11. The Objective of Marketing
• Marketing aligns your brand with the
largest market segments in which you have
an advantage and targets promotions
– Brand – a promise of value (that your core
competence can fulfill)
– Market segment – personae with a need where
you can deliver a product or service
– Advantage – your differentiation so you don’t
compete on price alone
12. The good news
• Moore’s law
• Your potential customers can self-educate
24/7 from anywhere
• You can learn more about customers than
ever before through Business Intelligence
• Social can lower your support costs and
enhance virality
13. The bad news
• Moore’s Law
• Your potential customers can self-educate 24/7
from anywhere
• Data accumulates much faster than it can be
analyzed … for now
• Business Intelligence has only 4% penetration
• Social means that messaging about your brand can
easily get out of control
14. The really bad news
• Moore’s law and free trade = nowhere to
hide
• Product life cycles get shorter
• Differentiation gets harder
• Linearity is disappearing
– Traditional market forecasting is in trouble
• The bear is coming
15. Analytics at its best
• Imprecise indicators of trends
• Indicators of actions to take
• Use A/B testing for continuous refinement
– Tweak and retweak
– Pay attention to timing
• Report using the language of stakeholders
• Track ROI of analytics to justify efforts
16. Marketing Then and Now
• Revenue generation: • Revenue generation:
Marketing 30% Marketing 70%
Sales 70% Sales 30%
• 3 to 5 ad impressions • More than 10
impressions per
per conversion conversion
• You control the • You try to track the
messaging messaging
• A persona is an idea • A persona is a
segment that you can
target
17. The Google Perspective
• Return on Analytics is the improvement in
marketing revenue due to analytics
• Zero moment of Truth – prospects need
over 10 exposures before they first convert
and buy a product – you need to track and
measure to know how to build sales.
– ‘Micro-conversions’ – exposures before the
‘macro-conversion’
18. Data Sources
• Structured data • Unstructured Data
– E-mail responses – Blogs
– Web logs – Tweets
– Forms – Articles
– Client records – Social likes/comments
– Affiliate records – Rating sites
– Mobile Applications – Video
– Response forms – Images
– Tracking cookies
19. Typical Web Analytics
• Make sure all of your pages are tracking
• Model your funnel
• Define your goals
• Identify your Key Performance Indicators
• Identify historic baselines for KPIs
• Use a dashboard to monitor actuals vs
baselines
20. Market Evolution Examples
• Marketing automation
– RocketFuel – Use artificial intelligence to
tweak your marketing programs for you in real
time
• BI Services – adding in the unstructured
data
– Infinigraph – rate your campaigns and brands
based on sentiment on Twitter, Facebook etc.
21.
22.
23.
24. By the Numbers
An unconference presentation
3/30/2013
David Kohls
KohlsConsulting@gmail.com