Performance MetricWorkshop

Spencer AltmanHead of Business Consulting

Webtrekk

What are your KPIs?

KPI

Report

Training

Communicate

Explain/Fix/What does it mean?

Justify you did a good jobY

our

Effo

rt

What is the purpose of your

website?

Performance

Metrics

KPIs

KPI Drivers

Optimisation Insights

?

Source : iStock

Videos(€)

Media Views

Library Media Views

Live Streams

Qty Reminde

r

If Event is in the future, would a‘Add to my Calendar’ button increase the number of people watching the Livestream?

How about a mobile Push Notification?

Add to My Calendar

Example – Media / Content

Example – BankingPurpose of Website

Increase € in Current/Savings Accounts

Current/Savings Account

s (€)

Qty Current/Savings Account

s

Qty Clicks

Compare

Table

Avg Amount

per Account

Products

Without Tables

Example – BankingPurpose of Website

Increase Share of Wallet of Customers with > €50K Savings

Increase # of Products per Customer of Customers with > €50K Savings

Share of Wallet

(€)

Qty Users

Investing

CR% TargettedEmail

Avg Amount Invested

Step 2 : Determine Performance Metrics

Step 1 : Why is the website there?

Step 4 : Build Performance Analytics Tree

Step 3 : Determine Initial KPIs per Performance Metric

Step 5 : Prioritize Performance Analytics Tree

Step 6 : Implement Performance Analytics Tree

Spencer AltmanHead of Business Consulting

Berlin, Germany

+49 (0)160 928 707 72spencer.altman@webtrekk.com

@spenceraltman

Amsterdam | Beijing | Berlin | Frankfurt | Madrid | Milanwebtrekk.com

Digital Analytics : Organisational Issues

Spencer AltmanHead of Business Consulting

Webtrekk

Source : iStock

Source : iStock

Source : iStock

Source : iStock

Keys to Getting Value Out of Data

• Head Management in the Data

• Dedicated Analytics resource/team

• Clear & powerful KPI structure

• All teams in the value chain sit together

CEO

CFO COO

Category Managers

CIO CMO

Digital Marketing

Analytics Channels

Display

AdWords

Social

Affiliate

Retargetting

Trafficing

17 Total Channels

SEO Creative/ UX Mobile

Web Apps

iOS Phone

iOS Pad

Android

CRM

Data Mining

Email

Customer Database

Customer Relations

Offline Marketing

Market Research

CEO

CFO COO

Category Managers

CIO CMO

Digital Marketing

Analytics Channels

Display

AdWords

Social

Affiliate

Retargetting

Trafficing

17 Total Channels

SEO Creative/ UX Mobile

Web Apps

iOS Phone

iOS Pad

Android

CRM

Data Mining

Email

Customer Database

Customer Relations

Offline Marketing

Market Research

Color Key

Needs Reports/Analytics

No Need for Reports/Analytics

URM / CRM

Analytics

Creative / UX

Site

Man

agem

ent

Emai

l

SEO

Dis

play

AdW

ords

Soci

al

Affilia

te

Reta

rgetti

ng

Traffi

cing

All O

ther

Offs

ite C

hann

els

Mob

ile

Market Research

Offl

ine

Customer Relations

Potential Marketing Matrix Structure

Extended Marketing Matrix Structure

URM / CRM Category Managers

Analytics

Creative / UX

Market Research

Clot

hing

Acce

ssor

ies

Cate

gory

X

Customer Relations

All Channels (Online & Offline)

Analytics in the OrganizationRecommendation :

Each Marketing and Category team is trained on using Webtrekk and getting value from the Analytics data.

