV

Email

Social

Media

Offline

Retail

Callcenter

Cars

…

Data

Management

Platform

Data transformation process will be done in realtime here and is driven by technology (DMP). Additional

offline touchpoints will be digitalized.

Improve Your Analytics to become a strategically relevant asset

The race is won, if Analysts are

able to turn optimization potential

into actions and measure there

success or adjust plans

Analysts are not a Cost Center!

We as Analysts are not

Controllers for data.

Seeking for more optimization

potential is the first half of the

race

Hard skills could be learned, Soft

Sills are unbelievable more

important

Avoid discussions about data

quality and have your pitchdeck

always ready

Make sure the marketing

department has the right people

on board

How to find Target Groups

Individuality comes with Combinations

ATTRIBUTES ENGAGEMENT

REVENUE

Individuality comes with Combinations

ATTRIBUTES Gender

Age

Location

Demographic Info

Individuality comes with Combinations

New User

Customer

Lead

Micro Conversions

Individuality comes with Combinations

Page Groups

Product Groups

Brands

Price Groups

Channels

Individuality comes with Combinations

ENGAGEMENT

REVENUE

Our

Focus

Today

Groups for Engagment and Revenue

Improve Activity Improve Performance Top Groupof no Interest

currently inactive

low performance

currently inactive

high performance

currently active

low performance

currently active

high performance

Groups for Engagment and Revenue

Improve Activity Improve Performance Top Groupof no Interest

RFE-/RFM-Groups

113 / 122 / 123 /

133 / 212 / 213 /

222

RFE-/RFM-Groups

111 / 112 / 121 /

131 / 132

RFE-/RFM-Groups

211 / 221 / 231 /

311 / 312 / 313 /

321 / 322 / 331

RFE-/RFM-Groups

223 / 232 / 233 /

323 / 332 / 333

Groups for Engagment and Revenue

Improve Activity Improve Performance Top Groupof no Interest

We want to keep

them and get

them to buy/visit

more

Let us try to keep

our costs down

with this user type

How do we get

these guys back?

Reward them as

you want to keep

them and get

more people like

them

Combination

ENGAGEMENT

REVENUE

REVENUE ENGAGEMENT

engagement activity

engagement performance

order activity

order performance

4x4 Groups

Combination Examples

Browsers

Browsers with Potential

Sleeping Top Customers

Churning Top Customers

inactive low revenue

active high engagement

inactive high revenue

active high engagement

High Potential Customers Churned Customers

active low revenue

active high engagement

active high revenue

active low engagement

inactive high revenue

inactive low engagement

inactive low revenue

inactive high engagement

highly engaged with the website

motivated to come back

no order intent

stuck in the process

can be targeted onsite

good potential with low costs

Example: Browsers

Browsers

inactive low revenue

active high engagement

Example: Browsers

Scenario:

Reducing the Basket Abandonment

Rate by 15% for 30% of these visitors

would lead to an overall revenue

increase of 2,2%

Visitors: 8%

Conversion Rate: 5%

Avg. Basket Value: 100€

Product Views per Visit: 4

Basket Abandonment Rate: 70%

Avg. Product Value: 40€

Browsers

inactive low revenue

active high engagement

Example: Browsers

€What and how

did they buy last

time?

What are they

interested in

now?

What is the

problem?

Browsers

inactive low revenue

active high engagement

Example: Browsers

€What and how

did they buy

last time?

What are they

interested in

now?

What is the

problem?

Discover our

Sale

Products

You might be interested in…

Get 10% off!

€

You forgot

something

Browsers

inactive low revenue

active high engagement

Let‘s get active!

Use Case 1

Target Group

Goal

Channel

active low revenue

inactive high engagement

We want to get 10 more visits from

25% of this user group.

Newsletter

Content Product reco with products from category 2

This would bring us 1,07% more

revenue overall

WHY?

We want to reactivate them and it is a

good performing channel for this group.

This category got many product views

from this group but wasn‘t but that often

Addition Check payment obstaclesThis group has a low conversion rate for

the payment step

Use Case 2

Target Group

Goal

Channel

inactive low revenue

active high engagement

We want to get an average CR for

20% of this user group.

Onsite

Content 1 Product reco with products from category 5

This would bring us 3,18% more

revenue overall

WHY?

This user group is already very active on

our website.

This category has the best conversion

rate for this group

Content 2 Discount in basketThis group has a high basket

abandonment rate that needs to be

improved

Use Case 3

Target Group

Goal

Channel

inactive low revenue

active high engagement

We want to get an average CR for

20% of this user group.

Onsite / Retargeting

Content 1

This would bring us 3,18% more

revenue overall

WHY?

This user group is already very active on

our website.

Content 2 Retargeting of basket abandonersThis group has a high basket

abandonment rate that needs to be

improved

Reco for category 5 at category 1 pagesThe group shows high interest for

category 1 but has its highest conversion

rate for category 5

Incentives for newsletter and social media

Use Case 4

Target Group

Goal

Channel

inactive high revenue

active high engagement

We want 25% of them to become

part of the top group

Onsite

Content

This would bring us 2,40% more

revenue overall

WHY?

This user group is already very active

(interested) on our website.

Although they come very often to our

website we have more chance to guide

them via e-mail or social media

Product reco for category 1

Use Case 5

Target Group

Goal

Channel

inactive high revenue

inactive high engagement

We want 25% of them to do 10

more visits

Newsletter

Content

This would bring us 1,20% more

revenue overall

WHY?

We have to bring them back to our

website and newsletter has a good

performance for them

Although they have not bought much

from this category it‘s the one they are

most interested in

Next StepFind regular activites for them (content,

competitions, social media etc.)

