During this BlueSpire TrendLab webinar, our financial marketing strategists focus on the importance of big data analytics and how proper implementation can positively impact all of your marketing efforts. Other areas of emphasis were: • The latest consumer trends affecting financial institutions—results from an exclusive proprietary study on how today’s consumers are engaging with financial institutions. • How to properly plan for big data and setting institutional goals. • The importance of implementing marketing automation and why such efforts are bound to fail without a critical data-driven content marketing plan.

2. Welcome
Today’s presentation is brought to you by
BlueSpire Strategic Marketing.

3. Featured Speakers
Jen Joly, senior director of marketing,
communications and brand management
12+ years marketing
9 years in banking, serving FIs
3+ years in the highly data-driven gaming industry
Aaron Gregerson, account supervisor
9 years in financial services
Marketing and business development roles

4. What You’ll Learn Today
What’s driving the shift: consumers in the driver’s seat
The role of (big) data
How to properly plan for big data:
Visualizing and documenting data sources
Understanding the "five big data W's"
How to sett individual/institutional goals
Why marketing automation efforts are bound to fail
without a critical data-driven content marketing plan

5. What do consumers want?

6. 65% of respondents
spend one hour or
more with a specific
company’s apps, social
sites or website.

7. 59% of respondents
say they interact
with their bank or
credit union at least
once a week.

8. Features Consumers Want Most
Can store my account info 6.5%
Helps keep me organized 7%
Navigation 8.9%
Search feature to find answers myself 10.5%
Ability to purchase items 11.3%
Quality of design 11.8%
Large amounts of information 13.9%

9. Features They Like Least
Navigation 6.5%
Large amounts of info 6.7%
Video tutorials 7.2%
Pop up with phone number, email, web service 10.8%
Feedback survey 11.3%
Reco’s based on preferences/past behaviors 11.8%
Rating the app 13.7%

10. What They Expect from Your Emails
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%

11. “86% of US internet users
have attempted to remove or
mask their online activities,
despite only 37% believing it is
possible to be completely
anonymous online.”
- Pew Research Center, September 2013
http://trendwatching.com

12. “57% of consumers are willing to share
additional personal information, such as
their location, top five Facebook
friends’ names and information about
family members, in return for financial
rewards or better service.”
- Coleman Parkes, April 2013
http://trendwatching.com

13. The Role of Data

14. What is Big Data?
Volume
Velocity
Variability
Variety
Complexity

15. Big Data in Perspective
A single petabyte is
equivalent to 20 million
file cabinets worth of text.

16. “… without
analytics, big data
is just noise.”
- IBM.com

17. The Truth About Big Data
Big data = the next evolution of data
analytics
It’s not a magic solution to your marketing
challenges if you haven’t mastered basic
data analytics
Most success stories still center on fraud

18. In a recent study …
71 percent of FIs reported that
information and analytics are creating a
competitive advantage.
• IBM 2010 New Intelligent Enterprise Global Executive Study and Research Collaboration
• http://www.americanbanker.com/issues/178_135/how-zions-bank-is-conquering-big-data-for-marketing-campaigns-1060603-1.html
Zions Bank Use Cases:
• Commercial business card
• Mobile remote deposit capture
• Cross-selling
• “Lifestyle score model”
• Customer attrition

19. How do you prepare
for big data?

20. Visualize & Document Data Sources

21. Understanding the Five “W’s”
Who What / Where / When How
Personas / Segmentation
Propensity
Modeling

22. The Who: Personas / Segmentation
“Jim”
The Traditionalist
“Amy”
The Open Sharer
“Bill”
The Interactor

23. Why Personas/Segmentation?
Targeting by profit
potential
Brand positioning
Product development
Cross-selling
Targeted marketing
Retention

24. Personas are
critical to
addressing
buyer behavior
throughout the
sales funnel.

25. What / Where / When: Propensity
Your existing data is
more telling than you
give it credit for. You
just have to view it
through a different
lens.

26. What / Where / When: Propensity
Jane
Doe
Other
FIs
The
Greater
Web
Your FI
Other
FIs
Social
Media
Your FI
Website
Search
Search
Payments

27. Propensity Done Well
“A large data analytics project
is like painting a bridge.”
- Deva Annamalai, vice
president and product and
marketing technology
strategist at Zions Bank

28. Setting Goals
Goal is to identify business use cases and
"data recipes" that will help with:
More advanced customer segmentation
capabilities
Providing next-best offer products based on
predictive analytics
Optimize marketing campaign execution

29. The How: Modeling
Combining personas
with propensity
begins to formulate
the model.

31. Tying it together
+
+
= a complete customer view,
true 1:1 marketing

32. 33 touch points needed
to reach one sale!

33. Type of Touch Point Matters
Source Days to Deposit Touch Points
Other 562 42
Referral 241 28
Online 338 35
Marketing Efforts (Direct Mail, Events) 600 29
Media (TV, Newspaper, and Outdoor) 2,189 54

34. Pipeline Time Lapse
Media
I saw your ad on TV.
Traditional Marketing Efforts
I got an invitation in the mail to
your event.
Online Marketing
I looked online for a
retirement community.
Referrals
My friend lives there.
… to point of sale
6 years
1.5 years
12 months
4 months

35. The Lead Base
0
200
400
600
800
1000
1200
1400
FY 15 FY 16 FY 17
"Mature" Leads Over Time
Lost Lead Type Total
Lost Lead Unknown Reason 1,364
Lost Lead No Interest 1,286
Lost Lead Dissatisfied 3
Lost Lead Competitor 249
Total 2,902

36. Reality vs. Perception

37. Lead Generation/Conversion Tracking

38. Data-driven Marketing

39. Marketing Automation: What it is
An incredibly useful tool
A way to build qualified leads
A tool to gather better insights

40. What it is NOT
A way to circumvent a poorly
built website
A self-fulfilling lead generating
platform
A content solution

41. Content Fuels Automation
Your content
defines your
BRAND as its
delivered to
customer
segments based
on propensity in
defined models.

42. Audience-centric Message Maps
Define your content by:
Target audience
Decision cycle
Key goals to influence

43. The Right Content at the Right Time

44. “… we mine Facebook APIs for
likes and interests and look for
overlap. We can find out what
our fans also like.”
- Nate Luman, social marketing
manager at Zappos

45. Data Triggers Content
Average open rate of 43.2%
Average click through rate of 11.6%
Average conversion rate of 6.0%
http://www.telegraph.co.uk/

46. Building a Data-driven Content Plan
Address (Big) Data Analytics
Map the Experience / By Audience
Develop the Content Marketing Matrix

47. Parting thoughts …
Start small
Look at the data you already have
Track, measure, report  REFINE
Then, think big
Recognize content needs in
addressing marketing automation

48. Thank You!
BlueSpire’s Q1 TrendLab Webinar
Recording and Infographic