Plus, there should be at least one person per team who is designated as expert in Webtrekk system. This person is the main contact to the Reporting/Analytics team for the following questions impacting their team:

• Tagging• Training/Reporting• Analysis

CRM

Basic Training

+ 1 Expert

Site Mgmt

Basic Training

+ 1 Expert

Category X

Basic Training

+ 1 Expert

Team X

Basic Training

+ 1 Expert

Reporting /Analytics

Team

Analytics Team BreakdownResponsibility

Report Needs / Training of Other Groups / Report Generation

Tagging / Implementation Concept / Implementation Management

Analysis & Insights

Skill Need

Expert / Familiarity with Web Analytics and Digital Marketing Tools

(Recommended : 2 years experience)

Javascript/HTML/More Technical;Web Analytics tagging preferred

(Recommended : 2 years experience)

Business Analyst / Evangelist /Familiarity with Data Analysis more important

than Web Analytics Knowledge; Communicator with Top Managers

(Recommended : 5 years experience)

Recommendation : One person per each responsibility. At the beginning of most projects, all 3 responsibilities are covered by a single person. This team ensures uniformity of analytics processes across the different teams using analytics data.

Spencer AltmanHead of Business Consulting

Berlin, Germany

+49 (0)160 928 707 72spencer.altman@webtrekk.com

@spenceraltman

Amsterdam | Beijing | Berlin | Frankfurt | Madrid | Milanwebtrekk.com

URM:RFM / RFE ModelsIn Practice

Conrad MorbitzerSenior Business Consultant

Webtrekk

What is URM? Why URM?

Using RFM / RFE results

What is RFM / RFE?

How to configure RFM / RFE

Example of URM in Action

Agenda

30

What is URM?Why URM?

Right content.

Right time.

Right device.

Right channel.

Right location.

Owned DataPersonalisation

Engine

Where we are heading

BI Data

CRM Data

Web Analytics

Data

Other Data Sources

??

A Common Scenario

URM : Driving Profit RETARGETING

CHURN PREDICTION

PURCHASE

SMART LANDINGPAGES

RECOMMENDATION

EXIT

RETURNING BUYERS

Analytics/ URM

Website

Display

Email

Mobile (incl.Push)/In-Store

Social Media

Store

Call Center

Post/Paper

Retargetting

Website & Apps

CRM

Email

Social Media

Other

Display

RetargettingDWH & Other

Systems

Marketing Automation

SearchSearch

Channel Overview

URM enables…

More new customers

1

More profit:

• per customer

• per transaction

• per visit

2 3

Reduce time

between transactions

Last Transaction

Last Visit

Next Transaction

Next Visit

37

What is RFM / RFE?

Limited Resources Information Budget Interactions with the User/Customer

Optimize Available Resources Example: Generic Newsletter

Costs Response rate Lose relevance with your customers Dislike from your customers Destroy your e-mail sender rating

Be Relevant and Profitable

Why RFM/RFE?

Various models, just one example (Customer Life Time Value) High price and frequently returning customers

1 purchase for €1000

10 purchases for €100

100 purchases for €10

1000 purchases for €1 Variable and Fixed Costs

Customer Segmentation

What is the RFM Model?

Proven Scoring model for defining customer value

Based on historical customer data

Goals:

Prediction from purchase likelihood and return rates

Segmentation based on customer value

Target customers/users with right message

RFM Model

Recency

When was the last purchase?

Frequency

How often was purchased?

Monetary

What was the total order value?

Recency Score

Frequency Score

Monetary Score

RFM Score

RFM Model

Recency

When was the last visit?

Frequency

How often are the visits?

Engagement

What was the total engagement?

Recency Score

Frequency Score

Engagement Score

RFM Score

RFE Model

3 Rating Groups per section

2 threshold value split scores into the 3 groups

Exact limits are company and case specific!

Customers

Rating Group 1

Threshold 1 Threshold 2

Rating Group 2 Rating Group 3

RFM Model Scores Explained

Threshold 1 Threshold 2

1

bad

Recency Last purchase more than 90 days ago 90

Last purchase made between 30 and 90 days ago

30 Last purchase occurred within the last 30 days

Frequency Quantiy orders less than 3 3 Quantity orders

between 3 and 10 10 More than 10 Orders

Monetary Order value less than €100 100 Order value between

€100 – €1000 1000 Order value is higher than €1000

Score: 2

middle

3

good

Example RFM Model

45

How to configure RFM / RFE?

