The document discusses the necessity of integrating customer analytics within the marketing technology stack to enhance customer experiences. It emphasizes the importance of transforming data into actionable insights for better customer engagement, retention, and targeting. The text also highlights the challenges organizations face in adopting measurement and analytics, indicating a need for improved data use and technology solutions to drive more effective marketing strategies.

1. Is the Martech Stack Missing Its Brain?
Transform Your Marketing to Deliver Relevant Customer Experiences
Featuring
Brandon Purcell
Senior Analyst
Forrester Research
Rob Romano
VP of Digital Strategy
NGDATA
WEBINAR

2. 2© 2017 FORRESTER. REPRODUCTION PROHIBITED.
In the Age of the Customer, We Gather
Massive Amounts of Data
• Behavioral data
• Social data
• Mobile data
• Environmental data
• Sensor data
• Transaction data
• Customer data
• Third-party data
• Financial data
• Sales data
• Product data

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Customer Insights are the Gold Buried
Within Your Data

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Key Phases of the Insights Lifecycle
Insights
Action
Data

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“We are drowning in data and
starving for insight.”
— Global Bank

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Customer Analytics Turns Data Into Insights
Customer analytics uses customer data
and analytic insight to design customer-
focused programs that win, serve and
retain customers.

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Customer Analytics is Different. Really.
METHODS DATA TECHNOLOGY
Descriptive
Predictive
• Predictive modeling
• Forecasting
• Simulation
Prescriptive
• Reporting & measurement
• Business intelligence
• Optimization
• Decision arbitration
Internally-sourced, at-
rest, Structured
Externally-sourced,
unstructured
Multi-sourced, in-
motion, multi-structured
Relational
Non-relational
• CRM, EDW, POS, Web
• Social, location, VoC
• Sensor, open data, IOT data,
device data
• Hadoop, noSQL
• Traditional EDWs
Advanced
CustomerAnalytics
Traditional
Analytics

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Source: June 19, 2014, “How Analytics Drives Customer Life-Cycle Management” Forrester report
ENGAGE
ASK
USE BUY
EXPLORE
DISCOVER
The Potential Value for Customer Analytics is Real
Across the Customer Lifecycle

9. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Increase customer engagement
Improve data-driven focus of organization
Improve customer retention
Increase marketing performance
Increase customer acquisition and targeting
Please share the top three drivers that encourage your organization to adopt
measurement and analytics
2017 2016
+13%
-5%
+16%
-1%
+10%

10. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Hiring talent to manage measurement and
analytics
Providing real-time insights to the business
Getting buy-in from business stakeholders on the
value of measurement and analytics
Accessing data from a variety of sources
Ensuring data quality from a variety of sources
Please rank the top three challenges that prevent your organization from
making use of measurement and analytics.
2017 2016
+4%
+7%
-2%
+10%
-1%

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If I only had a
BRAIN…

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A Lot of Insights and
Action, Not Much
Data…
Source: https://www.forrester.com/TechRadar+Marketing+And+Advertising+Technology+Q1+2016/fulltext/-/E-RES115810
Insights
Action
Data

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Technology is the Wrapper for Contextual
Marketing
Source: https://www.forrester.com/report/A+More+Perfect+Union+Adtech+And+Martech+Convergence+Will+Revolutionize+Marketing/-/E-RES135282#figure1

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Why Not Just Go to IT?

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Marketers are Frustrated by a Lack of Agility

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They Want Insight Independence!
Customer
insights
for the marketer
by the marketer

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Unfortunately,
AI Won’t Solve
this Problem

18. The Birds and the Bees of Model Making
Deep
learning
algorithm
Classification
model
Final output:
Newly
classified data
Labeled
data
Training data
Unlabeled
data
Validation data

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In a World of AI, Not Having the Right
Data Could Spell Your Doom

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Yikes! What are Companies
Able to Do Today?

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The State of Customer Analytics Survey
› Fielded by Forrester and Burtch Works to senior-level analytics
professionals in May 2017
› 229 respondents answered the survey in its entirety
› Half of respondents have more than 13 years of measurement and
analytics experience
› Over 67% of respondents are influencers or decision-makers in their
organizations
› Broad industry representation
• 13% Retail
• 9% CPG

22. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
Digital data (e.g. website activity, mobile app
data)
Campaign response data (e.g. open, click,
redemption)
Transactional/POS data (e.g. product purchase
history not linked to customer)
Customer behavior data (e.g. loyalty program
data, identifiable customer data)
Demographic data (e.g. location, family status)
Which of the following data sources do you use to perform
measurement and analytics?
2016 2017
+3%
-2%
-5%
-8%
-3%
Honorable mention: Unstructured voice of
the customer data +5% to 32%
Data Sources

