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„Save your digital life!“
in a sea of Big Data…
Fred Pellenaars Ralf Haberich
Country Manager CCO
Benelux
MIE 2014

Utrecht

Welcome to the





100+ Employees
Headquarter Berlin
Dedicated Partner Program
> 40% Annual Revenue Growth every year
Successful with Big Data and analytics

Know if you
are
prepared

How and where to
start

Have seen 2
relevant
Case studies

Welcome to the
Context – Big Data

Variety, volume
and
Velocity
Big Data analytics–value?
Extract business value by revealing correlations on:
 Trends
 Hidden drivers of profit
 Opportunities

“In some industries it will be the
difference between surviving
and not surviving”

Source: /www.mckinsey.com/insights/strategy/are_you_ready_for_the_era_of_big_data
Big Data - How the boss sees it
Big Data – In reality
Where to start?

1. Be prepared
team, data

2.Focus
goal
rule out assumptions

3. Start with asking
the right questions
Asking the right questions

Follow the money trail
In the end all Big Data and analytics should lead to succes
More profit
Then start with small steps

Look for small changes
that drive
Big Bucks
Example: TV commercials vs. Online revenue
Context

 Dutch TV spot market 800 million euro
 Viewing time:H1, new record: 201 minutes (6+) per person
 Cost of one 30 second tv spot prime time: € 20k
 Producing costs, film set costs, internal costs.
 Budget TV commercial campaign, between 50 and 500k
Good investment ?
CASE STUDY

„Driving eCommerce with TV Commercials“
Company WIRKAUFENS
Location Germany
About wirkaufens.de

 Founded 2008
 100+ Employees in Frankfurt & Berlin
 Online marketplace for buying your Second Hand
 Mobile
 MP3
 Navigation

 Turnover €20 Million
Watches TV commercial

Visits Website

Analysis
Traffic

Brand Search
Direct Entry
Newsletter
Campaign
Traffic

TV Spot
t0

time
Traffic

Brand Search
Direct Entry
Newsletter
Campaign
Traffic

TV Spot
t0

time
Traffic

Spot related
Brand Search
Spot related
Direct Entry
Newsletter
Campaign
Traffic

TV Spot
t0 - X minutes

t0

t0 + X minutes

time
Number of TV Visitors - per Minute
Transaction Influence - per Commercial
Learnings

 Data beats assumption
 Valuable and actionable insights on impact of
 Specific TV spot
 Specific TV campaign
 Value driver or not

Suitable for

and
CASE STUDY

„Model Selection via eCommerce analytics“
Company Anonymous
Location Hongkong
About the Company

 Founded 1970s
 15.000 Employees Worldwide
 Fashion Shopping
 Women
 Men
 Kids

 10,000 Stores/Wholesales
 Turnover $4.5 Billion
Is a blonde model
the best choice
to sell bikinis online?
Fashion Brand re-structured photo shoots
by analysing the model impact on sales and
increased orders by 38% to achieve a seasonal
turnover increase of $960,000.
Data-Driven Companies perform stronger
&
will take the Lead
(Company Value, Marketing Knowledge, ROI)

Output

Business
Optimization

Data
Integration
Analysis
Data CollectionReporting

Website
Optimization

Input (Time, Effort)
(Company Value, Marketing Knowledge, ROI)

Output

Statistics

Digital
Intelligence

Web Analytics

Business
Optimization

Data
Integration
Analysis
Data CollectionReporting

Website
Optimization

Input (Time, Effort)
(Company Value, Marketing Knowledge, ROI)

Output

Statistics

Digital
Intelligence

Web Analytics
Customer
Journey

Real
Time

Business
Optimization

Segmentation

Tagging

Data
Integration

Analysis
Data CollectionReporting

Website
Optimization

Input (Time, Effort)

Real
OnlineOffline
Combination
(Company Value, Marketing Knowledge, ROI)

Output

Gartner Hype Cycle

Statistics

Digital
Intelligence

Web Analytics
Customer
Journey

Real
Time

Business
Optimization

Segmentation

Tagging

Data
Integration

Analysis
Data CollectionReporting

Website
Optimization

Input (Time, Effort)

Real
OnlineOffline
Combination

Digital Intelligence Model
©by Ralf Haberich
The Digital Marketing Challenges

Digital Marketing World

Control
Campaign
Budgets

Optimize
Advertising
& Reach

A/B Testing

Keyword Tracking

Real Time Bidding

Tag-Management

Recommendations

Multivariate Testing

Campaign Controlling

Re-Targeting

TV/Print/Instore

Mobile Analytics

Merchandising

Landing Page &

Customer Tracking

Behavioral Targeting

Trusted Data

E-Commerce

Onsite Targeting

User Experience

Attribution Modelling

Predictive Targeting

1-First / 3rd

Predictive Analytics

Digital Intelligence Suite

Get
Data &
Insights

Personalize
Content &
Offers

Web Analytics

Dynamic Teaser

Social Analytics

Optimize
Conversion
Rates

Email Remarketing

Optimization

Real Time Advertising

Other Data

Analytics
Performance

Marketing
Action Center

Testing &
Optimization

Customer
Journey

Program.
Advertising

Use Every
Data
Everywhere

Safe Tag/
API
WRAP UP

Be prepared
Focus
Small changes, big bucks
Thank You

Amsterdam | Beijing | Berlin | Frankfurt | Madrid | Milan | San Francisco

More info:
Fred Pellenaars, Country Manager Benelux | fred.pellenaars@webtrekk.com
+31 6 347 11 500 | webtrekk.com

