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Why Personalized Digital Marketing Hasn’t Worked….Yet
Date
Today’s Speakers
Robert Mattson, Director of Product Marketing, Sitefinity – Telerik, A Progress Company
Robert has been in the technology space for over 25 years with companies such as Allaire, Eprise, Applix, ADP and Workscape. His focus has been on how technology can be effectively leveraged to overcome both technical and business challenges. He has spoken at events and conferences in the US and abroad, and his thoughts and research have been published both online and in print ranging from the Java Developer’s Journal to Talent Management Magazine.
Svetla Yankova(@Ssvetla_Yankova), Product Marketing Manager, Sitefinity – Telerik, A Progress Company
Svetla has always worked in the web content management industry and has previously held different positions in engineering, design and sales. Her work with Telerik began with pre- and post-sales consulting for customers, where she was able to focus on translating enterprise requirements into solutions. With a background in mathematics, Svetla is passionate about data-driven marketing as well as discovering and advocating better ways of how technology can address specific business questions. She is the author of the Data-Driven Marketing e-book.
HOT TOPIC ALERT
Personalization: A Digital Priority*
*Econsultancy 2015 Digital Trends
Personalization is about to pass mobile
*Econsultancy 2015 Digital Trends
B2C vs B2B
B2C• Purchase focused• Shorter decision cycles• Personalized by
Individual • Products and Services• 18% more likely than B2B
to focus on targeting( vs. 55% more likely in 2014)
B2B• Research focused• Longer decision
cycles• Personalized by
Account• Products and Services• Big investment and
focus in 2015
Challenges
TECHNOLOGY
SCALABILITY
DATA
PROCESS
PRIVACY & COMPLIANCE
Challenge: Technology
• Maturity of personalization platforms
• Many offering include personalization, but how many are actually used due to difficulty implementing at scale?
• Personalization domains• Owned website• Advertising platform• Marketing campaigns
• Accessing the data needed to create persona or specific personalization models
Challenge: Scalability
• Types of Scale• Number of profiles• Number of
personalizations• Depth of personalizations• Amount of data required• Amount of effort to plan
and implement requirements in alignment with business goals
Challenge: Data
• What is it?• Where is it?• Can I get access to it?• Can I relate data from
one system to another?
• Can I do all of this consistently, quickly and efficiently?
• Can I even store all the data I need?
Challenge: Process
• Who owns the systems that have the data?
• Who owns integration of systems?
• Who decides the personalization strategy?
• What team maintains the integrations and personalizations?
Challenge: Privacy and Compliance
• What data is fair game for personalization?
• Is it different in the US versus EU versus APAC?
• What data privacy legislations do you need to be aware of?
• HIPAA Example of Protected Data• Health information, including demographic
information• Relates to an individual’s physical or mental
health or the provision of or payment for health care
• Identifies the individual
• Perception is as important as reality
• The Target Example** - Forbes Feb 2012
Solutions
INTEGRATION OF BUSINESS & IT
SEPARATION OF PRESENTATION AND CONTENT
INTEGRATION OF DATA & PROCESS
Scale requires true integration between business & IT
Business:
1)Decides on segments
2)Decides on content
IT:
1)Delivers new data points
2)Delivers new ways to segment
2. Complexity Requires Separation of Presentation and Content
3. Investment requires agile, data-driven process.
Investment
New Content
PersonalizationResults
ROI
The enrichment of data perspective
0 CLICKS
IP, INFERRED LOCATION
INFERRED COMPANY
CAMPAIGN PARAMETERS
0 – 10 CLICKS
BROWSING HISTORY
ON-SITE SEARCH
NAVIGATION BEHAVIOR
UPON IDENTIFICATION
PURCHASE HISTORY
ADDRESS
SEARCH KEYWORDS
OFF-SITE BROWSING
PERSONA
CONVERSION LIKELIHOOD
CRM DATA
FORM DATA
PAST BROWSING
UPON PURCHASE
SATISFACTION
SOCIAL DATA
Personalization can impact different areas of the funnel
Exposure
Discovery
Consideration
Conversion
Customer Relationshi
p
Retention
Implicit
Profiling
Implicit + Explicit
Predictive
Account Based
Purchase History Based
Depth of data
Audience Size
Where to start = which conversion do you want to impact
Exposure
Discovery
Consideration
Conversion
Customer Relationshi
p
Retention
Opportunity
1% Conversion rate
20% conversion rate
60% conversion rate
Agile + Analytics Validation
Pick 1 location personalize Pick 1
persona personalize Pick winner Invest
The predictive approach
1000 visitors
1% conversion rate
100
5%
From Washington DC
From Washington DC
AND
seen Government Solutions video
The predictive approach
1000 visitors
1% conversion rate
100
5%
From Washington DC
From Washington DC
AND
seen Government Solutions video
Conclusion: Showing
Government solutions to DC
visitors may lead to
Up to 35 Net New
Conversions
The predictive approach
1000 visitors
1% conversion rate
100
5%
100
10%
500
5%
Up to 35 Net New
Conversions
Up to 15 Net New
Conversions
From Washington DC
Seen Government Solutions
Marketing Persona
Read “Digital Experience Cloud” brochure
Prescriptive AnalyticsDynamic Segment
“Best Next” Action
Result Prediction
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