It is a good performing user group with

lack of activity. So we have to keep them

active

Appendix

Example Data: User Groups

Revenue Engagement Visitors % Visits % PI per Visit CRBasket

Value Avg.

Product

View per

Visit

Add to

Cart Rate

Aban-

donment

Rate

Avg.

Product

Value

No Interest Super User 15,69% 38,65% 13,88 5,94% 116,42€ 6,20 11,00% 61,61% 26,40€

Activity Super User 5,63% 17,57% 17,22 10,78% 173,42€ 9,01 14,32% 49,63% 28,76€

Performance Activity 4,42% 1,53% 22,69 25,14% 117,81€ 9,92 16,46% 34,34% 27,64€

Activity Activity 3,19% 3,18% 24,30 22,91% 201,72€ 12,97 17,23% 32,87% 30,80€

Performance Super User 2,92% 5,23% 16,98 8,86% 115,18€ 7,70 12,04% 55,86% 24,95€

Performance Performance 2,87% 0,79% 20,81 27,49% 129,85€ 9,77 16,16% 22,87% 29,30€

No Interest Performance 2,73% 1,48% 15,30 15,41% 126,59€ 6,33 15,11% 29,71% 29,00€

Total Total 100,00% 100,00% 16,98 11,85% 141,33€ 8,02 13,69% 46,16% 28,34€

Example Data: Scenarios

Revenue Engagement Visitors % Scenario Revenue Increase

No Interest Performance 2,73% 20% with 20% more PI per Visit 0,07%

No Interest Super User 15,69% 20 % with Average CR 3,18%

No Interest Super User 15,69% 30% with 15% lower Basket Abandonment Rate 5,94%

Activity Activity 3,19% 25% with 10 more Visits 1,20%

Activity Activity 3,19% 10% with 30% more Visits 0,26%

Activity Super User 5,63% 30% with Average CR 0,58%

Activity Super User 5,63% 25% becoming Top Group 2,40%

Performance Activity 4,42% 25% with 10 more Visits 1,07%

Performance Activity 4,42% 20% with 20% more Basket Value 0,11%

Performance Performance 2,87% 15% with 25% more Product Views per Visit 0,06%

Performance Super User 2,92% 25% becoming Top Group 2,99%

Example Data: Product Views

Product Views (last 30 Days)

CategoryNo Interest /

Super User

Activity /

Super User

Performance /

Activity

Activity /

Activity

Performance /

Super User

Performance /

Performance

No Interest /

Performance

Cat 1 17,09% 18,79% 7,34% 12,95% 17,77% 8,17% 12,04%

Cat 2 7,51% 6,91% 12,20% 11,11% 6,93% 13,73% 11,29%

Cat 3 8,52% 8,97% 7,33% 7,18% 8,88% 8,03% 7,74%

Cat 4 8,14% 8,40% 7,48% 7,61% 8,29% 7,08% 7,36%

Cat 5 7,76% 7,93% 7,08% 6,98% 8,05% 7,18% 7,34%

Example Data: Purchased Products

Purchased Products (last 180 Days)

CategoryNo Interest /

Super User

Activity /

Super User

Performance /

Activity

Activity /

Activity

Performance /

Super User

Performance /

Performance

No Interest /

Performance

Cat 1 7,00% 13,01% 3,31% 5,29% 5,99% 4,32% 3,84%

Cat 2 3,18% 3,91% 5,21% 5,59% 2,82% 7,67% 6,41%

Cat 3 4,76% 5,33% 6,51% 4,48% 8,91% 9,85% 5,57%

Cat 4 3,61% 3,89% 5,68% 3,57% 5,17% 6,40% 3,65%

Cat 5 7,32% 7,96% 7,74% 7,07% 7,85% 8,61% 6,77%

Example Data: Product Type

Purchased Products (last 180 Days)

Product TypeNo Interest /

Super User

Activity /

Super User

Performance /

Activity

Activity /

Activity

Performance /

Super User

Performance /

Performance

No Interest /

Performance

Regular 43,51% 51,02% 50,67% 48,95% 49,49% 56,81% 47,87%

Sale 37,60% 29,02% 21,83% 28,59% 27,89% 15,40% 28,18%

New 18,88% 19,95% 27,49% 22,46% 22,62% 27,73% 23,93%

Example Data: Channel

Entries (last 180 Days)

ChannelNo Interest /

Super User

Activity /

Super User

Performance /

Activity

Activity /

Activity

Performance /

Super User

Performance /

Performance

No Interest /

Performance

Direct 33,54% 36,61% 28,97% 32,19% 36,62% 28,68% 23,76%

SEO 15,79% 13,80% 26,48% 18,96% 13,87% 29,37% 27,43%

SEM 8,27% 6,53% 10,30% 9,52% 6,21% 10,80% 14,82%

Display 10,77% 7,41% 10,61% 7,86% 8,43% 10,58% 18,25%

Newsletter 6,38% 7,32% 10,70% 13,02% 5,78% 7,15% 7,79%

Example Data: Checkout

Conversion Rate (last 30 Days)

Funnel StepNo Interest /

Super User

Activity /

Super User

Performance /

Activity

Activity /

Activity

Performance /

Super User

Performance /

Performance

No Interest /

Performance

Basket 45,59% 55,85% 85,55% 82,10% 67,34% 85,73% 70,36%

Payment 73,13% 75,73% 76,42% 77,96% 75,97% 76,90% 74,12%

Confirmation 75,71% 77,63% 89,32% 88,07% 84,75% 90,98% 76,74%

Thank you - - - - - - -

Thank you for your attention

Marcel Martschausky / Director Consulting / marcel.martschausky@webtrekk.com

Kay Lehmann / CEO Converlytics / kay.lehmann@converlytics.com

Markus Nagel / Senior Consultant / markus.nagel@webtrekk.com