1Define Goal : Limiting Wasted Marketing Spend or Improve Revenue

for Key Target Groups

3 Determine how to structure the part of curve you are to focus on

4 Go into URM data (existing standard configuration) to determine thresholds

5 Target campaigns to relevant segments via marketing actions

6 Verify results and adjust (a) RFM/RFE? or (b) marketing actions?

RFM/RFE Setup Overview

2 Determine to focus on head of curve or tail of curve

Pareto Principle:

80% of revenue is generated by 20% of customers

Configuring the Model

Action based Grouping:

Churn Prevention Use Churn time frame as lower limit (RFM and RFE)

Break Even Profitability Use Break Even Cost (approx.) as lower limit Use desired Profit Margin as upper limit

Power Shoppers/Users

Configuring the Model

RFM Group

MonetaryWhat Order-Value was reached?

1bad1

bad3

good3

good

FrequencyHow often did they purchase?

1bad1

bad3

good3

good

RecencyWhen was the last purchase?

2mid2

mid3

good3

good1

bad

Mobile-Phone without contract (IPhone)

2mid

2mid

Bought last phone 2 years ago

Bought a new phone every 2 years

IPhone 4s – best price value configuration

122

Examples of RFM Groups

FrequencyHow often did they purchase?

2mid

MonetaryWhat Order-Value was reached?

2mid

2mid

1bad

1bad

3good3

good

RFM Group

3good3

good

RecencyWhen was the last purchase?

2mid2

mid3

good3

good1

bad

Mobile-Phone without contract (IPhone)

2mid

Bought last phone 2 years ago

Only one purchase

IPhone 4 – minimal-features

111

Examples of RFM Groups

FrequencyHow often did they purchase?

1bad1

bad

MonetaryWhat Order-Value was reached?

3good

3good

RecencyWhen was the last purchase?

1bad

2mid

2mid

2mid

1bad

RFM Group

2mid2

mid3

good1

bad

Mobile-Phone without contract (IPhone)

2mid

Purchase on release

every model will be purchased

IPhone 6s – top-features

333

1bad

Examples of RFM Groups

53

Using RFM / RFE results

Actions: Loyalty Programm Thanks, Personalised, Spread

Low Frequency High

ThanksHi

gh Continue UpsellImprove

Cross-Sell

Recency Increase Guide

1 time

Low Do not

continueActivate

Reactivate with Upsell

Reactivate

MonetaryLow High

Possible recommended actions for RFM segments

How to approach customers?

Activate

RFM Group 123

target segment

Visitors New Visitors Bouncer Returning Visitors

Female Age Cluster:18-25 Years

Predefined / custom segments

How to approach customers?

address them

RFM Group 123

Better Targeting and Actions:

Expand Segmentation to address segments even better Predefined:

URM Customer Micro/Macro Status, Conversion Probability, Churn Probability, Next Basket Value, Age, Gender, CLV, Qty Product Views

Custom: Product Return Rates, Household Income

Include "offline contacts" to keep model accurate Leverage channel preference

Cases Create Communication channel for "new" users

Push the sale or create a connection? Post Sale Experience – Service Offering Targeted On Site Survey Preferred Marketing Channel Call Center Integration

Using RFM/RFE Plus X

Possible approach:

Churn Prevention Use Churn time frame as lower limit for Frequency Target people onsite before churn

Offer (Premium) Content to right audience Incentivize Log-ins Personalized Recommendations

No Products to sell? - Expand Model to Ad clicks Work with performance based marketing for higher eCPM

Increase Premium Ad Prices (combination with URM information)

