SAVE THE DATE
GET YOUR TICKET NOW!
www.noah-conference.com/request-invitation
Old Billingsgate, London Tempodrom, Berlin
12-13 NOV2015 8 - 9 JUN2016
MISFITS REBELS
RESULTS
OF DIGITAL
DISRUPTION
70%+ of Fortune 500
companies have
disappeared since 1990
Digitalisation is the
driving force trans-
forming business
Digital disruption
demolishes old
business models
Big data permits new
and amazing customer
insights
VERIVOX
has disrupted
the energy market
1
German electricity market liberalised in 1998.
Verivox was founded and compared offers
nationwide
2
In 2005 the gas market was liberalised
and added to Verivox comparison portfolio
3
Breakthrough year with 600.000 brokered
switches only in 2007 – customers had choice
4
Customer acquisition cost decreased c.60+%
for established energy providers
5 In 2014 almost one million German households
switched their energy provider via Verivox and
saved in excess of €300.000.000
SUCCESS-BASED
LOW COST SALES CHANNEL
Verivox provides industry a c.40%
customer acquisition cost saving
No switch,
no commission Targeted Efficient Measurable
0
50
100
150
200
250
300
350
Electricity Gas DSL Mobile discount Mobile smartphone Car insurance Loans
OCP
Offline average
61%
saving
33%
saving
70%
saving
38%
saving
53%
saving
26%
saving
15%
saving
€
Online
comparison portals
manage big data
Comparison
business
model is
driven
by ever
increasing
input
variables
›1.000+ electricity and
850+ gas providers
›8.200 zip codes & 27.000
tariffs
›Tariff pricing include
consumption levels and
region
›Dynamic provider pricing
models
›Provider and tariff quality
evaluation
+of constantly moving parts
1 MILLION
THE TV MARKETING
EQUATION IS MORE COMPLEX
Using millions of data points to evidence
the financial effectiveness of TV advertising
SEASONAL
VARIABLES
Weather
Holidays
Seasonality
TIME
VARIABLES
Hour of day
Billing days
Weekday
Financial quarters
OTHER INFLUENCING
FACTORS
Market media spend
Consumer interest
Price changes
Media budget/placement
OPTIMAL
MEDIA SPEND
TV | Online | Print
VISITS &
CONTRACTS
VALIDATING
THE MODEL
TIME
VOLUME
ACTUAL MODELLED
ENERGY
FORECAST MODEL
REAL EFFECT›Model output based upon
input data of 24 months
›Quantifying short-, mid- and
long-term impact of TV
advertising
›Next: Forecasting transactions
THE
MODEL
WORKS
TV ADVERTISING
EFFECTIVENESS1
ENERGY FRANK 2012
MULTIPRODUCT FRANK 2013
KLAUS HUFNAGEL Q1-Q2‘14
GEISSENS Q4’14 (ONGOING)
1
1.5
2.0
5
Campaign period
Visit Uplift factor
(1) Media Plan Database, AGF in cooperation with GfK, TV Control, Google
Analytics (Measurement 10 mins before and 10 mins after broadcasting)
› New campaign “The Geissens” 5 x more effective
› TV is creating a positive ROI
BEFORE
BIG DATA
First TV ad in Germany
(Persil Historischer Werbespot)
Verivox - NOAH15 Berlin

Verivox - NOAH15 Berlin

  • 2.
    SAVE THE DATE GETYOUR TICKET NOW! www.noah-conference.com/request-invitation Old Billingsgate, London Tempodrom, Berlin 12-13 NOV2015 8 - 9 JUN2016
  • 4.
  • 5.
    RESULTS OF DIGITAL DISRUPTION 70%+ ofFortune 500 companies have disappeared since 1990 Digitalisation is the driving force trans- forming business Digital disruption demolishes old business models Big data permits new and amazing customer insights
  • 6.
    VERIVOX has disrupted the energymarket 1 German electricity market liberalised in 1998. Verivox was founded and compared offers nationwide 2 In 2005 the gas market was liberalised and added to Verivox comparison portfolio 3 Breakthrough year with 600.000 brokered switches only in 2007 – customers had choice 4 Customer acquisition cost decreased c.60+% for established energy providers 5 In 2014 almost one million German households switched their energy provider via Verivox and saved in excess of €300.000.000
  • 7.
    SUCCESS-BASED LOW COST SALESCHANNEL Verivox provides industry a c.40% customer acquisition cost saving No switch, no commission Targeted Efficient Measurable 0 50 100 150 200 250 300 350 Electricity Gas DSL Mobile discount Mobile smartphone Car insurance Loans OCP Offline average 61% saving 33% saving 70% saving 38% saving 53% saving 26% saving 15% saving €
  • 8.
    Online comparison portals manage bigdata Comparison business model is driven by ever increasing input variables ›1.000+ electricity and 850+ gas providers ›8.200 zip codes & 27.000 tariffs ›Tariff pricing include consumption levels and region ›Dynamic provider pricing models ›Provider and tariff quality evaluation +of constantly moving parts 1 MILLION
  • 9.
    THE TV MARKETING EQUATIONIS MORE COMPLEX Using millions of data points to evidence the financial effectiveness of TV advertising SEASONAL VARIABLES Weather Holidays Seasonality TIME VARIABLES Hour of day Billing days Weekday Financial quarters OTHER INFLUENCING FACTORS Market media spend Consumer interest Price changes Media budget/placement OPTIMAL MEDIA SPEND TV | Online | Print VISITS & CONTRACTS
  • 10.
    VALIDATING THE MODEL TIME VOLUME ACTUAL MODELLED ENERGY FORECASTMODEL REAL EFFECT›Model output based upon input data of 24 months ›Quantifying short-, mid- and long-term impact of TV advertising ›Next: Forecasting transactions
  • 11.
    THE MODEL WORKS TV ADVERTISING EFFECTIVENESS1 ENERGY FRANK2012 MULTIPRODUCT FRANK 2013 KLAUS HUFNAGEL Q1-Q2‘14 GEISSENS Q4’14 (ONGOING) 1 1.5 2.0 5 Campaign period Visit Uplift factor (1) Media Plan Database, AGF in cooperation with GfK, TV Control, Google Analytics (Measurement 10 mins before and 10 mins after broadcasting) › New campaign “The Geissens” 5 x more effective › TV is creating a positive ROI
  • 12.
    BEFORE BIG DATA First TVad in Germany (Persil Historischer Werbespot)