Ist Big Data wirklich in der Praxis des Marketings angekommen? Was heißt das eigentlich Big Data im Marketing? Was bewirkt der Einsatz von Marketing Data Science? Und welchen Einfluss hat das auf den Return on Marketing Investment?
Vortrag auf dem Big Data Summit von Bitkom und IHK Berlin, Oktober 2016
3. 2
„We make sense of (big) data in Marketing”:
Seit 2006. >150 Marketing Science Projekte. Darunter für 9 DAX-Kunden.
End-to-end
Marketing im
driver seat
Tools statt
PowerPoint
Cutting-edge
Methodik auf
vorhandenen Daten
4. Unsere Mission: Data Science auf den Schreibtisch des CMO!
3
Industrie trifft
Marketingwissenschaft
Top Data Science Team
Entscheider-Tools im
Browser
Ex-McKinsey Gründer, inhabergeführt
>125 Data Scientists
Berlin, Posen, Zürich
Produktmarketing
PortfolioWorx & CrowdWorx
Marketing-
Kommunikation
SpendWorx & GeoWorx
+
Berater: jeweils >10J Industrie-Erfahrung
+
Akademischer & Industrie-Beirat
13. 12
Kanalexplosion
Massiver ROI-Druck
of CMOs state that
their greatest
challenge is showing
measurable ROI
Quelle: How to meet marketing ROI milestones;
http://www.marketingtechnews.net/news/2016/sep/15/how-meet-
marketing-roi-milestones/
Big Data, aber
nicht big insights
Skill & Culture Gap
93%
15. So viel Verschwendung trotz Big Data?
14
Quelle: Michael Brenner, Solving The Challenge of Marketing ROI
2016
71%
Advertising
fails to meet
expectations
96%
Ads reach people
outside the intended
target and lead to ad
waste
89%
digital marketing mix
is not optimized and a
different mix would
yield better results
16. Worldwide Budget for
advertising, detailing and
other marketing activities
15
Source: Albers, Fischer, Frie und Wagner 2011: Dynamic marketing budget allocation across countries,
products, and marketing activities, in: Marketing Science, 30(4), S. 568-585
Marketing
Analytics
Marketing induced profits p.a.
+ $ 658.7 Mio
Wissenschaftliche Studien: Massiver EBIT Effekt durch
Marketing Data Science.
17. 16
Source: Rishi Bhandari, Marc Singer, and Hiek van der Scheer: “Using marketing analytics to drive superior
growth”; McKinsey Insights, June 2014
McKinsey: 20% ROI-Steigerung durch Marketing Data Science.
There’s no question that the development of better analytical tools and approaches in
recent years has given business leaders significant new decision-making firepower. Yet
while advanced analytics provide the ability to increase growth and marketing return on
investment (MROI), organizations seem almost paralyzed by the choices on offer. As a
result, business leaders tend to rely on just one planning and performance-management
approach. They quickly find that even the most advanced single methodology has limits.
The diverse activities and audiences that marketing dollars typically support and the
variety of investment time horizons call for a more sophisticated approach. In our
experience, the best way for business leaders to improve marketing effectiveness is to
integrate MROI options in a way that takes advantage of the best assets of each. The
benefits can be enormous: our review of more than 400 diverse client engagements from
the past eight years, across industries and regions, found that an integrated analytics
approach can free up some 15 to 20 percent of marketing spending. Worldwide, that
equates to as much as $200 billion that can be reinvested by companies or drop straight
to the bottom line.
Here’s one example. A property-and-casualty insurance company in the United States
increased marketing productivity by more than 15 percent each year from 2009 to 2012.
The company was able to keep marketing spending flat over this period, even as related
spending across the industry grew by 62 percent. As the chief marketing officer put it,
“Marketing analytics have allowed us to make every decision we made before, better.”
Anchoring analytics to strategy
A company’s overarching strategy should ground its choice of analytical options. Without
a strategy anchor, we find companies often allocate marketing dollars based largely on
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>400
integrated marketing
analytics can free up
15-20%of marketing spend
=$200b
EBIT effect globallyclients involved
“
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18. 17
Zielgrößen
• Marktanteil
• Absatz
• Umsatz
• Ertrag / Deckungsbeitrag
• Trial / Test drive
Treiber
• Produktportfolio
• Preise
• Promotions
• Media-Spendings
• Distribution
• Wetter
• Social Media
Benefits
Einflussstärke: Welche Treiber sind wie wichtig?
Simulation: Was wäre wenn?
Optimierung: Produktportfolio, Preise, Media-
Budget & Allokation etc.
x y
Marketing Data Science erklärt die Treiber von Erfolg anstatt
„nur“ die Schritte dazwischen.
Marketing Data Science
Ad
Awareness
Impressions
Clicks /
Response
Consideration/
1st choice
19. Dafür ist ein sauber gepflegter ”Datenmarktplatz” erforderlich.
18
§Daten-
Management
§Marketing Data
Science in a box
§Serverbetrieb
und Wartung
§Rechte-
management
§Data Security
§Trusted 3rd party
OMNIROMITM
Deutsches Data Center
Private Cloud je Kunde
On premise möglich
§ Anzahl VIPs: Geschäfts-führer,
Gesellschafter usw.
§ B2B-Daten (Unternehmen)
Datenpartner (Auswahl) &
Standard-Schnittstellen
§ Werbespendings (alle Wettbewerber)
§ Mikro-Passantenfrequenzen
§ Geodaten wie Kaufkraft, Haushalte,
Einwohner etc.
§ Google Maps API-Daten
Kunden
§ TelCo
§ Banken
§ Handel
§ Automotive
§ System-
Gastronomie
20. Omni-Kanal Optimierung ist Pflicht, denn:
>500 Milliarden USD sind eben nicht Online-Marketing.
19
542
202
938
396
154
53
51
61
22
Global marketing
spendings
non advertising (e.g.
events, sponsoring, store
promotions (!), Market
research, CRM)
advertising Breakdown by channel
2012; in billion USD
TV
1.312 by
2020;
CAGR: 5,8%
Online
(50% mobile)
Direct Mail
Display
Newspaper
Magazines