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´Save your Digital Life!´ - MIE2014 Webtrekk

  • 1. „Save your digital life!“ in a sea of Big Data… Fred Pellenaars Ralf Haberich Country Manager CCO Benelux MIE 2014 Utrecht Welcome to the
  • 2.     100+ Employees Headquarter Berlin Dedicated Partner Program > 40% Annual Revenue Growth every year
  • 3.
  • 4.
  • 5. Successful with Big Data and analytics Know if you are prepared How and where to start Have seen 2 relevant Case studies Welcome to the
  • 6. Context – Big Data Variety, volume and Velocity
  • 7. Big Data analytics–value? Extract business value by revealing correlations on:  Trends  Hidden drivers of profit  Opportunities “In some industries it will be the difference between surviving and not surviving” Source: /www.mckinsey.com/insights/strategy/are_you_ready_for_the_era_of_big_data
  • 8. Big Data - How the boss sees it
  • 9. Big Data – In reality
  • 10. Where to start? 1. Be prepared team, data 2.Focus goal rule out assumptions 3. Start with asking the right questions
  • 11. Asking the right questions Follow the money trail In the end all Big Data and analytics should lead to succes More profit
  • 12. Then start with small steps Look for small changes that drive Big Bucks
  • 13. Example: TV commercials vs. Online revenue
  • 14. Context  Dutch TV spot market 800 million euro  Viewing time:H1, new record: 201 minutes (6+) per person  Cost of one 30 second tv spot prime time: € 20k  Producing costs, film set costs, internal costs.  Budget TV commercial campaign, between 50 and 500k Good investment ?
  • 15. CASE STUDY „Driving eCommerce with TV Commercials“ Company WIRKAUFENS Location Germany
  • 16. About wirkaufens.de  Founded 2008  100+ Employees in Frankfurt & Berlin  Online marketplace for buying your Second Hand  Mobile  MP3  Navigation  Turnover €20 Million
  • 17. Watches TV commercial Visits Website Analysis
  • 20. Traffic Spot related Brand Search Spot related Direct Entry Newsletter Campaign Traffic TV Spot t0 - X minutes t0 t0 + X minutes time
  • 21.
  • 22. Number of TV Visitors - per Minute
  • 23. Transaction Influence - per Commercial
  • 24. Learnings  Data beats assumption  Valuable and actionable insights on impact of  Specific TV spot  Specific TV campaign  Value driver or not Suitable for and
  • 25. CASE STUDY „Model Selection via eCommerce analytics“ Company Anonymous Location Hongkong
  • 26. About the Company  Founded 1970s  15.000 Employees Worldwide  Fashion Shopping  Women  Men  Kids  10,000 Stores/Wholesales  Turnover $4.5 Billion
  • 27. Is a blonde model the best choice to sell bikinis online?
  • 28. Fashion Brand re-structured photo shoots by analysing the model impact on sales and increased orders by 38% to achieve a seasonal turnover increase of $960,000.
  • 29.
  • 30. Data-Driven Companies perform stronger & will take the Lead
  • 31. (Company Value, Marketing Knowledge, ROI) Output Business Optimization Data Integration Analysis Data CollectionReporting Website Optimization Input (Time, Effort)
  • 32. (Company Value, Marketing Knowledge, ROI) Output Statistics Digital Intelligence Web Analytics Business Optimization Data Integration Analysis Data CollectionReporting Website Optimization Input (Time, Effort)
  • 33. (Company Value, Marketing Knowledge, ROI) Output Statistics Digital Intelligence Web Analytics Customer Journey Real Time Business Optimization Segmentation Tagging Data Integration Analysis Data CollectionReporting Website Optimization Input (Time, Effort) Real OnlineOffline Combination
  • 34. (Company Value, Marketing Knowledge, ROI) Output Gartner Hype Cycle Statistics Digital Intelligence Web Analytics Customer Journey Real Time Business Optimization Segmentation Tagging Data Integration Analysis Data CollectionReporting Website Optimization Input (Time, Effort) Real OnlineOffline Combination Digital Intelligence Model ©by Ralf Haberich
  • 35.
  • 36.
  • 37. The Digital Marketing Challenges Digital Marketing World Control Campaign Budgets Optimize Advertising & Reach A/B Testing Keyword Tracking Real Time Bidding Tag-Management Recommendations Multivariate Testing Campaign Controlling Re-Targeting TV/Print/Instore Mobile Analytics Merchandising Landing Page & Customer Tracking Behavioral Targeting Trusted Data E-Commerce Onsite Targeting User Experience Attribution Modelling Predictive Targeting 1-First / 3rd Predictive Analytics Digital Intelligence Suite Get Data & Insights Personalize Content & Offers Web Analytics Dynamic Teaser Social Analytics Optimize Conversion Rates Email Remarketing Optimization Real Time Advertising Other Data Analytics Performance Marketing Action Center Testing & Optimization Customer Journey Program. Advertising Use Every Data Everywhere Safe Tag/ API
  • 38. WRAP UP Be prepared Focus Small changes, big bucks
  • 39. Thank You Amsterdam | Beijing | Berlin | Frankfurt | Madrid | Milan | San Francisco More info: Fred Pellenaars, Country Manager Benelux | fred.pellenaars@webtrekk.com +31 6 347 11 500 | webtrekk.com