Establish a persistent communication channel

Using RFM/RFE for Publishing

58

Example of URM in Action:Buying Furniture

If it helps your business make

more money, use it in the URM

Campaign Channel: SEOKeyword: sofa

Standard landing page is shown

Personalised Sofa Buying

Begin to use URM / MA

Marketing Automation

UserRelationshipManagement

Because the user searches with an iPad, we show higher priced

items, such as :Leather Sofas

Campaign Channel: SEOKeyword: sofa

Device: iPad

Begin to use CRM Data

Marketing Automation

UserRelationshipManagement

Indications of customer who buys higher priced

items

Thus, even higher priced

recommendations than just leather sofas

Campaign Channel: SEOKeyword: sofaDevice: iPad

Gender: Woman

Income: €60K+

More CRM Data

Marketing Automation

UserRelationshipManagement

With children in the house,

maybe leather/too many high priced

items is not such a good idea

Campaign Channel: SEOKeyword: sofaDevice: iPadGender: WomanIncome: €60K+

Kids: 1

Include Survey Data

Marketing Automation

UserRelationshipManagement

It turns out the child is likely already in or

moving to university

If it (significantly) impacts the likelihood to buy, we should ask the

customer…

Campaign Channel: SEOKeyword: sofaDevice: iPadGender: WomanIncome: €60K+Kids: 1

Next Big Project:

Student Flat

Example : Potential Ikea Survey

For a 10% discount off of your next purchase over €1.000, please tell us your next big project:

New KitchenNew Living RoomNew BedroomApartment for our childSecond Home

Customer Looks at a Specific Product

Customer browses the site for various sofas

and sofa beds, including the one to the left.

Customer does not purchase and leaves the

site.

What could happen next?

Targetted Email

Campaign Channel: SEOKeyword: sofaDevice: iPadGender: WomanIncome: €60K+Kids: 1Next Big Project: Student Flat

RFM:333Preferred Marketing:

Email

The customer :

Bought Recently (R = 3)Buys a lot Frequently (F = 3)Spends a lot of money with us (M = 3)

Customer also purchases via our newsletter sometimes.

Therefore, we will close following marketing channels for the next 15 days for this customer:

• Criteo Retargetting• Display• Affiliate• AdWords

Focus on Email for 15 days.

Instore Push Message

Customer looked at

sofaonline

One Week Ago Today in Store

This sofa is just a 2

minute walk away in the sofa

section

Integration Overview from Examples

Analytics/ URM

Website

Email

Mobile (incl.Push)/In-Store

Criteo

Display

AdWords

Affiliate

Website & Apps

CRM

Email

AdWords

Affiliate

Display

RetargettingDWH & Other

Systems

Marketing Automation

Survey

Conrad MorbitzerSenior Business Consultant

Berlin, Germany

+49 (0)30 755 415 408conrad.morbitzer@webtrekk.com

Amsterdam | Beijing | Berlin | Frankfurt | Madrid | Milanwebtrekk.com

MA / URM Quick Start

UserRelationshipManagement

1

CreateUser Segments

Marketing Automation

2

LaunchCampaigns

3

AutomatedPersonalised

Banners & Content

Customer Prints Product

Form

Without Webtrekk User Centric – Data shows 2 People

Today

Customer Submits

Form/Signs Up for Product

In 6 Weeks

Customer Prints Product

Form

Webtrekk User Centric – Data Shows Single Customer

Today

Customer Submits

Form/Signs Up for Product

In 6 Weeks

Bank Example 1 – New Product Signup

Customer Prints Product

Form

More Targeting, Shorter Cycles

Today

Customer Submits

Form/Signs Up for Product

In 6 2 Weeks

Only to customers with Account

holdings greater than

€XXX.000

Bank Example 2 – New Product Signup

Customer Plays with Mortgage Calculator

Customer Signs up for

Home Loan in a Branch

Click here to set up an appointment to take

advantage of the best mortgage rates in

History.

Bank Example 3 – Home Loan

?Unknown prospect

searches for ‘best savings

account‘

Unknown

Visitor

Searches

Compare savings options

Transfer nowReceive 2%

Banners on SitePersonalisation

LocationBerlin

LocationMunich

DeviceiOS

DeviceAndroid

HighlyEngaged

Visitor

LowEngaged

Visitor

Bank Example 4 – Prospect Handling

Customer looks at dress online

Last Night Today

This dress is

available at the front

of the store near

shoes

E-commerce Example

Via RFEUser is

Targeted

Last Night

Anonymous Surfer looks at sports &

stocks

First Month

as of month 2

Today

Media Example – Improve Subscriptions