23. 22%
30%
79%
79%
93%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Artificial intelligence (e.g. deep learning, cognitive
analytics)
Real-time/streaming analytics (e.g. recommendation
engines, continuous learning)
Descriptive analysis (e.g. OLAP/analytics with
interactive reporting, trend analysis, driver analysis)
Predictive analysis (e.g. propensity modeling, uplift
modeling)
Basic reporting and measurement (e.g. static reports
or data visualization)
Which of the following types of analytics is your organization using to
inform decision-making? Select all that apply.
Types of Analytics

24. 0% 10% 20% 30% 40% 50% 60% 70% 80%
Customer journey/path analytics
Customer lifetime value analysis
Customer engagement analysis
Customer lookalike targeting
Customer satisfaction analysis
Customer churn/attrition analysis
Response propensity or uplift models
Forecasting models
Behavioral customer segmentation
Test and control methods
Of the following types of customer analytic techniques, which techniques
does your organization currently use or plan to use?
2016 2017
Customer and Marketing Analytics Techniques

25. 24%
25%
29%
29%
30%
0% 5% 10% 15% 20% 25% 30% 35%
Customer lifetime value analysis
Network/graph analysis
Social media analytics
Customer journey/path analytics
Next best action/offer models
Of the following types of customer analytics techniques, which techniques is
your organization planning to use?
Wish List

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Forrester’s Analytics Sophistication Model
Exposed Three Distinct Groups:

27. 19%
34%
48%
28%
23%
49%
26%
37% 37%
0%
10%
20%
30%
40%
50%
60%
Leader Follower Laggard
Analytical sophistication by year
2014 2016 2017
Analytics Maturity Continues to Rise

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How to Become a Leader
› Take an inventory of your customer data sources
› Create an analytics roadmap that leverages these sources
› Build, buy, beg, borrow, or steal yourself a brain!
› Your customer data platform needs to be “by the marketer, for
the marketer”
› Measure and communicate success

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Don’t Be Afraid to Get Your Hands Dirty.

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It Will Be Worth the Effort.

31. The Missing Brain in the Martech Stack

32. Consumers Seek Connected Experiences at Every Micro-Moment

33. …And Brands Need a “Brain” to Drive These Fluid, Superior
Customer Experiences That Meet Customers’ Demand

34. Which can be unpredictable, a guessing game and rarely leads to truly personalized experiences
Without a Brain, We Work in Segments

35. Deliver always-relevant and personalized experiences to every customer
The Brain Removes the Guesswork
Exceed customers’
expectations with
experiences that
wow!

36. THE RIGHT MOMENT
MULTI-CHANNEL
FIRST-PARTY DATA
Deliver an
Omni-Channel
Experience
Integrated, Personalized POS

37. 3RD PARTY DATA
GEO-TARGETING
Get in the Game
Before Your
Competition
Data Enrichment

38. A relevant experience at any point in time
The Connected Experience Leads to
Brand Advocacy
uninterrupted
conversations

39. A relevant experience at any point in time
The Connected Experience Leads to
Brand Advocacy
uninterrupted
conversations

40. How Do You Achieve Advocacy and Connected Experiences?
Bring your 1st, 2nd and 3rd party data together to get a richer understanding of every customer
A seamless,
relevant and
personized
customer
experience

41. The core elements of the Brain
Complete and Real-Time

42. Rule Engines
Reporting Tools
Measurement & Optimization Tools
Scoring Engines
Analytical Workbenches
Data Preparation/Integration/Transformation Tools
Content Management Systems
Identity Graphs
Data Service Providers
Tag Management Systems/Data Management Platforms
Asset Management Systems
Digital Content Optimization Tools
Customer Experience Tools
Dynamic Video Tools
CRM Systems (Branch/Store/Contact Center)
Personalization Engines
Campaign Management Systems
Demand/Supply Side Platforms
Display Advertising Platforms
Today’s Martech Architectures
Contact Platforms
(Email/Web/Mobile/SMS)
Companies are struggling to
leverage the growing amount
of data with fragmented
technologies

43. Lily™: The Brain in the Martech Stack

44. Effectively manage, analyze and deploy multi-source data to power connected experiences
The Brain

45. Next Generation Customer Experiences
Delivering Impressive Results
TRIGGERED MARKETING
NBO / NBA
ADVISOR SUPPORT
CUSTOMER
LOYALTY
OVERALL JOURNEY
SATISFACTION
Targeting Precision
+65%
PERSONALIZED AD
TARGETING
Ad Waste
-58%
Conversions
4-5x
PERSONALIZED
COMMUNICATION
Upsell
+25%
Support Cost
-30%
NPS
+15 pts
Churn Reduction
16%

46. Thank you. Any questions?
Featuring
Brandon Purcell
Senior Analyst
Forrester Research
bpurcell@forrester.com
Rob Romano
VP of Digital Strategy
NGDATA
robertr@ngdata.com